U.S. Department of 

Transportation

Federal Railroad 

Administration

Passenger Train Emergency Systems: Review

of Egress Variables and Egress Simulation 

Models

Office of Research 

and Development

Washington, DC 20590

DOT/FRA/ORD-13/22 Revision A Final Report 

Revised May 2013
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4. TITLE AND SUBTITLE

Passenger Train Emergency Systems: Review of Egress Variables and

 Egress Simulation Models

5. FUNDING NUMBERS

RR 28 DB036

6. AUTHOR(S) RR 93 KB049

 Stephanie H. Markos and John K. Pollard

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

 John A. Volpe National Transportation Systems Center

 Research and Innovative Technology Administration

 U.S. Department of Transportation

 Cambridge, MA 02142-1093

8. PERFORMING ORGANIZATION 

DOT-VNTSC-FRA-12-04

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

U.S. Department of Transportation

Federal Railroad Administration

Office of Research and Development

Washington, DC 20590

10. SPONSORING/MONITORING 

DOT/FRA/ORD-13/22 

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11. SUPPLEMENTARY NOTES

12a. DISTRIBUTION/AVAILABILITY

This document is available to the public through the National Technical Information 

Service, Springfield, VA 22161, and through the FRA Web site at www.fra.dot.gov.

12b. DISTRIBUTION CODE

13. ABSTRACT (Maximum 200 words)

Federal Railroad Administration (FRA) regulations are intended to ensure the safe, timely, and effective evacuation of 

intercity and commuter rail passengers when necessary during passenger train emergencies. Although it is recognized 

that during the majority of emergency scenarios, it is much safer for passengers to remain on the train, it may be 

necessary for passengers and crew to evacuate a passenger train quickly, due to certain life-threatening conditions (e.g., 

fire).

FRA is sponsoring a research program to investigate a variety of emergency evacuation concepts, strategies, and 

techniques for applicability to passenger trains operating in the United States.

One aspect of the FRA research program is directed at evaluating the potential applicability to passenger trains of 

performance-based criteria specifying minimum necessary evacuation times. No methodology currently exists for 

evaluating the passenger rail car emergency egress system as a whole, or the effects on egress times of failures within 

this system. 

This report presents the results of a review of passenger rail car egress variables and evaluation of the potential 

application of computer models that simulate egress for developing passenger train evacuation times. 

14. SUBJECT TERMS

Egress computer models, egress simulations, emergency egress, emergency evacuation, 

emergency preparedness, exits, Federal Railroad Administration, passenger rail, passenger 

trains, railroads, transportation 

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96

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ii

METRIC/ENGLISH CONVERSION FACTORS

ENGLISH TO METRIC METRIC TO ENGLISH

LENGTH (APPROXIMATE) LENGTH (APPROXIMATE)

1 inch (in) = 2.5 centimeters (cm) 1 millimeter (mm) = 0.04 inch (in)

1 foot (ft) = 30 centimeters (cm) 1 centimeter (cm) = 0.4 inch (in)

1 yard (yd) = 0.9 meter (m) 1 meter (m) = 3.3 feet (ft)

1 mile (mi) = 1.6 kilometers (km) 1 meter (m) = 1.1 yards (yd)

1 kilometer (km) = 0.6 mile (mi)

AREA (APPROXIMATE) AREA (APPROXIMATE)

1 square inch (sq in, in2) = 6.5 square centimeters (cm2) 1 square centimeter (cm2) = 0.16 square inch (sq in, in2)

1 square foot (sq ft, ft2) = 0.09 square meter (m2) 1 square meter (m2) = 1.2 square yards (sq yd, yd2)

1 square yard (sq yd, yd2) = 0.8 square meter (m2) 1 square kilometer (km2) = 0.4 square mile (sq mi, mi2)

1 square mile (sq mi, mi2) = 2.6 square kilometers (km2) 10,000 square meters (m2) = 1 hectare (ha) = 2.5 acres

1 acre = 0.4 hectare (he) = 4,000 square meters (m2

)

MASS - WEIGHT (APPROXIMATE) MASS - WEIGHT (APPROXIMATE)

1 ounce (oz) = 28 grams (gm) 1 gram (gm) = 0.036 ounce (oz)

1 pound (lb) = 0.45 kilogram (kg) 1 kilogram (kg) = 2.2 pounds (lb)

1 short ton = 2,000 pounds = 0.9 tonne (t) (lb) 1 tonne (t) =

=

1,000 kilograms (kg)

1.1 short tons

VOLUME (APPROXIMATE) VOLUME (APPROXIMATE)

1 teaspoon (tsp) = 5 milliliters (ml) 1 milliliter (ml) = 0.03 fluid ounce (fl oz)

1 tablespoon (tbsp) = 15 milliliters (ml) 1 liter (l) = 2.1 pints (pt)

1 fluid ounce (fl oz) = 30 milliliters (ml) 1 liter (l) = 1.06 quarts (qt)

1 cup (c) = 0.24 liter (l) 1 liter (l) = 0.26 gallon (gal)

1 pint (pt) = 0.47 liter (l)

1 quart (qt) = 0.96 liter (l)

1 gallon (gal) = 3.8 liters (l)

1 cubic foot (cu ft, ft3) = 0.03 cubic meter (m3) 1 cubic meter (m3) = 36 cubic feet (cu ft, ft3)

1 cubic yard (cu yd, yd3) = 0.76 cubic meter (m3

) 1 cubic meter (m3

) = 1.3 cubic yards (cu yd, yd3

)

TEMPERATURE (EXACT) TEMPERATURE (EXACT)

[(x-32)(5/9)] °F = y °C [(9/5) y + 32] °C = x °F

QUICK INCH - CENTIMETER LENGTH CONVERSION

0 1 2 3 4 5

Inches

Centimeters 0 1 2 3 4 5 6 7 8 9 10 11 12 13

QUICK FAHRENHEIT - CELSIUS TEMPERATURE CONVERSIO

 -40° -22° -4° 14° 32° 50° 68° 86° 104° 122° 140° 158° 176° 194° 212°

 

°F

 °C -40° -30° -20° -10° 0° 10° 20° 30° 40° 50° 60° 70° 80° 90° 100°

For more exact and or other conversion factors, see NIST Miscellaneous Publication 286, Units of Weights and Measures. 

Price $2.50 SD Catalog No. C13 10286

Updated 6/17/98
iii

ACKNOWLEDGMENTS

Funding and direction of the passenger rail emergency preparedness research program has been 

provided by Kevin Kesler, Chief, Equipment and Operating Practices Division, Office of 

Research and Development, Federal Railroad Administration (FRA), United States Department 

of Transportation (U.S. DOT). 

Melissa Shurland, FRA Rail Energy, Environment, and Engine (E3) Technology Research 

Program Manager; Jeff Gordon, FRA Occupant Protection Program Manager; Eloy Martinez, 

former Manager, FRA Occupant Protection Program; and Brenda Moscoso, FRA Railroad 

Safety Advisory Committee (RSAC) Emergency Preparedness Task Force Leader, FRA Office 

of Safety; reviewed and provided technical comments for the final draft report. In addition, 

Suzanne Horton, of the Systems Engineering and Safety Division, John A. Volpe National 

Transportation Systems Center (Volpe Center), Research and Innovative Technology 

Administration (RITA)/U.S. DOT, provided review and comments for the final draft report.

Claire Orth, former Chief, Equipment and Operating Practices Division, FRA; and N. Thomas 

Tsai, former Manager, FRA Occupant Protection Program, provided initial specific research 

program direction. 

The contents of this report are based on a review of egress variables and models which simulate 

egress from structures originally completed by staff of Hughes Associates, under contract to the 

Volpe Center in 2003. However, the previously prepared report by Hughes Associates has been 

substantially reorganized, revised, and updated by Volpe Center staff. Accordingly, although 

Hughes Associates staff reviewed the final draft of this report and provided technical review 

comments, as well as new or updated information for certain egress models, the findings in this 

published report are the responsibility of Volpe Center staff.

In addition, Garnett (Mac) MacLean, Civil Office of Aviation Medicine, Federal Aviation 

Administration, U.S. DOT, provided technical peer review and comments for the final draft 

report.

Finally, Robert Gaumer, formerly of Chenega Advanced Solutions and Engineering, LLC

(CASE) provided extensive editorial review and reorganization of the initial Hughes draft report;

Barbara Siccone, formerly of CASE, provided extensive formatting and typing support for the 

draft final report; Cassandra Oxley, MacroSys, LLC, and Chinenye Okparanta, Hawley-Thomas 

Enterprises, Inc., provided editorial review of this final report. Ms. Okparanta prepared the 

report for FRA Web publication.
iv

CONTENTS

EXECUTIVE SUMMARY ............................................................................................................ 1

1. INTRODUCTION .............................................................................................................. 3

1.1 Purpose and Scope .................................................................................................. 3

1.2 Objectives ............................................................................................................... 4

1.3 Background............................................................................................................. 4

1.3.1 U.S. DOT Prescriptive Vehicle Egress Design Requirements ................... 4

1.3.2 Performance-Based Vehicle Design Requirements.................................... 4

1.4 Technical Approach................................................................................................ 5

1.5 Report Organization................................................................................................ 6

2. EMERGENCY EGRESS TIME......................................................................................... 7

2.1 Literature Review.................................................................................................... 7

2.2 Passenger Rail Car Emergency Egress Time Prediction ........................................ 7

2.3 Emergency Egress Time Performance Criteria....................................................... 7

2.4 Egress Time Studies................................................................................................ 8

2.4.1 Passenger Rail Car Studies ......................................................................... 9

2.4.2 Aircraft Evacuation Studies...................................................................... 14

2.4.3 Bus Evacuation Studies............................................................................. 16

2.4.4 Other Related Studies ............................................................................... 17

2.5 Effects of Smoke and Emergency Lighting and Exit Marking Systems .............. 18

2.6 Summary............................................................................................................... 19

3. PASSENGER RAIL CAR EGRESS TIME VARIABLE FACTORS ............................. 20

3.1 Rail Car Geometry and Configuration.................................................................. 20

3.2 Operating Environment......................................................................................... 22

3.3 Rail Car Orientation.............................................................................................. 23

3.4 Occupant Characteristics ...................................................................................... 23

3.5 Train Crew, Passenger, and Emergency Responder Actions................................ 24

3.6 Fire and Smoke and Other Hazardous Conditions................................................ 25

3.7 Potential Variables for Egress and Time Estimates.............................................. 25

3.8 Summary............................................................................................................... 26

4. METHODS FOR PREDICTING PASSENGER RAIL CAR EGRESS TIME ............... 27

4.1 Prescriptive Specifications and Standards............................................................ 27

4.2 Egress Time Estimates Using Models .................................................................. 27

4.2.1 Hydraulic Models – Theory and Methods................................................ 27

4.2.2 Egress Computer Models.......................................................................... 30

4.3 Passenger Rail Car Egress Time Simulation ........................................................ 33

4.4 Summary............................................................................................................... 34
v

CONTENTS

5. APPLICABILITY OF EGRESS COMPUTER MODELS TO PASSENGER RAIL 

CAR EMERGENCY SCENARIOS ................................................................................. 35

5.1 Existing Egress Computer Models........................................................................ 35

5.2 Features and Capabilities of Existing Egress Computer Models.......................... 41

5.3 Application of Computer Models to Rail Car Egress Scenarios........................... 41

5.3.1 Egress to Adjacent Car or Station Platform (Including Fire) ................... 46

5.3.2 Egress to ROW (Track) Level .................................................................. 46

5.4 Egress from Rail Cars that Have Overturned Onto Their Sides........................... 48

5.5 Model References ................................................................................................. 49

6. POTENTIAL COMPUTER MODEL INPUTS FOR PASSENGER RAIL CAR 

EGRESS TIME ESTIMATION ....................................................................................... 58

6.1 Egress Scenarios ................................................................................................... 58

6.2 Input Data for Estimating Egress Time ................................................................ 61

6.2.1 Input Data for Hydraulic Models.............................................................. 61

6.2.2 Input Data for Individual-Movement Computer Models.......................... 63

6.3 Summary............................................................................................................... 65

7. SUMMARY...................................................................................................................... 66

7.1 Overview............................................................................................................... 66

7.2 Emergency Egress Variables ................................................................................ 66

7.3 Egress Time Prediction and Use of Egress Computer Models............................. 66

8. REFERENCES ................................................................................................................. 69

APPENDIX: Bibliography.................................................................................79
vi

ILLUSTRATIONS

Figure 1. Hydraulic Model – Simple Example ............................................................................ 30

Figure 2. Individual-Movement Model – Simple Example......................................................... 32
vii

TABLES

Table 1. Volpe Center 2005 and 2006 Egress Experiment Results............................................... 9

Table 2. Comparison of Rail Car Egress Rates – Recent Experiments....................................... 14

Table 3. Overview of Current Egress Computer Models ............................................................ 36

Table 4. Key Features of Egress Computer Models in Relation to Passenger Rail Car Egress

 Scenarios...................................................................................................................... 42

Table 5. Passenger Rail Car Emergency Egress Scenarios.......................................................... 59

Table 6. Potential Input Data for Calculating Egress from Upright Passenger Rail Cars........... 62

Table 7. Potential Input Data for Hydraulic and Individual-Movement Models......................... 64
1

EXECUTIVE SUMMARY

U.S. intercity passenger and commuter rail train system operators have maintained a very good 

safety record, and the number of passenger trains involved in accidents or other emergency 

situations is low. The majority of passenger train emergencies are usually resolved quickly and 

evacuation from the train is not necessary since passengers are generally safer if they remain on 

the train. Nevertheless, emergency situations continue to occur and, at times, they result in 

occupant casualties. In certain cases, the delay, difficulty, or inability of passengers and crew to 

evacuate the train can contribute to the number and severity of casualties.

The majority of Federal Railroad Administration (FRA), U.S. Department of Transportation 

(U.S. DOT) regulations for passenger train emergency systems are specified in Title 49, Code of 

Federal Regulations (49 CFR), Part 238, Passenger Equipment Safety Standards and Part 239, 

Passenger Train Emergency Preparedness. The intent of the FRA regulations is to ensure the 

safety of intercity and commuter rail passengers and crew, as well as the safe, timely, and 

effective evacuation of passenger trains when necessary during emergencies. 

FRA’s Office of Research and Development is sponsoring an ongoing research program that is 

investigating how to enhance the safety of passengers and crew during passenger train 

emergencies. One aspect of the FRA research program is directed at evaluating the potential 

applicability to passenger trains of performance-based criteria which specify evacuation times. 

Emergency egress from a passenger train is a complex process that depends on a number of 

dynamic factors and conditions. Many variables that affect the time necessary for passengers to 

exit from a passenger train in an unusual or emergency situation must be considered. 

No methodology currently exists for evaluating the passenger rail car emergency egress system 

as a whole, or the effects on egress times of failures within this system. 

Several methods have been used to establish transportation vehicle occupant egress time: 

1) hydraulic hand-calculation and analysis, based on the number of occupants and simple exit 

routes; 2) simulated emergency evacuations or egress experiments, during which occupants exit

from the actual vehicle; or 3) analysis using an egress computer model. Building occupant 

egress data are readily applicable for use with these available analytical tools for estimating 

emergency egress times. However, none of the building egress models have been validated 

using actual passenger rail car occupant data. In addition, individual agility and physical 

obstacles have a significant impact on the amount of time necessary for persons to exit from a 

passenger rail car, depending on its location. 

Various existing egress models were evaluated for their capability to predict the time necessary 

to evacuate U.S. passenger rail cars under various emergency conditions. Passenger car egress 

variables were also reviewed to determine their usefulness as data inputs to an egress computer 

model. Passenger rail car designs were reviewed, representative evacuation scenarios were 

developed, and necessary data inputs were identified for modeling purposes.

With adaptation, certain egress simulation computer models could be expected to provide 

reasonable predictions of necessary egress times for different passenger rail car types with the 
2

rail car upright and passengers exiting either from one upright car to the adjacent car, onto high 

or low station platforms, or to the right-of-way (ROW). 

Data from actual passenger rail car egress experiments provide a key means, when combined 

with known physical characteristics of each type of individual, physical characteristics of the rail 

car, and the operating environment at the time the data were recorded, to validate egress time 

predictions for upright cars generated by these egress simulation computer models. However, 

because of the inherent risk of injury to participants, passenger rail car egress experiments that 

provide egress-related time data involving higher-risk emergency scenarios (egress from cars 

overturned or extremely tilted on their sides, egress from exit windows, egress of severely 

mobility-impaired occupants, etc.) to validate the egress models may not be feasible. 
3

1. INTRODUCTION

U.S. intercity passenger and commuter rail train system operators have maintained a very good 

safety record, and the number of passenger trains involved in accidents or other emergency 

situations is low. The majority of passenger train emergencies are usually resolved quickly and 

evacuation from the train is not necessary since passengers are generally safer if they remain on 

the train. Nevertheless, emergency situations continue to occur and, at times, they result in 

occupant casualties. In certain cases, the delay, difficulty, or inability of passengers and crew to 

evacuate the train can contribute to the number and severity of casualties.

The majority of Federal Railroad Administration (FRA), U.S. Department of Transportation 

(U.S. DOT) passenger rail equipment regulations related to emergency systems are specified in 

Title 49, Code of Federal Regulations (49 CFR), Part 238, Passenger Equipment Safety 

Standards [1] and Part 239, Passenger Train Emergency Preparedness [2]. The intent of these 

requirements is to ensure the safety of intercity and commuter rail passengers. FRA first issued 

extensive emergency preparedness and emergency system equipment regulations in 1998 and 

1999 [3] [4]. FRA issued subsequent revisions to these regulations, most recently in 2008 [5]. 

In early 2012, FRA also indicated the intent to further revise the regulations to further enhance 

passenger and train crew safety during emergency situation in a new notice of proposed 

rulemaking [6].

The FRA Office of Research and Development has sponsored an ongoing research program that 

is investigating a variety of emergency evacuation concepts, strategies, and techniques for 

applicability to U.S. passenger trains and to assist in further enhancing emergency systems 

requirements specified in Part 238 [1] and Part 239 [2]. As part of the FRA research program, 

the John A. Volpe National Transportation Systems Center (Volpe Center), Research and 

Innovative Technology Administration (RITA), U.S. DOT is assisting FRA in evaluating the 

potential feasibility of specifying performance-based criteria for passenger rail car egress times. 

No methodology currently exists for evaluating the passenger rail car emergency egress system 

as a whole, or the effects on evacuation times of failures within systems. 

1.1 PURPOSE AND SCOPE

The purpose of the study described in this report is to assist FRA in evaluating the applicability 

of performance-based minimum evacuation time standards for passenger rail cars to supplement 

existing prescriptive regulations for emergency exits and related emergency systems. The study 

scope focused on the potential application of computer models to predict U.S. passenger rail car 

egress times. With adaptation, egress computer models could potentially provide reasonable 

estimates of the minimum egress times necessary for different rail car types with the rail car 

upright with passengers exiting from one car to the next adjacent car, out onto a station high or 

low platform location, or to the right-of-way (ROW). Although more difficult, it may also be 

feasible to provide passenger egress time estimates for when the rail car is not in an upright 

position.
4

1.2 OBJECTIVES

Various existing egress models were evaluated for their capability to predict the time necessary 

to evacuate U.S. passenger rail cars under various emergency conditions. Passenger car egress 

variables were also reviewed to determine their usefulness as data inputs to an egress computer 

model. Passenger rail car designs were reviewed, representative evacuation scenarios were 

developed, and necessary data inputs were identified for modeling purposes.

1.3 BACKGROUND

1.3.1 U.S. DOT Prescriptive Vehicle Egress Design Requirements

FRA [1] [2], the Federal Aviation Administration (FAA) [7], and the U.S. Coast Guard

(USCG) [8], respectively, require that passenger rail cars, commercial passenger aircraft, and 

passenger ships comply with extensive prescriptive emergency egress-related design 

requirements for the number, type, location, identification, and operation of emergency exits; and 

the type, location, operation, and duration of emergency lighting. The National Highway Traffic 

Safety Administration (NHTSA) also requires that large buses and school buses comply with 

specific emergency exit requirements depending on the type and size of the bus, but does not 

currently require emergency lighting [9]. The general principle, whatever the type of public 

transportation vehicle, is that provision of clearly identified emergency exits that are easily 

operable will allow occupants during an emergency to effectively and efficiently evacuate, when 

necessary, to a point of safety.

1.3.2 Performance-Based Vehicle Design Requirements

A “performance-based” systems approach to emergency egress recognizes that addressing one 

aspect of the “system” in isolation does not always yield the best outcome for the desired 

objective of occupant safety. For example, the time necessary for passenger train crew decisionmaking and providing instructions to passengers may have a greater influence on passenger 

evacuation from a passenger car in an emergency than the number, type, location, and operation

of emergency exits. Accordingly, since it is usually safer for passengers, due to other hazards 

such as passing trains, to remain on board the train during the majority of emergencies, focusing 

only on passenger rail car exits could result in a lower level of passenger safety. 

As previously noted, FRA,* FAA, and USCG regulations specify prescriptive design 

requirements related to emergency exits and related emergency systems for passenger rail cars, 

commercial aircraft, and passenger ships. In addition, FRA, FAA, and USCG regulations 

contain minimum requirements for the proper training of crews in procedures to evacuate 

passengers during emergency situations.

 

* As of the date of the original report (April 2013), FRA requires emergency lighting only for new 

equipment ordered on or after September 8, 2000, or placed in service for the first time on or after 

September 9, 2002.
5

However, aircraft and ships are currently the only U.S. public transportation vehicles specifically 

required to demonstrate emergency evacuation time capability. FAA requires that transport 

aircraft carrying more than 44 passengers be shown to be capable of being evacuated in 

90 seconds or less [10]. USCG requires that, when transporting passengers in international 

waters, U.S.-registered ships comply with International Maritime Organization (IMO) 

guidelines [11] specifying completion of an evacuation analysis which demonstrates that a ship 

can be evacuated within 60 minutes. The IMO guidelines have been established in recognition 

of the hazards (e.g., fire, hull damage, etc.) likely to be encountered in maritime operations, as 

well as the availability and effectiveness of emergency exits, associated safety equipment, and 

life support systems. 

U.S. DOT agencies do not currently specify emergency evacuation time requirements for buses 

or passenger trains.

Extensive egress time studies have been conducted for a range of public structures, from highrise office buildings to stadiums and mass transit stations. In addition, FAA sponsored and 

conducted several emergency evacuation studies, which are further discussed in Chapter 2. 

1.4 TECHNICAL APPROACH

Volpe Center developed the following work plan to investigate the feasibility of using egress 

computer models to evaluate how quickly passengers and crew are able to evacuate passenger 

rail cars in various emergencies:

Task 1: Review and evaluate literature on existing public transportation vehicle 

requirements, research studies, and existing publicly available egress models for applicability 

to passenger rail car egress. In addition, emergency egress time considerations will be 

identified. Egress models will be evaluated for their potential applicability to passenger rail 

cars. A series of likely emergency egress scenarios will be identified, along with necessary 

critical data inputs.

Task 2: Design and conduct a series of egress experiment “trials” using: different types of 

passenger rail cars; a variety of participants, in multiple scenarios; and, if feasible, lowambient (i.e., emergency) light conditions. These trials will provide actual data for analysis 

of the selected scenarios identified in Task 1.

Task 3: Develop an egress computer model including: related modeling tools for different 

types of passenger rail car geometries and emergency scenarios. Significant occupant 

behaviors and times based on the results of Tasks 1 and 2 will be used as inputs to the model. 

Model test, evaluation, documentation, and validation will be completed. 

Task 4: Using the completed egress computer model, develop a library containing U.S. 

passenger rail car geometries, as well as time estimates for occupant egress from individual 

rail cars and complete trainsets (and consists), using a variety of exits and exit routes.

This report presents the results of Task 1. The results of Task 2 are summarized in a research 

brief published by FRA [12], and more extensively described in another Volpe Center-prepared 

report, published by FRA in 2012, which describes single-level commuter rail car egress 

experiments conducted in 2005 and 2006 [13]. The results of the egress computer model 

development (Task 3) are expected to be published by FRA in 2013. Task 4 is still in progress. 
6

1.5 REPORT ORGANIZATION

Chapter 2 summarizes the results of an international literature review of egress time prediction 

research. 

Chapter 3 summarizes the results of a review of selected National Transportation Safety Board 

(NTSB) investigations of accidents involving passenger rail car emergency egress and discusses 

egress time variables. 

Chapter 4 summarizes current methods for predicting passenger rail car egress times. 

Chapter 5 presents the results of a review of the types and capabilities of existing egress

computer models and discusses their applicability to typical passenger train emergency egress 

scenarios. 

Chapter 6 describes various rail car emergency scenarios for potential egress modeling studies 

and identifies potential data inputs for egress computer models. 

Chapter 7 contains a summary of the report. 

The Appendix contains a bibliography of selected U.S. transportation modal agency and selected 

international regulatory organization regulations, research, and guidelines related to public 

transportation vehicle emergency egress.
7

2. EMERGENCY EGRESS TIME

2.1 LITERATURE REVIEW

A follow-up literature review was performed to supplement preliminary searches previously 

conducted by Volpe Center staff (and Hughes Associates in 2003) in order to identify research 

conducted for human behavior and crowd characteristics potentially relevant to passenger rail car 

egress variables and emergency evacuation. 

The literature review identified only a few studies that specifically focus on passenger train 

evacuation. However, documents relevant to specific aspects of passenger rail car emergency 

egress were identified, including variables that affect egress time. These are discussed in the 

remainder of this chapter. The Appendix contains a bibliography of selected U.S. transportation 

modal agency and selected international transportation vehicle regulations, research, and 

guidelines related to public transportation emergency evacuation. (An extensive list of other 

documents describing a variety of egress computer models is contained in Chapter 5.) 

2.2 PASSENGER RAIL CAR EMERGENCY EGRESS TIME PREDICTION

The typical means to establish transportation vehicle occupant egress times has been to conduct 

simulated emergency evacuations or egress experiments, during which occupants exit from the 

actual vehicle. However, such “demonstrations” have significant cost, as well as safety and 

health issues. The safety issues include slipping, tripping, or falling by the participants. A major 

challenge to conducting a valid test of egress behavior and safety features is how to create a 

realistic test without putting individuals at significant risk of injury. Consequently, the use of 

analytical methods, such as computer models that have been developed to simulate egress 

behavior, could reduce the number of actual egress tests that need to be performed to determine 

egress times for various passenger rail car designs. These models can make use of actual 

occupant egress rates (data inputs) obtained from prior egress studies and vehicle evacuation 

certification trials. In addition, using an egress computer model may permit many more 

passenger rail car emergency egress system designs to be evaluated in a far shorter time period 

and at less cost than lengthy and complicated hand-recorded data and subsequent calculations.

The development of an analytical methodology to predict the minimum necessary egress time for 

passengers and crew from a passenger rail car to a point of safety could provide a tool to evaluate 

the performance of specific egress design features within the design of the overall “emergency 

egress system” for a representative set of emergency egress scenarios.

2.3 EMERGENCY EGRESS TIME PERFORMANCE CRITERIA

An emergency egress performance criterion for passenger rail cars could be that the minimum 

time necessary for passengers to exit from the rail car (i.e., necessary egress time) must be 

shorter than the available emergency egress time. (Available egress time is defined as the time 

provided by the materials and design of the car before the interior of the car becomes untenable 

due to fire, smoke, or other hazardous conditions.) 
8

Therefore, an appropriate safety criterion for a passenger rail car could be that the minimum 

available egress time must be longer than its actual necessary emergency egress time. This 

safety criterion is important, especially in the FRA progression from prescriptive safety design 

standards for passenger train safety toward performance-based standards. Thus, it is critical to 

determine both the minimum necessary egress time period required by occupants to exit from 

passenger rail cars of any design, as well as the minimum available time to evacuate the rail car 

safely when necessary. 

2.4 EGRESS TIME STUDIES

Although theoretical evacuation time studies for passenger trains have been developed by 

consultants for the Amtrak Acela Express high-speed intercity passenger rail trainset cars [14] 

and MARC commuter rail passenger cars [15] (see Chapter 4), very few passenger rail car egress 

time estimates are based on actual evacuation times since these data are often not publicly 

available. As a result, the majority of theoretical passenger rail car egress time studies that have 

been previously conducted rely primarily on building occupant egress flow rate estimates. 

Accordingly, a limited number of scientifically designed experiments using a human factors 

“systems” approach, are available to provide actual egress time data for evacuation from 

passenger rail cars. Thus, it is not currently possible to have the same level of confidence in 

emergency egress data and time predictions for passenger train emergency evacuation as those 

calculated for buildings, aircraft, or ships. Moreover, the differences between the passenger train 

operating environment related to emergency egress and the emergency egress environment of 

buildings, aircraft, passenger ships, and buses, as well as occupant characteristics and behaviors,

may all contribute to significant differences in exit path routes taken and other egress behaviors 

of occupants, and thus alter the actual necessary egress times.

As part of the FRA-sponsored occupant safety research program, a series of fire hazard analyses 

using a modified version of a fire growth zone compartment computer model was conducted. 

This fire growth model was configured to generate a series of fire performance design curves, 

based on heat release rate (HRR), to determine untenable (e.g., life-threatening) conditions and 

egress times for three intercity passenger rail car types [16]. Although proof of concept for the 

computer fire modeling application to passenger rail cars was demonstrated, calculations of the 

minimum necessary egress times were based on a theoretical average (based on building and 

aircraft data) for all passengers using the rail car end doors as the preferred evacuation route to 

go from one car to the next, under nonpanic “fire drill” conditions. (For example, the egress time 

for 72 passengers to exit a single-level coach was calculated as 88 seconds.) Egress times for 

other egress scenarios, such as using side doors to exit from the rail car to a high-platform 

station, or down steps to the right-of-way (ROW) track bed using stairway steps, were not

calculated. 

Reliable actual egress flow rate data for occupants using the passenger rail car end doors, as well 

as side doors to other egress locations (e.g., high- and low-platform locations and the ROW) 

could increase confidence in the accuracy of the predicted minimum necessary egress times 

versus actual occupant egress times. 
9

2.4.1 Passenger Rail Car Egress Studies

2.4.1.1 Volpe Center Egress Experiments

Volpe Center staff conducted a series of passenger rail car egress experiments using a singlelevel commuter rail car. The experiments were conducted in 2005 and 2006 and detailed results 

are described in Reference [13]. In the 2005 experiment, which was conducted at a highplatform station, 84 participants exited under either emergency or normal lighting conditions

from the rail car to either an adjacent car or to the station platform, using either one or two side 

doors. To the authors’ knowledge, the 2005 commuter rail car experiment was the first time that 

U.S. passenger rail car egress time trials were conducted with regular commuter rail passengers 

as “test” participants. 

Two follow-up experiments were conducted by Volpe Center staff in 2006. The experiments 

consisted of a series of more limited egress trials for 15 and 17 Volpe Center individuals, 

respectively, who exited from one commuter rail car side door using the stairway step, either to 

the ROW (track level) using a step box, or to a paved surface simulating a low-platform station. 

The Volpe Center egress experiment data were collected to assist in establishing estimates and 

norms for passenger rail car egress times and to evaluate various aspects of car design that may 

impede prompt emergency evacuation. 

Participant egress flow times in terms of persons per second (pps) (persons per minute (ppm)) 

varied significantly by the number of door exits used and the exit route taken from the commuter 

rail cars. The results are summarized in Table 1.

Table 1. Volpe Center 2005 and 2006 Egress Experiment Results

EGRESS 

PATH ROUTE

AVERAGE 

ELAPSED TIME TO

FIRST PERSON OUT 

(s)

AVERAGE 

FLOW RATE 

PER DOOR#

(pps / ppm)

High platform / adjacent car 5 0.88 / 52##

Side-door stairway to low platform 6 0.70 / 41

Side-door stairway to ROW 9 0.34 / 20

# Representative of best-case conditions which do not reflect actual emergency conditions

## Values are rounded 

It is emphasized that the 2005 Volpe Center commuter rail experiment egress trials were 

conducted under most favorable conditions to establish a baseline for egress computer model 

calibration verification and for comparisons with the 2006 egress trials, which were conducted 

under conditions that would more closely approximate an emergency scenario requiring 

evacuation to a location other than a high-platform station. 
10

2.4.1.2 British Passenger Train Studies

The Railway Safety and Standards Board (RSSB), United Kingdom (UK), was established to 

carry out research and develop rail industry-wide standards for the national railroad network, 

following the privatization of passenger train operations in the UK. In particular, RSSB 

sponsored a number of studies to respond to a 1999 passenger train accident that resulted in 

numerous casualties, including 29 deaths [17]. These studies included the performance of 

passenger rail vehicle evacuation time exercises and the development of a “Stay or Go” 

evacuation risk model to estimate the probability of fatalities and injuries to passengers if they 

evacuated a passenger train or remained on the train under various emergency scenarios. The 

2002 report documenting the results of the risk model study indicated that in the majority of 

cases, it was safer for passengers to remain on the train rather than be evacuated 

immediately [18]. 

Evacuation experiments conducted for Virgin Railways in 2001 and 2003 became the basis for 

inclusion of requirements in a RSSB Railway Group Standard [19], which specifies that the total 

evacuation time to a high platform must not exceed 90 seconds, with a minimum egress flow rate 

of 40 ppm (0.67 pps). For evacuation to the track level from an end door, the minimum required 

egress flow rate is 30 ppm (0.5 pps). For example, the required evacuation times for a fullyloaded car with 100 seated passengers would be 149 and 200 seconds (2.5 to 3 minutes), to the 

high-platform and ROW (track level) locations, respectively. 

In addition, the RSSB commissioned two projects that analyzed passenger train escape and 

evacuation data and included recommendations for the specific types of human factors data to be 

collected during accident investigations [20] [21]. An extensive appendix contains examples of 

the detailed human factors data considered necessary to obtain during accident investigations.

In 2000, the First Great Western Rail company conducted an experiment using four passenger 

rail cars that simulated an evacuation due to a fire on board a stopped high-speed train [22]. 

More than 100 persons took part in the simulation, including children and individuals with 

mobility impairments. The exercise was designed to test the effectiveness of existing safety 

measures, such as information notices, lighting, and other emergency procedures, as well as 

measures being considered for the future. Smoke was used and normal lighting was turned off. 

However, detailed information for evacuation time or egress flow rates is not publicly available.

In 1999, the University of Greenwich conducted two full-scale experiments involving 

noncompetitive (e.g., orderly) evacuation of 32 persons from the open end doors of an 

overturned “standard” passenger rail car having a seated capacity of 62 persons, with and 

without theatrical smoke [23]. The participants were positioned lying down in the car to 

simulate their having fallen out of their seats. (The occupants had been told beforehand during 

both experiments that one end door would be unavailable but not which one.) During the first 

trial, the average occupant flow rate was 8.7 ppm (0.15 pps), with a total time estimate of 3 

minutes and 34 seconds for 62 persons to evacuate the car, using both ends of the car; and a time 

estimate of 7 minutes and 8 seconds, with only one car end used. During the second experiment, 

which introduced nontoxic smoke into the car, the average occupant flow rate was 5 ppm (0.08 

pps) from one end of the car, with a time estimate of 13 minutes and 19 seconds to evacuate the 

full load of 62 passengers. Smoke was found to slow the egress flow rate because of visual 

obscuration. However, egress time was shortened by increasing the number of train crew 
11

overseeing the evacuation, as well as the removal of interior dividers in the rail car. Study 

recommendations included: provision of internal doors that slide open from both directions; an 

escape hatch in the car roof; airline style luggage compartments to contain luggage; and “popout” windows to make access by rescue personnel easier and permit possible escape by

passengers.

A 1997 conference paper discussed criteria for the design and evaluation of passenger train 

emergency evacuation exercises from a human factors perspective [24]. A major point of the 

paper stated that the accuracy of predictions for crowd control is dependent on proper crowd 

management. The paper also stated the importance of testing public response and behavior, as 

well as the interactive effects of emergency systems, procedures, and staff training, rather than 

just incorporating predicted crowd behavior into the emergency plan. 

A 1994 conference paper addresses the importance of using a technical model to estimate 

evacuation times for passenger rail vehicles during an accident occurring in a tunnel [25]. The 

study concludes that the model should provide a means to quantify evacuation time from a 

passenger rail car by understanding the movement of passengers during a crisis situation and that 

the model should be validated against known accident scenarios. No particular model is 

recommended for passenger rail car evacuation, but the importance of a mathematical model is 

stated.

In 1991, evacuation experiment trials were conducted by the Cranfield Institute (now University 

of Cranfield), UK, for a single British Mark III passenger rail coach with 76 seats, to evaluate the 

egress times with different passenger loads during noncompetitive and competitive evacuations 

for an intercity car [26] [27] [28]. Noncompetitive evacuation is defined as orderly movement 

(i.e., without high motivation and with no pushing) to an exit by occupants. In contrast, 

competitive evacuations are not orderly and can be induced by the immediate threat to oneself or 

family members in an actual emergency or, in the case of experiments, by financial reward. The 

participants were mostly students, who were paid ₤10 (about $18 in 1991) for attendance with an 

additional ₤5 (about $9 in 1991) if they were among the first half of the subject pool to exit

during the competitive trials. 

Passengers were allowed to evacuate through all doors on one side of the vehicle onto a station 

platform. In the fully-loaded trials (76 seated participants), egress to a high platform through the 

side doors was completed in 53 seconds in the noncompetitive trials and 39 seconds in the 

competitive trials. These times imply egress flow rates of 43 and 58 ppm (0.72 and 0.97 pps) per 

door, respectively. Competitive evacuation times were faster than noncompetitive evacuations at 

100 percent of seating capacity. However, when a trial was attempted with 103 persons

(135 percent of capacity), injuries occurred and the trial was stopped at the point at which only 

89 individuals had exited. This increase in injury potential with high-passenger densities in 

competitive conditions is consistent with aircraft evacuation study results. The study report also 

discusses certain aspects of passenger rail car geometry and the operating environment that may 

affect evacuation, including interior features, such as barriers, drop-down tables, and armrests,

and provides related recommendations on how to improve evacuation. 
12

2.4.1.3 Austrian Passenger Train Study

The Austrian National Railways (ÖBB), in conjunction with Vienna University of Technology,

conducted two evacuation trials for a new commuter rail car type using three cars, which are 

described in a 2007 report [29].

**

 The center car had two sets of side doors, while the end cars

had one set of side doors. Both trials involved the same 192 persons and the use of nontoxic 

smoke located in different areas of the train, which was assumed to be moving. One trial 

simulated a train on the normal ROW while the second simulated a train in a tunnel. The closed 

car doors were opened after 2 minutes to permit people to exit onto the ground or platform for 

which there was a drop of about 26 in (65 cm). In the first trial, the smoke was generated in a 

toilet in one of the end cars; after 2 minutes all the side doors on the platform side of the train 

were opened and the participants exited. For the second trial, the smoke was generated in the 

other end car and use of the set of side doors in that car was blocked, making it necessary for 

individuals to move to the next adjacent car to exit. In addition, the doors were not opened for 

15 minutes, simulating the delay in reaching an evacuation location safer than the tunnel. Most 

of the observations recorded are qualitative and refer to passenger behavior and included 

references to acoustic messages, signage systems (particularly in smoke), operating instructions, 

and the height of the drop from the car to the ground.

The exit flow rates in both egress trials were approximately 1 pps. Using the exact flow rate 

value (1.03 pps) and the average exit time of 60 seconds when using more than one door, the 

ppm was calculated as approximately 62 for both high-platform and adjacent car egress and 

egress to the ROW. However, the number of persons who were in each car was not provided in 

the cited reference. (An additional report (in German) which further describes the two egress 

trials provides more information for car exit times [30].) Since the only verbal instructions were 

via an audio link, and there was no train crew, another important observation was the role of 

“leaders” among the passengers who took charge and directed the evacuation.

2.4.1.4 Spanish Passenger Train Study

The Spanish Railroad Administration (RENFE) conducted a series of high-speed trainset 

evacuation drills in 2009, which were later analyzed by the University of Cantabria to develop 

egress flow rates [31]. The 218 participants in the 2009 drills were railroad employees and some 

of their family members. All participants in the 11-car trainset (which included 1st and 2nd class 

cars and a lounge car) were required to use car end doors to move through the train and then use 

only a single car side door exit from one car to a 5-foot, 10-inch (1.7-meter)-wide platform 

walkway along the tunnel wall. (There was a height difference of (9.8 in) 25 cm between the 

“exit” rail car floor and the walkway platform, and a gap of 15.7 in (40 cm) from the door 

threshold to the edge of the platform. Participants had no luggage, but were allowed to gather 

personal belongings and carry them out during the drills. Participants were often observed to 

behave deferentially to each other; in particular, men often stopped to allow ladies first. The 

2009 passenger flow rate result was approximately 0.57 pps (35 ppm). 

 

• ** Information was derived from Austrian report information provided by University of Greenwich.
13

To take a more comprehensive view of emergency evacuation, and reflect actual real-world 

passenger evacuation, the data collection and analysis framework of the Spanish research team 

included the following elements:

• Pre-evacuation Stage

- Time from ignition to detection,

- Time from detection to sounding of alarm,

- Time for passengers to recognize alarm,

- Time to decide how and which way to move,

- Movement within the train before it stops;

• Evacuation Stage

- Opening doors, deploying emergency ladders, and

- Actual movement of passengers off the train.

Results from the 2011 Spanish paper imply that (1) default values in current building egress 

models may not be adequate for passenger trains, because of the need to stop the train before 

evacuation begins, differences in passage widths, and stair riser heights, etc., and (2) different 

coaches can produce different response times depending on the timing of information about the 

emergency. In addition, when passenger rail cars are not fully occupied, response time is a key

parameter in determining the total evacuation time. Otherwise, the total evacuation time depends 

on the flow capacity of the exits. 

The time to stop a high-speed train travelling at full speed was estimated by the authors to be 3 

minutes and can be much longer in some situations.

2.4.1.5 Summary

Data from the Volpe Center-conducted egress experiments for U.S. passenger rail cars, as well as 

similar rail car emergency evacuation experiments conducted in the United Kingdom, Austria, 

Spain, are reasonably consistent with regard to egress to a high platform or an adjacent car – the 

egress flow rate is slightly less than 1 pps (60 ppm), as shown in Table 2.

However, if passengers must traverse an elevation difference substantially greater than normal 

stairway step heights, as is typically the case in passenger train evacuations to the ROW, egress 

flow rates become much more variable. To avoid the risk of injury to persons of low agility, 

some experiments have excluded exiting to the ROW entirely, or tested this path using only 

young, physically fit participants. As a result, reported egress flow rates for egress from a rail 

car to the ROW range from below 6 to 60 ppm (0.1 pps to about 1 pps). However, the 

experiment participant populations are often unrepresentative of the general traveling public.

In an actual time-critical passenger rail evacuation to the ROW, it is likely that to expedite egress 

it will be necessary for train crew members and physically fit passengers to assist persons with 

mobility impairments who have difficulty getting down from the car door the low platform or 

ROW due to the varying distance between door threshold and the track level. However, due to 

the risk of injury, very limited experimental egress data are available for persons with mobility 

impairments.
14

Table 2. Comparison of Rail Car Egress Flow Rates – Recent Experiments

EGRESS 

PATH ROUTE

U.S. (Volpe / 

MBTA)

(pps / ppm)#

UNITED 

KINGDOM

(pps / ppm)#

AUSTRIA

(pps / ppm)#

SPAIN

(pps / ppm)#

Side door to high platform or 

end door to adjacent car## 0.9 / 52 0.7–0.9 / 43–55 ~1 / 62 -

Side door to tunnel side 

platform walkway### - - - 0.6 / 34

Side-door stairway to low 

platform#### 0.7 / 41 - - -

Side-door stairway to ROW##### 

and platform ####### 0.3 / 20 - ~1 / 62- -

 #

 All numbers have been rounded.

## Noncompetitive / competitive.

### 9.8-in (25-cm) height from door threshold to platform and 15.7-in (40-cm) gap from door threshold to platform.

#### 15-in (38-cm)-height difference from bottom of last step of side-door stairway to pavement.

##### 25-in (63.5-cm)-height difference from door threshold to platform.

###### 26-in (65-cm)-height difference from bottom of last step to track level.

2.4.2 Aircraft Evacuation Studies

2.4.2.1 FAA/CAMI

The Appendix of this report contains a complete listing of FAA/Civil Aerospace Medical 

Institute (CAMI) aircraft-related evacuation studies. 

CAMI has conducted an extensive research program to determine the effects of type, size, 

location, and operation of emergency exits, as well as emergency lighting and “floor proximity” 

escape path marking on the time required by passengers and crew to evacuate from aircraft. 

CAMI also funded several studies related to the development of a computer model for aircraft 

emergency evacuation time prediction [32] [33] [34] [35].

For example, in well-controlled tests conducted by CAMI during the 1990s, 174 adults between 

18 and 40 years of age repeatedly exited an aircraft fuselage mockup [36]. The door openings 

were 30-inch (76-centimeter) wide in all tests, but door heights ranged from 4 to 6 ft (1.2 to 1.8 

m). Just outside the door was either a slide or a platform at the same height as the door sill. For 

the condition most similar for egress from a passenger rail car (to a low-platform or ROW 

location), the average egress flow rate was about 2 pps (114 ppm), using a 6-foot (1.8-meter)-

high door to the platform). This relatively high rate is consistent with the relatively younger age 

of the FAA test participant population. 

Egress flow rates through aircraft over-wing window exits (“Type III”) have been a particular

topic of interest to FAA. In a 2001 meta-analysis of the factors relating to “Type III” exits [37],

the findings applicable to passenger rail car egress included the following:
15

• Human factors effects predominate in controlling evacuation performance and obscure 

the effects of other evacuation factors. Controlling human factors (and other 

confounding effects) is necessary to clarify the effects of other factors, such as 

passageway configuration.

• Passageways between 13- and 25-inch (33- and 64-centimeter) wide provide essentially 

equivalent egress flow rates, whereas those with narrower widths (especially for older 

passengers) are less effective. Widths above 25 in (64 m) show slightly lower flow rates 

in competitive trials because two subjects may attempt to pass through at the same time.

• Blockages of the Type-III exit by participants during competitive evacuation trials are 

related more to the attitudes and motivation levels of individuals than to passageway 

configuration, as blockages or extremely delayed evacuations have occurred for almost 

all studied passageway widths.

• Information materials, such as safety briefing cards related to emergency evacuation 

activities, have been poorly rendered; consequently, passengers either cannot understand 

the intent of the materials or do not feel obliged to read and follow the instructions.

• Directions from a flight attendant can organize passenger behavior during both actual and 

experimental evacuations without producing idiosyncratic effects or interactions that 

necessarily render the results of evacuation studies inapplicable to rulemaking.

The implication of the FAA/CAMI studies is that only individual-movement egress computer 

models are capable of incorporating all of the factors that affect egress time because these 

models are able to establish consequences of human response based on the specific scenario 

conditions. Of particular significance is the fact that the linear relationship between the width of 

passageways and the passenger flows through them, characteristic of hydraulic building egress

models, breaks down for the narrow aisles of aircraft and passenger rail cars because faster 

individuals are not able to pass slower-moving individuals.

Several of the FAA/CAMI studies also discuss the importance of the design of evacuation 

experiments, noting that the variable factors evaluated during a series of evacuations may be 

affected by other factors. For example, in one report evaluating the effect of seat row and 

bulkhead passageway width on occupant access to the exit, the study authors observed that 

placement of the exit hatch after it was removed had a variable impact on the results [38]. The 

inconsistent placement of the hatch resulted in discrepancies in the data that could have been 

avoided by having the participants place the exit hatch in the same location during each test. 

2.4.2.2 CAA/FAA

The Civil Aviation Authority (CAA), UK has sponsored two aircraft evacuation time studies, the 

latter of which was conducted in coordination with the FAA [39] [40] [41]. 

The aircraft evacuation experiments conducted by the University of Cranfield, UK, evaluated the 

effects on evacuation times of: 1) passenger motivation, 2) the width of the bulkhead opening

leading to a door exit, and 3) the width of the passageway leading to over-wing exits. The 

competitive behavior of passengers was established by the prospect of a financial reward.

In the evacuations using the door exit, the influence of the opening between the two bulkheads

leading to the exit was dependent on whether the evacuation was orderly or competitive. In 
16

orderly evacuations, changing the width of the opening did not have an impact until one of the 

bulkhead walls was completely removed. 

Competitive evacuation times decreased with an increase in opening width; however, these 

evacuations had an initial surge of people toward the exits, which caused congestion in the 

vicinity of the exit. The fastest evacuation time recorded was again achieved with one of the side 

bulkhead walls removed; however, this configuration also resulted in other difficulties. With one 

bulkhead wall removed, the surge to the rear door exit by people was so sudden that the cabin 

staff member had difficulty opening the door; she was, in a number of trials, pushed out of the 

aircraft by the occupant surge. 

In the evacuations through the over-wing exit, effects on evacuation time were evaluated for: 

1) variable longitudinal spacing between seats adjacent to the exit row and 2) removal of the 

outboard seat. Evacuations were slowest when the seats adjacent to the exit were separated by a 

3-inch (7.5-centimeter)-wide passageway between the rows, while seat row passageways to the 

exit that were 6–25 in (15–64 cm) in width resulted in approximately the same evacuation times. 

Competitive occupant evacuations with the 3-inch (7.5-centimeter)-wide passageway between 

seat rows caused blockage due to congestion at the exit opening, severe enough that the 

evacuation had to be stopped in three of the trials. Noncompetitive orderly evacuations using a 

34-inch (85-centimeter)-wide passageway to the exit resulted in about an approximately 5 second 

faster time. However, this wider passageway to the exit resulted in the formation of two lines of 

occupants who then competed for use of the exit. A similar result was obtained when the 

increased room adjacent to the exit resulted in passenger lines in front of and in back of the exit 

row seats. Again, occupants competed for the exit.

Tests conducted on an aircraft with two deck levels to evaluate the difference in evacuation times 

between the lower and upper decks showed that occupant hesitation times at the upper-deck 

escape slides were higher, indicating that passengers will delay egress more at exits located 

higher above the ground [42].

The European Transport Safety Council (ETSC) conducted a study that reviewed various aircraft 

crashes and investigated the idea that all airplane crashes lead immediately to death [43]. The 

study paper stated that providing training to crew and cabin staff and maximizing the opportunity 

for an orderly evacuation can increase the chance that passengers survive a transportation 

accident.

2.4.3 Bus Evacuation Studies

During the 1970s, NHTSA (then National Highway Safety Bureau) commissioned the University 

of Oklahoma to study evacuation from school buses and intercity buses. The published reports 

provide important insights into the ability of people to safely exit a bus after an accident, 

especially if the accident renders the main entrance and exit door(s) unusable [44] [45] [46]. 

The significant findings potentially applicable to passenger train egress time are summarized 

below:

• Exits are usually not used in optimal fashion. Passengers do not minimize the total egress 

time; they will take the path that seems best to them at the time.
17

• Passengers are reluctant to use exits that require a multistep process to initiate, e.g., 

emergency exit windows with a latch system that needs two hands and two operational 

steps to open.

• Children are very reluctant to jump from window exits and are more likely to queue at a 

door exit than to use an available window exit.

• For vehicles overturned onto their sides, end doors and roof hatches are the best exits. 

The drop to ground from a roof hatch is 2 to 4 ft (.6 to 1.2 m), compared with over 7 ft 

(2.1 m) for windows. Roof hatches on all buses were recommended. 

• Pre-trip instructions on use of exits and other emergency considerations were 

recommended.

• Operation of emergency exits should not require more than 35 lbs of force.

• Emergency exit design needs to consider how to reduce chance of injury and 

accommodate use by the obese, aged, disabled, and injured.

• Emergency lighting is needed in all vehicles. 

• Effects of low visibility are magnified in overturned vehicles.

A more recently completed Volpe Center study in 2009 included the measurement of egress flow 

rates by occupants who exited from a typical intercity bus and from a mock-up bus [47]. In the 

first case, participants exited from an actual intercity bus using the front door and alternative 

exits, such as emergency exit windows and roof exit hatches, under daylight conditions. In the 

second case, participants exited from a bus mockup using a simulated second side-door stairway,

as well as from two wheelchair-access doors of different widths, under various lighting 

conditions. The study report indicated that “normal” egress times for able-bodied adults during 

an evacuation from a fully loaded motorcoach, using any of the tested egress paths and exits,

could be less than three minutes. However, the finding with application to passenger rail car 

emergency egress is that occupant egress flow rates are likely to be considerably longer if:

• Passengers do not understand how to open or use the emergency exits.

• Passengers cannot find or see how to use the emergency exits because of darkness or

smoke.

• Passengers are injured or lack the agility and strength to use emergency exits, other than 

doors.

• Exits will not stay open (or are unusable due to blockage or damage). 

2.4.4 Other Related Studies

Occupant selection of an exit has been shown to depend on a number of variable factors. Two 

studies determined that people tend to exit from an emergency situation through the door they 

entered [48] [49]. Those 1996 and 1988 studies found that staff encouragement to use other 

emergency exits would prompt more people to use alternative exits. These findings indicate that 

train crew personnel may have a significant impact on passenger rail car evacuation by notifying 

passengers of their potential exit routes and how to manually open the exits. Another study 

concluded that staff instructions help reduce pre-movement (e.g., decision-making) times [50],
18

estimated by the 2003 Society of Fire Protection Engineers (SFPE) human behavior engineering 

guide (SFPE Guide) to be as much as 75 percent of total evacuation times [51]. Thus, the 

reduction of pre-movement times could result in a marked improvement in total evacuation time. 

Three other studies indicate that instructions during evacuation can aid people in finding exits 

and moving away from unsafe conditions [52] [53] [54].

2.5 EFFECTS OF SMOKE AND EMERGENCY LIGHTING AND EXIT MARKING 

SYSTEMS

Numerous studies describe the effects of smoke and emergency lighting on the movement of 

people toward exits. This section summarizes the results of selected studies, which are relevant 

to passenger rail car emergency lighting and emergency exit marking.

The University of Greenwich study report cited earlier [23] stated that passenger movement was 

reduced in evacuation tests conducted inside passenger rail cars with smoke, compared with tests 

without smoke. Another study concluded that smoke does not affect passenger movement until 

the optical density** of smoke is less than 1.5 [55]. Two other studies cited in the previous 

section indicate that even when visibility is significantly reduced by smoke, people will continue 

to move and attempt to find exits, but evacuation times will increase [52] [53]. This finding has 

been recognized by the 2003 SFPE Guide [51]. In addition to reduced visibility resulting from 

smoke, smoke will also affect the movement of persons as noted in a 1997 paper [56]. Two 

additional studies found that occupant movement was affected more by visibility through smoke 

and familiarity with the building layout than by heat [57] [58]. 

Several other studies evaluating emergency lighting, as well as the visibility and legibility of 

emergency exit signs and exit path marking, were presented in papers presented at a 2001 

conference. One paper concluded that while the effectiveness of emergency lighting and 

“wayguidance” (i.e., emergency exit signs and exit path marking) systems depended on the 

illuminance at floor level, visual cues provided by the lighting system were more important in 

leading occupants to exits [59]. Another conference paper reported that additional overhead 

lighting did not make it easier to see exit signs, but that signs were most easily seen under 

emergency lighting or without overhead lighting [60]. 

In addition, the earlier 1997-cited study determined that exit signs with flashing lights were more 

effective than continuously lit signs [56]. A 2001 study conference paper concluded that a bluecolored flashing light is most effective, but that the blue flashing light should only be activated 

during an emergency to bring attention to all alternative emergency exits [61]. However, green 

was demonstrated to be a better color for lighted signs according to another study paper 

presented at a 2005 conference [62]. 

A National Research Council of Canada (NRC) field study of photoluminescent (PL)

wayguidance systems, as installed in the stairways of an office building, concluded that the PL 

systems appeared to be as effective as emergency lighting in providing guidance to the building 

 

 ** Optical density is the measurement of the attenuation of the test chamber light beam by the

quantity of smoke produced and collected in the chamber. The lower the optical density, the 

higher the visibility of the test object.
19

occupants who exited down the stairways [63]. A follow-on field study by the NRC evaluated

different installations of PL material in building stairways and confirmed that use of this material 

to mark the exit path was positively commented upon during an evacuation drill, but that the 

density of the occupants had a greater impact on the evacuation times than the type of PL 

material used [64]. Another study found that exit finding was improved when PL and tactile 

markings were used to guide occupants toward exits [65]. The importance of clear visual cues 

provided by the wayguidance system was also demonstrated in another study in which less clear 

cues resulted in people not following the specified escape path [66]. That same study also found 

that audible and tactile wayguidance systems were as effective as visual systems.

2.6 SUMMARY

The studies discussed in this chapter relate to various factors that affect the calculation of 

emergency evacuation time predictions for theoretical and regulatory purposes. However, major 

differences exist between the passenger train operating environment and the operating 

environment of aircraft, buses, and ships. These differences include the type of vehicle seating 

configurations, the number and type of door and other exits that can be used in an emergency, 

and the distance the occupant must traverse from the exit to the ground or other safe area. 

Therefore, it is important to carefully consider the impact of those differences, as well as 

common egress factors, when selecting variable factors for calculating passenger rail car egress 

times. 
20

3. PASSENGER RAIL CAR EGRESS TIME VARIABLE FACTORS

The majority of “unusual” or other nonaccident emergency situations can be addressed by the 

passenger train crew without evacuating passengers because in most cases, it is safer to remain 

on the train. Some conditions, such as locomotive power failure or derailed locomotives or 

passenger cars as a result of an accident, may require the transfer of passengers from one train to 

another or evacuation of the train to another location off the train. If the evacuation of 

passengers is handled properly by the train crew, the safety of passengers is maintained, and 

there is a relatively low risk of injury to passengers and train crew.

However, occupant egress time from a passenger train can be a complex process affected by

numerous dynamic factors and conditions. Accordingly, these variables and conditions that 

affect the time necessary for passengers to exit must be considered when developing passenger 

rail car egress time predictions. 

FRA regulations in 49 CFR, Part 225, subsection 225.9 require that railroads immediately report 

a train accident resulting in the evacuation of a passenger train [67]. However, this notification 

and the FRA reporting form required to be completed by the railroad do not include requirements 

for specific information, such as number of passengers evacuated from the train, identification of 

which doors or other emergency exits were used, length of time required for the evacuation or 

transfer of passengers, or specific actions of the train crew. Since the emphasis of the railroad 

unusual condition or FRA investigation reports is on the cause of the collision or derailment 

rather than passenger egress (or emergency evacuation), detailed information concerning 

passenger egress is usually very limited.

With certain exceptions, the NTSB accident investigation reports and accident brief reports for 

passenger train accidents normally do not contain any detailed information concerning passenger 

train evacuation, beyond simply stating that an evacuation took place. The NTSB objective is to 

identify the probable cause of the accident and issue recommendations for railroads; FRA; state 

or regional agencies; or industry groups, such as the Association of American Railroads (AAR) 

and the American Public Transportation Association (APTA). Therefore, in most cases, detailed 

information concerning passenger egress is usually very limited. 

Accordingly, specific passenger evacuation information for egress variable factors is incomplete 

for the majority of NTSB passenger train accidents described in this chapter. However, it is 

important to note that the specific evacuation “issues,” whether documented or not for certain 

accidents, may have a major impact on whether an “unusual occurrence” develops into an 

emergency that results in injuries or casualties to passengers. Thus, the discussion of variable 

factors in this chapter is intended to provide examples of those egress factors that may or may 

not be controllable, particularly in terms of input into a passenger rail car egress simulation 

model, and regardless of their applicability to specific passenger train emergencies. 

3.1 RAIL CAR GEOMETRY AND CONFIGURATION

Passenger rail car design factors which have an obvious impact on occupant egress times during 

emergency scenarios include the following: type and size of car, number of seating levels, 

width of aisles and stairways (if multilevel), number of doors and exit windows, exit locations, 
21

exit dimensions, and construction materials. Other important factors are emergency exit 

identification, emergency lighting, exit accessibility, design of emergency exit-release 

mechanisms, and placement and content of instructions for release mechanisms. Special 

consideration is necessary to address the exit design differences for various configurations of 

multilevel cars, as well as sleeping cars and food service cars, in order to improve passenger 

ability for egress from survivable accident scenarios. 

FRA regulations contained in Part 238 and Part 239 [1] [2] include requirements to address 

these design factors (e.g., type, number, location, size, as well as exit marking and operating 

instructions for emergency exits and emergency lighting) since the inaccessibility of doors and 

other exits in passenger rail cars has been cited in several NTSB accident investigation reports as 

being the cause of significant evacuation delays. Such delays depended on the severity of the 

emergency, if passenger car and interior stairways and side and end doors were crushed or 

damaged, thereby preventing train crew or passengers from opening them. 

The NTSB accident investigation report of the 2003 collision of a multilevel commuter train and 

a freight train in Placentia, CA, found that access from the upper level to the exterior of the rail 

car was not possible due to substantial crush damage to a stairwell and “misaligned” end 

doors [68]. Passengers on the upper car level removed the emergency exit windows and climbed 

ladders down to the ground.

After the 1996 collision of an Amtrak train and a commuter train in Silver Spring, MD, multiple 

commuter rail car exits were inoperable or inaccessible. Moreover, the NTSB accident 

investigation report stated that emergency evacuation from the cars was impeded because the 

cars lacked readily accessible and identifiable quick-release mechanisms for the exterior side 

doors [69]. Therefore, egress through the emergency windows was considerably slower than 

what might have been possible if passengers had been able to exit using the car doors. One 

passenger reported that it took him 3 minutes to remove an emergency window exit and an 

additional 7 minutes to get himself and one injured person out of the commuter rail car. Another 

survivor reported not being able to open either of the rear side doors of the car. He escaped

through an opening created during the collision, which resulted in a total evacuation time of 

5 minutes. Several passengers died because of fuel fire intrusion into the car and their inability 

to exit the commuter car, which had been heavily damaged during the collision.

In the December 1990 collision of an Amtrak train and a commuter train in Boston, MA, some 

passenger rail car end vestibules were crushed, rendering the doors unusable; the window exits 

were the only viable options for egress. Evacuation was further slowed by heavy smoke inside 

the car and the lack of emergency lighting. The NTSB accident investigation report concluded 

that some passengers may have chosen not to wait for the side door to be opened manually but 

instead may have attempted to exit through an end door into an adjacent car [70]. 

According to the NTSB accident investigation report for the 1989 Amtrak train collision with a 

semi-trailer truck accident in Stockton, CA [71], passengers decided to leave the train via the 

emergency exit windows, at least in part because of the absence of visible interior markings and 

operating instructions at the vestibule end and side doors.

In addition to the 1996 Silver Spring commuter train and Amtrak accident cited above [69], 

NTSB concluded that lack of emergency lighting significantly slowed evacuation during several
22

Amtrak passenger train accidents, including Kingman, AZ, in 1997 [72] and Selma, NC, in 

1994 [73], as well as the 1998 commuter train accident in Portage, IN [74]. NTSB first made its 

recommendation concerning passenger rail car emergency lighting in its accident investigation 

report for the 1966 Everett, MA, commuter rail accident [75].

These accidents provided the basis for the FRA regulation that new passenger car equipment be 

equipped with emergency lighting [1]. In early 2012, FRA requested comments in a proposed 

rulemaking for revising Part 238 [76] to require, by incorporation by reference, compliance by 

railroads with the APTA emergency lighting standard, which requires self-contained emergency 

lighting on new and existing passenger rail cars (see Reference [6]).

3.2 OPERATING ENVIRONMENT

Passenger trains carry occupants between stations along a unique operating environment, 

including track, tunnels, bridges, and waterways, which may complicate and delay the 

evacuation of passengers, if necessary. Exterior conditions, such as location of the train, if it is 

stopped between stations, or weather conditions, can increase the time required to exit from the 

rail cars and hinder passengers from being able to reach a point of safety in a timely manner. 

Considerable differences in egress conditions, egress flow rates, and egress time estimates for 

passenger train evacuations are affected by the following exit routes (all of which may be remote 

from emergency responders):

• From an upright car to:

− Another adjacent car,

− Station platform 

o High-level and

o Low-level;

− Pavement or ground away from a station platform;

− ROW next to adjacent tracks with passing trains; 

− Hillside with sloped terrain; 

• From a derailed rail car (upright or on its side) to above locations, which are located:

− In a ditch; 

− Inside a tunnel

− On a bridge over water; 

• From rail car located in or under water; and 

• From the car under the above listed conditions, to the above locations, during severe 

weather or conditions of darkness.

A 2009 paper describes the results of a study for the Swedish rail agency that focused on 

controlled nonemergency evacuations [77]. The paper stated that most passenger train 

evacuations are low-hazard situations which are effectively managed by the train crew. 

However, the paper noted that factors, including length of time on the train, environmental 

conditions (e.g., high temperatures), and number of train crew, could result in spontaneous 

evacuation, which if not controlled could lead to risk of injury due to the outside train 

environment.
23

In May 2006, a power outage disrupted all rail traffic on Amtrak’s Northeast Corridor between 

Washington, D.C. and New York City during the morning rush hour, stranding approximately 

112 trains with tens of thousands of passengers on board. Many passengers remained on trains 

for several hours, including trains in tunnels located in Baltimore, New York City, as well as

locations in New Jersey. Immediate passenger evacuation in these locations was not desirable. 

Evacuation from a passenger rail car on a bridge is naturally slower due to the caution required 

to prevent occupants from falling into the water. In the 1993 Amtrak train collision with a bridge

that occurred near Mobile, AL [78], the evacuation of the two passenger rail cars that remained 

on the bridge was slowed because emergency responders had difficulty gaining access to the rail 

cars. 

3.3 RAIL CAR ORIENTATION

Passenger rail car orientation can present additional egress challenges for passengers. The 

majority of rail cars remain in the upright position during most accidents. However, in other 

accidents, cars tilt or roll onto their sides. When a rail car is resting on its side, side- and endexit doors and exit windows are located overhead or on the ground. 

The 2002 derailment of the Amtrak AutoTrain near Crescent City, FL, resulted in eight 

passenger cars being overturned onto their sides and into a ditch. The NTSB report noted that 

the assistant conductor in the overturned dining car assisted passengers in climbing upward out 

of the “top” of the car through what had been a side door [79]. Since 7 other passenger cars 

were overturned and 5 other derailed cars were leaning in various angles along the ROW, the 

report stated the likelihood that many other passengers either climbed out of or were evacuated 

from side doors and emergency exit windows located “on top” of the overturned car, with the 

assistance of train crew or emergency responders, the exits being as much as 10 ft (3 m) above 

the track level. 

The NTSB investigation report of the 1998 Amtrak train derailment in Arlington, TX, noted that 

some passengers in rail cars that were not upright could not exit from the doors or emergency 

exit windows and had to evacuate the cars by ladders that responders put through open 

emergency windows [80].

3.4 OCCUPANT CHARACTERISTICS

The process of estimating the time and ability of passengers to safely egress from a train must 

also consider occupant demographics. Intercity passenger trains are likely to carry a broad 

spectrum of people, including families with children and elderly individuals, as well as mobilityimpaired persons who use wheelchairs. In contrast, commuter trains are usually occupied by 

working age, able-bodied passengers who tend to be regular riders and are thus more familiar 

with the rail car configuration, including location of doors and emergency exits. 

Accordingly, different occupant characteristics and train crew interaction with passengers, in 

relation to rail car orientation, lighting conditions, and the operating environment, can cause 

significant variations in egress times.
24

As noted in the previously cited Amtrak 2002 Crescent City, FL [79], and 1998 Arlington, 

TX [80], accidents, significant delays in evacuation can result for less physically able passengers 

or those injured in the accident.

Individuals who have low agility or other mobility issues may find it difficult to exit by using the 

passenger rail car side-door stairways to a low-platform location or to the ROW (even with a step 

box), without additional assistance from the train crew or other passengers, thus increasing the 

total time to exit from a fully-loaded car. In addition, if passenger rail side-door stairways are 

not available (such as on the Acela Express trainset cars) or cannot be used, egress times would 

be much longer. 

3.5 TRAIN CREW, PASSENGER, AND EMERGENCY RESPONDER ACTIONS

Before evacuation of a passenger train can begin, train crew and passengers must first be aware 

of the emergency. Passengers and train crew must then define what is happening and recognize 

the appropriate action to take, which may or may not include evacuation from the train. From 

that point, if egress is necessary, the following iterative process can occur depending on the 

situation: 1) taking action, 2) having success or failure, 3) re-evaluating based on success or 

failure, and finally, 4) taking more action. Accordingly, the decision-making process and actions 

could be crucial to the overall objective of safe passenger egress from the train, if necessary. A 

few minutes’ delay due to indecision or an incorrect decision can make the difference between 

passenger safety or potential injury or death. 

The FRA requirement in subsection 239.101 of Part 239 requires that passenger train operating 

crews be properly trained according to the railroad emergency plan [2]. Additional 

nonregulatory but extensive information relating to passenger train crew training in emergency 

procedures is contained in a 1993 FRA research report that discusses recommended guidelines 

for passenger train crew training as part of the operating railroad emergency plan [81]. (FAA 

and USCG also recognize the importance of well-trained, assertive crewmembers and therefore 

require flight and ship crews to undergo intensive initial and ongoing training in responding to 

emergency scenarios [82] [83].)

In addition, subsections 238.113, 238.114, and 238.123 of the FRA Part 238 regulations [1]

require that passenger rail car emergency exits be clearly marked and instructions for their use be 

provided. These requirements are intended to enable passenger train occupants to locate, reach, 

and operate emergency exits, if it becomes necessary to immediately evacuate the train in an 

emergency. In support of the FRA rulemaking process, Volpe Center has conducted an 

extensive research investigation program to identify new, longer-lasting, and more cost-effective 

technologies for marking emergency egress locations [84]. These technologies include “highperformance” photoluminescent materials, as well as components for emergency lighting, 

including LED lamps and independent power sources.

Several passenger train accidents highlight the importance of emergency evacuation training and 

education for passenger train crew, emergency response personnel, and passengers. 

For example, train crew actions, such as not using the public address system to direct passenger 

evacuation, contributed to the slow or unnecessary egress to the ROW under hazardous 

conditions, according to the NTSB investigations of the 1991 Amtrak Lugoff, SC, and the 1996 

Secaucus, NJ, commuter rail accidents [85] [86]. 
25

Emergency responder actions have had major impacts on timely occupant evacuation, especially 

from passenger rail cars that are on their sides. In accidents that occurred in Arlington, TX

(1998) [80], Russell, IA (1997) [87], Kingman, AZ [72], and Intercession City, FL (1993) [88], 

emergency responders accessed door and emergency window exit openings and used ladders to 

help trapped passengers escape from the cars. Emergency responders at the Russell, IA, and 

Intercession City, FL, accidents removed injured passengers through emergency exit windows 

using backboards and lifts.

3.6 FIRE AND SMOKE AND OTHER HAZARDOUS CONDITIONS

Evacuations can be further complicated by fire and smoke, such as in the previously-cited 1996 

Silver Spring Amtrak and commuter train collision and fire [69], and the 1983 Amtrak 

Gibson, CA, train fire [89]. Fire outside the car (e.g., resulting from a collision) in any 

passenger rail car operating environment can also complicate evacuation. In fact, egress from 

the train in even the least challenging rail-operating environments, (e.g., at a high-platform 

station) may be hindered by smoke accumulation.

Fire and smoke conditions within passenger rail cars also have multiple effects on emergency 

evacuation. Injury and death can result from exposure to flames, heat, and/or from inhalation of 

toxic products. Toxic products, such as carbon monoxide, can affect cognitive processes and 

slow movement, even before lethal levels are reached. Reduction in visibility also slows 

movement and can contribute to the occurrence of injury during egress, as well as lead to 

incorrect decision-making due to lack of information. 

FRA regulations in Part 238, subsection 238.103 [1] address passenger rail car fire safety by 

requiring that new equipment designs and construction materials provide sufficient fire 

resistance to reasonably ensure adequate time is available to detect a fire and safely evacuate 

passengers and crew members if a fire cannot be prevented.

3.7 POTENTIAL VARIABLES FOR EGRESS AND TIME ESTIMATES

A variety of potential variables that can affect the time necessary for occupants to exit from a 

passenger train in an emergency may be categorized as follows for input to an egress model:

• Passenger Characteristics 

− Age and gender,

− Weight (body mass),

− Agility and strength,

− Mobility impairments (including injuries and disabilities),

− Number of persons in rail car,

− Seat location, and

− Frequency of rail travel and familiarity with rail car;
26

• Rail Car Geometry and Configuration

− Car type,

− Number of levels (single or multilevel),

− Number and arrangement of seats,

− Aisle and stairway arrangement, and 

− Door and emergency window location, size, and operation;

• Operating Environment 

− Location of emergency

ο Station:

+ High-platform: best case

+ Low-platform, and

ο ROW (ballast, tunnel, bridge): worst case,

− Time of day and lighting conditions,

− Weather conditions,

− Platform or ROW conditions,

− Car condition (damage) and orientation of car(s), and

− Hazardous condition

ο Fire,

ο Smoke, and

ο Water immersion;

• Train Crew (and emergency responder) Training 

- Plan and procedures and

- Equipment;

• Passenger Awareness;

• Passenger Assistance in Exiting,

− Direction and assistance from train crew,

− Assistance from other passengers; and

• Assistance from emergency response personnel.

3.8 SUMMARY

Various egress factors, whether documented or not for certain types of passenger train 

emergency scenarios, may have a major impact on the length of time necessary for occupant 

egress from passenger rail cars, as well as whether an “unusual occurrence” develops into an 

emergency that requires evacuation. Moreover, many of these variable factors may or may not 

be controllable. However, to the extent feasible, these egress factors must be considered in order 

to develop realistic egress time predictions that reflect the unique railroad-operating 

environment.
27

4. METHODS FOR PREDICTING PASSENGER RAIL CAR EGRESS 

TIME

Four primary methods can be used to estimate emergency egress time: prescriptive structural 

specifications and equipment design standards; hand and spreadsheet calculations; estimates 

based on past egress experiment trials; and egress computer models. 

4.1 PRESCRIPTIVE SPECIFICATIONS AND STANDARDS

Specifications and standards, such as those contained in the FRA and other transportation agency 

regulations, prescribe requirements (e.g., number of exits and their dimensions) for various 

elements of the passenger rail car egress system. Implicit in these prescriptive requirements is 

the assumption that compliance will provide the necessary evacuation time under maximum 

occupant loading conditions and during anticipated accident scenarios. The specifications imply 

that such consideration has been given to the minimum requirements. However, scientific 

justification for the prescriptive requirements is often limited or left unstated. 

4.2 EGRESS TIME ESTIMATES USING MODELS

To develop the total necessary time for occupant egress from a structure, the egress flow rate 

(number of persons per unit of time flowing through an exit) and walking speed (distance 

traveled per unit of time) must be calculated. 

4.2.1 Hydraulic Models – Theory and Methods

When required to predict egress and emergency evacuation times, passenger rail car designers 

and builders, as well as passenger train system operators, have historically opted to use handcalculation methods based on the hydraulic theory because the methods are simple, readily 

available, cost little to apply, and provide a reasonable result, unless the scenario is complex. 

Hydraulic models for egress calculations treat exiting individuals as “fluid” moving through a 

network of pipes. In the hydraulic model, people movement is controlled by occupant density 

and the width of openings of doorways, stairs, and corridors. The entire population is assumed 

to move (walk) with the same speed, and the overall flow rate is determined by the most 

restrictive point ahead of the flow. When occupant density in a flow element (e.g., a corridor) is 

low, the speed will equal the maximum person walking speed observed by researchers. As 

occupant density increases above a critical value, the walking speed begins to decrease due to 

congestion. The critical value does not apply to occupants walking along a narrow passenger rail

car.

Typical assumptions associated with this methodology include the following:

• All persons will start to evacuate at the same instant.

• Occupant flow will not involve any interruptions caused by decisions of the individuals 

involved.

• All or most of the persons involved are free of disabilities that would significantly 

impede their ability to keep up with the movement of a group.
28

Accordingly, the “modeled time” calculated using the hydraulic method will likely differ from 

the actual egress time. Because of the basic assumptions, this method is most useful to make 

estimates of the optimal egress time for a structure (i.e., determining the fastest possible egress 

time). The optimal evacuation time will be achieved if the distribution of occupants using the 

available exits is such that the egress efficiency is at its highest, and no delays are encountered 

during the egress process. These hand calculations are not intended to account for the influence 

on evacuation caused by decision-making. Past accidents have demonstrated that decisionmaking can be crucial to the outcome of an emergency. Instead it is common practice to apply a 

safety factor to the modeled egress time with the intention of bounding the answer. However, 

there is a significant level of uncertainty in trying to choose an appropriate safety factor, 

especially when factors, such as car orientation, come into play that do not affect building 

evacuation. In building egress prediction, a factor of 2 is the most common safety factor, 

although no strong scientific reasoning exists for this value.

Hydraulic prediction of egress flow rates is a function of parameters, such as passenger density, 

effective aisle width, pitch of stairs, etc. The coefficients in these egress calculations are based 

on observations of occupant egress from buildings, and are usually described as the number of 

ppm per unit of passageway width. These methods work well enough that their use has been 

accepted by the National Fire Protection Association (NFPA) and other organizations concerned 

with building life and fire safety codes. The Society of Fire Protection Engineers (SFPE)

Handbook of Fire Protection Engineering (SFPE Handbook) specifies calculation methods for 

egress from buildings [90]. Formulas are based on observations of both uncontrolled and 

controlled evacuations, as well as several empirical studies by Predtechenskii and Milinskii [91]

and Fruin [92].

However, the application of these hydraulic calculation methods directly to passenger rail car 

egress is problematic for the following reasons: 1) different methods estimate quite different 

flow rates for specified exit openings and 2) the widths of aisles and pitches of passenger rail car 

stairways are outside the ranges observed in buildings. For building egress, the flow rate through 

a given opening is estimated as directly proportional to its effective width. (Effective width is 

actual width minus the “boundary effect,” an “adjustment” factor of 4 to 18 in (10 to 46 cm).) 

However, this linear relationship between width and flow rate does not necessarily hold for 

widths less than 43 in (109 cm or 1.1 m) [92]. 

In buildings, room and corridor widths are large enough that evacuating individuals who wish to 

overtake slower persons can easily do so, but passing other persons becomes progressively more 

difficult as widths diminish below 43 in (109 cm). Flow rates per unit of width in passenger rail 

car aisles are certainly lower than for buildings, but there has been little agreement on exactly 

how much lower. 

As a result, different analysts have come to substantially different conclusions about passenger 

rail car egress times for similar egress scenarios. For example, in the 1998 Acela Express highspeed train evacuation time assessment prepared for Amtrak [93], the methodology for transit 

stations, as described in the NFPA 130 Standard for Fixed Guideway Transit Systems (1997

edition) [94], was used. The 1998 analysis was based on an egress flow rate of 0.83 pps (50

ppm) through an end door, as specified in the 1997 NFPA 130 standard for one “exit lane.” This 

flow rate is consistent with the actual egress flow rates observed during the 2005 Volpe Center 

passenger rail car egress experiment [13]. However, this value was then multiplied by 1.5, 
29

resulting in an adjusted flow rate of 1.25 pps (75 ppm). The rationale was that the 35 in door 

width is 1.5 times the minimum width of an exit lane (22.5 in). However, this rationale is 

problematic since before the passengers reach the end door exit, they would likely be walking in 

single file down the narrower rail car aisle at the lower 0.83 pps (50 ppm) flow rate. 

The egress flow estimation formula for station exits in the 2000 edition of the NFPA 130 

Standard was changed to 2.27 ppm per inch of doorway width, which would result in an egress 

flow rate of 1.32 pps (79 ppm) for the Acela Express trainset car end door [95]. The 2010 NFPA 

130 standard revised the station exit door flow coefficient downward to 2.08 ppm per inch, 

which would change the egress flow rate to 1.2 pps (73 ppm) for the same trainset end door 

exit [96]. 

Notwithstanding the more conservative station exit egress flow rate in the later 

NFPA 130 standard, use of the NFPA 130 station egress calculation method in the context of 

developing passenger rail car egress time estimates is not realistic due to the much wider 

NFPA 130 required minimum corridor width of 68 in (173 cm) versus the 22.5 in (57 cm) rail 

car aisle, which train passengers must walk along before reaching the car end door.

An analysis prepared for the Maryland Area Rail Commuter (MARC) system passenger rail

cars [97] included an estimate of egress flow rates based on the SFPE Handbook calculation 

method [90]. Egress flow rates were estimated using a formula that includes density and 

boundary layer factors, as well as average walking speed. However, “density” was defined as 

the total number of passengers divided by the floor area of the rail car, but should have been 

defined instead as the usable floor area (the reciprocal of the number of square feet of floor area 

for each person in the moving stream of exiting passengers). Accordingly, instead of only the 

usable floor area, the MARC analysis calculations used the entire floor area of the car, including 

all of the area occupied by seats. Estimates were prepared for various MARC rail car 

configurations, which included using an end door to an adjacent car. The calculated egress flow 

rate was 0.36 pps (21.5 ppm). 

The observed flow rates in the Volpe Center 2005 experiment [13] for exiting to an adjacent car 

were 0.88 pps (52 ppm). This value implies that the egress flow-rate estimates developed for the 

Acela Express trainset cars are too high, while the estimates for the MARC cars are too low. The

discrepancies between the Acela and MARC flow-rate calculations and the actual flow-rate 

based on the 2005 Volpe Center experiment observations are the result of the use of formulas 

developed from observations of pedestrian flows in large building spaces using much wider 

corridors and door exits. 

In the only other known example of an egress rate calculation for a U.S. rail car, a 1980 analysis 

estimated that for a Bay Area Rapid Transit (BART) rail car located in a tunnel, the passenger 

egress flow rate through the tunnel, not the door, would be the limiting factor; thus, all aspects of 

car geometry were ignored [98].

In summary, hydraulic calculations provide a quick method for generating estimates of egress 

times and methods that can be referenced to publications of recognized fire-safety organizations. 

However, egress time calculations for passenger rail car egress based only on occupant egress 

behavior from buildings do not consider that building corridors are much wider than passenger 

rail car aisles and building stairway step heights are much lower than the height of stairway steps 
30

used from a side-door stairway to the ROW or low-platform location. Depending on which 

method is chosen, what assumptions are made about the boundary-layer effect, and how the 

effective floor area is measured, occupant-flow rate estimates can vary by a factor of three or 

more. Therefore, the reliability of passenger rail car egress time prediction based on hydraulic 

hand-calculation methods using only floor-area and passage-width data is low. Hydraulic 

calculations based on actual observations of passenger egress have a greater likelihood of 

reliability, but still represent only the “best case” conditions under which such experiments are 

conducted without risk of injury to participants. The primary shortcoming of hydraulic models is 

that they treat all rail car passengers as having equal ability to navigate the egress path. This 

assumption does not consider individual differences in agility and movement, especially in 

difficult emergency situations. Accordingly, the shortcomings in the hydraulic modeling 

approach justify the development and use of computer models that specifically simulate 

emergency egress from passenger rail cars. 

4.2.2 Egress Computer Models

Computer models that simulate egress range in levels of sophistication from those that include 

the hydraulic calculations mentioned above to those that simulate individual person movement 

and decision-making. One of the attractive features of using computer models to simulate 

passenger rail car egress time is that it is very easy to explore the influence of one or more 

individual variable factors on the egress system. Models require that the User create and input a 

representation of the structure, in this case, the passenger rail car, and in some cases, the exiting 

areas outside the passenger train. Such models can be divided into two main categories, based 

on the underlying principle defining people movement: hydraulic models and individual person 

movement models. Individual-movement models have only recently been developed and are still 

in the early stages of application to the passenger rail car egress environment.

4.2.2.1 Computer-Generated Hydraulic Models 

Hydraulic computer models (sometimes called network models) use the same principles as hand 

hydraulic calculations and typically use a global method to represent the population to be 

evacuated. Using such a global entry method, the population will usually have uniform 

characteristics, such as body size and movement speed (see Figure 1). Typically, hydraulic 

models do not represent individuals at all, but instead assume that movement can be represented 

by flows of people described by population size, as well as speed, flow, and density 

relationships. 

Figure 1. Hydraulic Model – Simple Example
31

Some models allow the User to specify percentages of the population that have subsets of certain 

characteristics. Each group type (e.g., able-bodied, working-age women) is then assigned its 

own set of characteristics that control the egress of that subgroup. 

The SFPE Handbook [90] states that the hydraulic model is limited in the factors it can represent. 

For example:

• Behaviors that detract from movement are not explicitly considered.

• Numbers of people in a structural component are considered rather than their identity and 

their individual attributes.

• Movement between egress components is considered (e.g., from room to room), rather 

than within them.

• Results are deterministic and will therefore remain the same unless changes are made to 

the scenario or the assumptions employed.

As noted for hydraulic hand-calculation methods (see Section 4.2.1), building corridors are much 

wider than passenger rail car aisles, and normal interior step heights down a stairway are much 

lower than those in passenger rail car exterior side-door stairways (if provided) that an occupant 

would use to exit to a low platform or to the ROW. Accordingly, occupant egress flow rates 

based on building egress times do not reflect the reality of the passenger rail car egress 

environment.

4.2.2.2 Computer-Generated Individual-Movement Models

Individual-movement models attempt to model the egress behavior of occupants as they assess 

the situation and make decisions based on their personal characteristics and any other imposed 

limiting factors. Decision-making is typically controlled by the interaction between individual

occupant characteristics, conditions and events experienced during the particular scenario, and 

the algorithmic rules built into the model. The sophistication and scope of the representation of

this interaction vary between models.

Many of these models give the User the flexibility to define characteristics for each individual 

person or groups of people, in relation to the structure. For example, variable factors, such as 

maximum walking speed, age, gender, motivation, and knowledge of the passenger rail car 

structure, can influence the egress behavior of each specific individual, and thus the group. 

These variable factors can be interpreted in terms of the effect of individual agility on egress 

time. Time predictions can be generated for specific passenger rail car egress scenarios, such as

egress using only one car door to ROW or low-platform locations under emergency lighting 

conditions. The reliability of the model egress time predictions is dependent on the availability 

of observational data collected from actual people movement. Model capabilities may also make 

it easier to include some of the unique aspects of passenger rail car egress scenarios.

Individual-movement models calculate travel speed differently from hydraulic models. Instead 

of having a global speed controlled by density, each person has his or her own individual 

maximum walking speed. If there are no hindrances (e.g., injuries), individuals will move with 

this speed until they encounter an obstacle, such as a person moving more slowly. At this point,
32

the speed of the faster person behind is “capped” by the person in front, unless the space is wide 

enough for two-abreast movement. The exact method used to achieve this effect differs between 

models since they employ headway calculations, approximate speed/density relationships, and 

incur delays when vying for specific locations, etc. Depending on the decision-making rules 

employed in the model, persons may “decide” to overtake other persons, choose another route if 

available, or continue in the queue. Some models add a degree of randomness to these decisions. 

Individual-movement models are more suited than hydraulic models to incorporating decisionmaking because the decisions are more naturally translated into their individual movement (see

Figure 2.

Figure 2. Individual-Movement Model – Simple Example

The inclusion of decision-making in the calculation of egress time is important because it gives 

the computer model the ability to simulate a wider range of emergency scenarios. This model 

capability takes into account the fact that passenger rail car occupants are faced with different 

choices, depending on the emergency egress scenario variables. The same population will react 

differently if the passenger train is stalled on a bridge over water, as opposed to if the train is 

stalled inside a tunnel. The influence of the presence of trained railroad personnel can be 

incorporated more readily into the egress time calculations if the User can define individuals in 

the group who have particular attributes that lead them to make different decisions and take 

different actions from other passengers. By representing occupant behaviors individually, rather 

than imposing them across the entire group, individual-movement models allow new conditions 

to develop, providing new insights into different accident scenarios and potential mitigation 

efforts. 

Some computer models simulate the effect of fire conditions on the occupants as they evacuate 

the structure. For example, hazardous smoke conditions in one location may overcome some 

occupants, while individuals located in another area would still be able to move to the exit. In 

other models, calculated egress times can be compared with calculations of independent hazard 

development to see if occupants are able to escape, in the minimum time necessary, the 

hazardous (e.g., untenable) conditions. If individuals must traverse an area directly affected by 

fire, smoke, or other toxic products, delays caused by the interaction with the hazardous 

conditions must be reflected in the egress times. 
33

4.3 PASSENGER RAIL CAR EGRESS TIME SIMULATION

FAA described the following objectives for computer models which simulate aircraft passenger 

evacuation that could be adapted for application to passenger rail car egress [35]:

“(1) The model must be capable of analyzing various cabin configurations without requiring 

changes to its source code.

(2) The model must run in real time or near real time.

(3) The model must be able to conduct simulations of both certification tests and accident 

evacuations.

(4) The model must consider relationships among passengers. For instance, the influence 

on evacuation behavior of a mother traveling with an infant versus a passenger 

traveling alone must be incorporated.

(5) The model must consider the impact a flight attendant’s behavior has on passengers. 

This feature will allow passenger management to be explored, such as determining the 

optimal number of flight attendants per passenger load.

(6) The model must offer dynamic behavior, as opposed to behavior that is fixed at the 

time of model execution. That is, the model must allow the behavioral characteristics 

to change over time.

(7) The model must take into account the dynamic, toxic environment of fire and consider 

the physiological, as well as psychological effects of fire and smoke on human 

behavior. 

(8) The model must support simulation output analysis, design of experiments, and 

sensitivity analysis.

(9) The model must provide animation of the evacuations to support model validation and 

presentation.”

In contrast to aircraft evacuation modeling, methods of estimating egress times by U.S. 

passenger railroad system operators and rail car builders have not employed evacuation 

simulation modeling.

Moreover, none of the egress simulation computer models described in Chapter 5 of this report 

appear to have the ability to directly simulate all of the various operating environments for 

passenger rail car egress since it would be difficult and costly for any model to take into account 

all the variable factors (see Section 3.7) that could influence passenger rail car emergency egress 

time. 

The results of passenger rail car egress experiments can provide the necessary data for 

developing a reliable passenger rail car-specific egress model for egress time prediction if the 

numerous factors that affect egress flow rate are carefully considered and specifically controlled 

in a repeatable and consistent way. 

It may also be possible to determine appropriate delay factors for each category of emergency 

scenario, including those that require opening a rail car door and exiting to a low-platform station 

or to the ROW, which could be applied to the exit availability or added to the total egress time. 
34

For example, commercial passenger airplane evacuation studies have allowed for the 

characterization of delays associated with occupant use of emergency slides (see References [36]

and [99]). A similar characterization for passenger rail car egress could be delays associated 

with sitting jumps by passengers from rail cars that do not have side-stairway steps installed 

(e.g., Acela Express trains which normally only stop at high-platform stations). 

Moreover, individual agility and physical obstacles have a significant impact on the amount of 

time necessary for persons to exit from a passenger rail car. Experiments to evaluate rail car-exit 

geometry for simulating egress to low-platform or ROW locations, should employ “withinsubject” designs (i.e., the same participants must be used for all conditions) so that differences in 

individual abilities do not affect the results of the experiment).

However, because of the inherent risk of injury to participants, passenger rail car egress 

experiments that provide new egress-related time data involving higher-risk emergency scenarios 

(e.g., egress from cars overturned or extremely tilted on their sides, egress from exit windows, 

egress of severely mobility-impaired occupants, etc.) to validate computer models that simulate 

egress may not be feasible or may be very expensive to conduct due to safety considerations.

Chapter 5 provides a survey review of egress computer models and their applicability to specific 

types of passenger rail car emergency scenarios.

4.4 SUMMARY

Egress time calculations for simple structures with low-level risk probability (e.g., occupant 

exiting from passenger rail cars at high-platform stations) can be routinely carried out through 

reference to structural specifications and design standards, or by using “back-of-the-envelope” 

hand-calculation methods. However, for complex egress situations, such as exiting from a 

passenger rail car to a low-platform station or ROW location, advanced modeling approaches 

may provide a more accurate prediction of egress time. 

For egress time predictions to reflect the actual railroad operating environment, regardless of 

whether the model uses calculations based on a hydraulic or individual-movement model,

passenger rail car egress experiment results can provide the necessary data for developing a 

reliable passenger rail car-specific egress model if the numerous factors that can affect egress 

flow rate are carefully considered and specifically controlled in a repeatable and consistent way. 

However, it is noted that individual agility and physical obstacles have a significant impact on 

the amount of time necessary for persons to exit from a passenger rail car. 
35

5. APPLICABILITY OF EGRESS COMPUTER MODELS TO 

PASSENGER RAIL CAR EMERGENCY SCENARIOS

Numerous computer models for egress time prediction have been developed. The majority were 

developed for use in predicting or evaluating egress from a range of public building structures, 

including high-rise office buildings, stadiums, and mass transit stations. Along with other 

performance metrics, such as the distances traveled or the congestion experienced, the models

also typically give the User an estimate of the potential time it would take for all occupants to 

reach the exterior of the structure (e.g., the point of safety). 

5.1 EXISTING EGRESS COMPUTER MODELS

References [100] [101] [102] contain more detailed information about the egress computer 

models reviewed in this chapter. In addition, Section 5.5 contains a reference list for the models

that are summarized in Table 3. The column descriptions used have the following meanings: 

Model Name – The version number is included only if it is actually part of the name, e.g., 

“EVACNET4,” rather than “EVACNET+.” 

Author(s) – The author(s) of the model, as noted in the available documentation.

Organization – The employer or sponsor of the author(s). In some instances it may be the 

organization that currently maintains the software.

Date – The year of release, as determined from the references reviewed. A blank entry 

indicates that the references used in this report gave no information about when the models 

were developed.

Typical Use – Structures that are typically analyzed using this model.

Model Description, Type – The basic principle behind the egress calculations: hydraulic or 

individual movement. “Probability driven variations” means that the model is capable of 

conducting several simulations to evaluate the impact of probabilistic variables within the 

model.

Model Description, Type and Data Source – The basis for the model assumptions, defaults,

and calculations. “Random Selection” means that the model uses the Monte Carlo 

(stochastic) technique to choose values for parameters that vary with a known probability 

distribution.

Required Inputs and Options – Data inputs needed and the options available to the User. 

“Standard” inputs are: layout and dimensions of the structure; number of people; and 

quantity, dimensions, locations and capacity of exits.

Output and Results – Information given by the model upon completion of the calculations.
36

Table 3. Overview of Current Egress Computer Models – Sheet 1

MODEL

NAME

ORGANIZATION

& AUTHOR(S)

DATE

DEVELOPED

TYPICAL 

USE(S)

MODEL DESCRIPTION

INPUTS & 

OPTIONS

OUTPUT 

& RESULTS Type Data 

Source(s)

ALLSAFE 

Interconsult, Group. 

Norway

A. Heskestad

G. Jensen

1998 Buildings, 

passenger 

vehicles

Hydraulic Research by 

IGP and 

SINTEF

Standard; occupant 

characteristics like 

sleep/wake, route 

familiarity and social 

role

Minimum total 

evacuation time for all 

occupants

ASERI

Integrierte 

Sicherheits-Technik,

(Integrity-SecurityTechnology)

Frankfurt, Germany

V. Schneider

1995 Buildings, 

mass 

transport 

vehicles

Individual 

movement 

with 

probability 

driven 

variations 

Statistical 

analysis of 

options; 

Purser's model 

for tenability; 

effects of 

visibility studies 

by Jin; 

observations of 

evacuations

Standard; fire conditions 

versus time; 

characteristics of 

individuals, including 

body size, incapacities, 

social interdependence; 

building knowledge

Evacuation times of 

individual occupants, 

incorporating effects 

of heat, smoke, toxic 

products and visibility; 

bottlenecks in the 

egress system

BGRAF

NJ Institute of 

Technology

F. Ozel+

1985 Buildings Individual 

movement

Random 

selection

Standard Evacuation or 

incapacitation time for 

individuals

CRISP

Fire Research 

Station, United 

Kingdom

WGB Phillips

J. Fraser Mitchell

1992 Buildings Individual 

movement 

with 

probability 

driven 

variations

Tenability from 

Purser

Standard

Options: Difficulty of 

use of each vent; 

behavioral 

characteristics of 

occupants

Evacuation or 

incapacitation time for 

individuals

EESCAPE

Cobau Ltd., Austria

E. Kendik

R. Friedman

1983 Multistory 

buildings

Hydraulic Predtechenskii 

and Milinskii

Standard Total evacuation time

EGRESS

AEA Technologies, 

United Kingdom

N. Ketchell

1991 Buildings, 

rail stations, 

ships, buses

Hybrid –

hydraulic 

with some 

basic 

individual 

movement

Predtechenskii 

and Milinskii; 

full-scale 

evacuations

Standard Total evacuation time
37

Table 3. Overview of Current Egress Computer Models – Sheet 2

MODEL

NAME

ORGANIZATION

& AUTHOR(S)

DATE

DEVELOPED

TYPICAL 

USE(S)

MODEL DESCRIPTION

INPUTS 

& OPTIONS

OUTPUT

& RESULTS Type Data

Source(s)

EVA

Rutgers University

H.C. Gea

2004 Aircraft Individual 

movement

Structure layout, 

physical attributes of 

passengers, occupancy 

level, group behavior

Distributions of total 

aircraft evacuation 

time, distributions of 

exit usage time, no. 

of passengers using 

each exit, 

visualization 

(animation) of 

evacuation process

EVACNET4 

University of Florida

Kisko & Francis

1984 Buildings Hydraulic Fruin; Pauls Standard (network 

description of building); 

initial number of people 

at each node

Minimum total 

evacuation time; 

floor clearing times; 

identifies bottlenecks

EVACS 

Fujita & Building 

Research Institute, 

Japan

Takahashi & Tanaka

1988 Buildings Hydraulic Study by K.

Togawa; and 

work of 

Predtechenskii 

and Milinskii

Standard; number of 

people in each space;

walking speed

Total evacuation 

time, congestion 

points in building

EVACSIM

Victoria University of 

Technology, Australia

L. Poon

1994 High-rise 

buildings

Hydraulic Nelson & 

MacLennan

Standard; behavioral 

characteristics, 

maximum travel speed, 

body size 

Optional: fire conditions

Evacuation sequence 

for each occupant

EXIT89

NFPA

R. Fahy

1991 High-rise 

buildings

Hydraulic Predtechenskii 

and Milinskii; 

Hillier & 

Lieberman; 

Levin

Standard; fire 

conditions. 

Options: explicit 

inclusion of children, 

disabled, etc.; Userspecified delays, 

walking speeds, and 

route familiarity

Total evacuation time

for each exit element, 

floor, and/or the 

entire building. 

Also can track the 

movement of each 

occupant throughout 

evacuation 
3

8

Table 3. Overview of Current Egress Computer Models – Sheet 3

MODEL 

NAME

ORGANIZATION

& AUTHOR(S)

DATE

DEVELOPED

TYPICAL 

USE(S)

MODEL DESCRIPTION

INPUTS

& OPTIONS

OUTPUT

& RESULTS Type Data 

Source(s)

EXITT

NBS (NIST)

B. Levin

1987 Small 

residential 

buildings

Individual 

movement

Controlled 

experiments; 

case studies; 

expert judgment

Standard; age, sex, 

location, and condition 

of occupants; smoke 

conditions; smoke 

detector action 

Evacuation sequence 

for each occupant

air

EXODUS

University of 

Greenwich, UK

Galea, Galparsoro &

Owen

1993 Aircraft, 

mass 

transport 

vehicles

Individual 

movement

Evacuation 

studies, 

especially, 

aircraft (e.g., 

Muir)

Standard; fire 

conditions; detailed 

demographics; 

physical attributes

Evacuation time of 

each individual and 

their physiological 

condition

building

EXODUS

University of 

Greenwich, UK

Galea, Lawrence &

Gwynne

1993 Buildings, 

especially 

public 

assembly 

occupancies

Individual 

movement

Studies of 

building 

evacuations; 

human behavior 

research, e.g., 

Bryan, Wood, 

Jin, Fruin,

Purser, etc.

Standard; fire 

conditions; detailed 

demographics; 

physical attributes; 

procedure employed

Evacuation time of 

each individual and 

their physiological 

condition, component 

performance 

maritime

EXODUS

University of 

Greenwich, UK

Galea, Lawrence & 

Gwynne

2007 Passenger

ships

Individual 

movement

Studies of 

building 

evacuations; 

human behavior 

research e.g., 

Bryan, IMO, 

Wood, Jin, Fruin,

Purser, etc.

Standard; fire 

conditions; detailed 

demographics; 

physical attributes

Evacuation time of 

each individual and 

their physiological 

condition, component 

performance

FDS_Evac

VTT (Finland) & 

NIST

Korhonen & 

Hostikka

2005 Buildings Individual 

movement

Existing Helbing 

model; research 

conducted by 

Langston, 

Thompson, & 

Proulx

Standard; fire 

conditions (via FDS); 

detailed 

demographics; 

physical attributes

Evacuation time of 

each individual and 

their physiological 

condition
39

Table 3. Overview of Current Egress Computer Models – Sheet 4

MODEL

NAME

ORGANIZATION

& AUTHOR(S)

DATE 

DEVELOPED

TYPICAL 

USE(S)

MODEL DESCRIPTION

INPUTS &

OPTIONS

OUTPUT &

RESULTS Type Data 

Source(s)

GRIDFLOW

Building Research 

Establishment, UK

Purser

2002 Buildings Individual 

movement

Nelson & 

MacLennan, 

Purser, Jin, 

Thompson

Standard; fire 

conditions; detailed 

demographics; physical 

attributes

Evacuation time flow 

conditions, component 

performance

LEGION

University of 

Warwick, UK

G.K. Still

Legion Limited

1997 Buildings Individual 

movement

Maia Institute Standard; fire 

conditions; detailed 

demographics; physical 

attributes

Evacuation time of 

each individual and 

their physiological 

condition, component 

performance

MAGNETIC 

SIMULATION

Kyoto University, 

Kyoto1 & Fukui 

University, Fukui2

, 

Japan

Okazaki1 & 

Matsushita2

1979 Buildings; 

analysis of 

queue 

spaces, e.g., 

turnstiles at 

rail stations

Individual 

movement

Physical laws 

governing 

magnetic fields

Standard; actual starting 

point of individuals, 

walking speed, delay to 

start walking. 

If large no. of 

occupants, data are 

entered for groups of 

people, not individuals

 Option: specify 

destination of occupants

Visual depiction of 

evacuation process; 

evacuation time; 

points of congestion 

and amount of time 

spent in queue 

MYRIAD I & II

(Evolution of 

VEGAS)

Crowd Dynamics,

Ltd, UK

G.K. Still

1992 (VEGAS) Large 

crowds in 

public 

spaces

Individual 

movement

Not enough 

information

Geometry imported from 

CAD program; 

objectives of individuals

Movement patterns of 

occupants; congestion 

points; egress time

NOMAD

Daamen & 

Hoogendoorn

Delft University of 

Technology

2009 Buildings, 

large public 

spaces

Individual

movement

Observations or 

assumptions 

about walking 

speeds, stairclimbing 

speeds, etc.

Description of the 

walking infrastructure 

Parameters describing 

behavior of the different 

pedestrian types

Activity patterns 

Demand for each 

activity pattern 

Location of detectors

Run-time parameters
40

Table 3. Overview of Current Egress Computer Models – Sheet 5

MODEL

NAME

ORGANIZATION

& AUTHOR(S)

DATE

DEVELOPED

TYPICAL 

USE(S)

MODEL DESCRIPTION

INPUTS &

OPTIONS

OUTPUT &

Type Data RESULTS

Source(s)

PATHFINDER

RJA Group

J. Cappucio

(Now, Thunderhead 

Engineering)

2003

(relaunched 

2011)

Buildings Individual

movement

Nelson & 

MacLennan, 

Reynolds,

Amor

Structure layout, 

occupant 

characteristics, 

occupant behaviors, 

individual or hydraulic 

movement

Evacuation time, flow 

rates, component/floor 

performance of each 

individual and their

physiological condition

PEDROUTE

Halcrow Fox, UK

G. Weston

1984 Public 

transport 

stations

Hydraulic Surveys at 

underground 

train stations

Structure layout, 

occupancy levels 

versus time during peak 

and near peak use 

times of day; User can 

enter flow rates of 

stairs, platforms, etc. or 

use defaults

Passenger flow 

patterns; average 

delay; areas of 

congestion; levels of 

use of building 

elements, such as 

escalators or stairs

SIMULEX

University of 

Edinburgh, UK

Thompson & 

Marchant

1994 Large,

complex 

buildings, 

including 

transit 

stations

Hydraulic Predtechenskii 

& Milinskii; 

Fruin

Standard, occupant 

density in each area of 

the structure

Minimum evacuation 

time of structure

STEPS

Mott McDonald

Group, UK

Hoffman & Henson

1997 Public 

assembly 

occupancies, 

including 

train stations

Individual 

movement

Not enough 

information

Standard; familiarity 

with the environment, 

patience and walking 

speed.

3-D visualization of the 

evacuation; evacuation 

times; flow rates 

through exits; 

bottlenecks

WAYOUT

Fire Modeling & 

Computing, Australia

V. Shestopal

2000 Multiroom & 

multistory 

buildings

Hydraulic Predtechenskii 

& Milinskii

Standard; start times 

for occupants in 

different sections of the 

structure

Maximum evacuation 

time for a group
41

5.2 FEATURES AND CAPABILITIES OF EXISTING EGRESS COMPUTER 

MODELS

The egress computer models evaluated in this study are either hydraulic models that use 

established calculation methods similar to those found in the SFPE Handbook [90], or 

individual-movement models that simulate the egress of individual persons. The features and 

capabilities of each model are summarized in Table 4, based on the descriptive documentation 

available, which varies widely. The column titles in Table 4 have the following meanings: 

Egress Path Characteristics – The model’s ability to account for exits being blocked before 

or during evacuation, different levels of difficulty for each exit type, and the impact of 

different levels of lighting. 

Controlled Egress – Whether the model can simulate the control of egress being directed by 

a crew member or other person. 

Occupant Characteristics – Whether the model can simulate individual characteristics in the 

population and options for varying its demographic breakdown. “Global” means that the 

User can enter the number of people (or a density of people) in an area. “Individual,” means 

that the User can enter details about each occupant individually. Many of the individual 

models also have the option to use a global entry method. 

Decision-making – Whether the model can simulate the decision-making of occupants 

during evacuation and to what extent this is done.

Fire Conditions – Whether the model can simulate the impact of fire, smoke, toxic products, 

and their interaction with occupants. 

5.3 APPLICATION OF COMPUTER MODELS TO RAIL CAR EGRESS 

SCENARIOS

As discussed in Chapter 4, egress time from a passenger rail car depends on variable factors that 

are unique to this type of transportation vehicle, because of its design and railroad operating 

environment. The impact of many relevant variable factors has not been experimentally 

quantified. As a result, some egress models do not include many of the relevant factors in a 

potential passenger train emergency scenario, limiting the utility of these models to passenger 

rail car egress simulations. Therefore, a thorough evaluation of the model must assess its 

capabilities for at least the following categories: 

• Egress to an adjacent car or to a station platform;

• Egress to ROW (track level); and 

• Egress from a car on its side. 
42

Table 4. Key Features of Egress Computer Models in Relation to Passenger Rail Car Egress Scenarios – Sheet 1

MODEL

NAME

EGRESS 

CHARACTERISTICS

CONTROLLED 

EGRESS

OCCUPANT CHARACTERISTICS DECISIONMAKING

FIRE

CONDITIONS Entry Method Demographics

ALLSAFE

Not enough available 

information

No Not enough 

information

Social roles, e.g., 

patients, visitors, 

customers

Not modeled Not modeled

ASERI

Availability of any exit 

can change during the 

simulation if fire 

conditions become 

hazardous in that area

No Can do both global 

and individual

User chooses 

random computer 

assignment or 

generic person

Heat, smoke, and 

toxic product values 

over time imported 

from a fire hazard 

model

Passengers' 

behavioral responses 

dependent on 

individual thresholds

Heat, smoke, and toxic 

product values over 

time imported from a 

fire hazard model

Passengers' 

behavioral responses 

dependent on 

individual thresholds

BGRAF

Not enough available 

information

Not enough 

available 

information

Not enough 

information

Not enough 

information

Route choice 

decisions based on 

environment and 

other occupants

Not enough 

information

CRISP

Difficulty of use can be

adjusted by tenability 

calculations 

Availability is initially 

randomly set by the 

program, then is 

controlled by the 

difficulty of the exit 

Smoke obscuration is 

modeled

Not explicitly 

modeled, but 

could possibly 

be captured in 

the assigned 

degree of

difficulty

User can define 

individuals or have 

random placement 

of individuals 

performed by the 

simulation

Breakdown by roles, 

such as leader, led, 

dependent 

These can be 

randomly assigned to 

individuals in the 

population

Decisions are based 

on rules associated 

with their role, 

interactions with the 

environment, e.g., 

smoke blockage and 

random selection 

based on statistics

Flame spread, heat, 

smoke, toxic products, 

obscuration effects

EESCAPE Availability set for entire 

simulation

No Global One generic person Not modeled Not modeled

EGRESS Availability set for entire 

simulation

No Global One generic person Not modeled Not modeled

EGRESSPRO Availability set for entire 

simulation 

No Global One generic person Estimates time to 

detection 

Estimates time to 

detection 
43

Table 4. Key Features of Egress Computer Models in Relation to Passenger Rail Car Egress Scenarios – Sheet 2

MODEL

NAME

EGRESS 

CHARACTERISTICS

CONTROLLED

EGRESS

OCCUPANT CHARACTERISTICS DECISIONMAKING

FIRE

CONDITIONS Entry Method Demographics

EVA

Availability of an exit 

can change during the 

evacuation, based on 

fire or other conditions

Trained crew to 

redirect 

passengers 

Global / Individual All passenger 

physical attributes are 

summed as a 

passenger fitness 

level 

Not modeled Not modeled

EVACNET4 Availability set for entire 

simulation 

No Global One generic person Not modeled Not modeled

EVACS Availability set for entire 

simulation 

No Global One generic person Not modeled Not modeled

EVACSIM

Availability set for entire 

simulation 

Can include 

evacuation 

warden to direct 

egress of 

occupants

User can define 

characteristics for 

individuals or 

group types

By roles, e.g. 

passenger, 

personnel, etc.

Can import from a fire 

hazard model

Can import from a fire 

hazard model

EXITT

Exits can be blocked by 

smoke

No Individual Age; sex; location; 

physical condition, 

travel speed

Smoke layer density 

and position are 

imported from a fire 

hazard model

Smoke layer density 

and position are 

imported from a fire 

hazard model

air

EXODUS

Availability of an exit 

can change during the 

evacuation based on fire 

conditions, awareness,

or User selection

Trained 

personnel can 

greatly impact 

evacuation

Individual Sex; age; weight; 

condition; mobility; 

agility; travel speed; 

breathing volume; 

incapacitation dose; 

response time; drive; 

patience

Choices based on 

rules and heuristics 

derived from 

statistical analysis of 

human behavior 

studies and "90 

second" certification 

tests

Individual adaptation 

possible

Heat, smoke, toxicity 

info entered from 

calculations done by a 

hazard development 

model

building

EXODUS

Availability of an exit 

can change during the 

evacuation based on fire 

conditions, awareness, 

congestion or User 

selection

Trained 

personnel can 

greatly impact 

evacuation

Individual Sex; age; weight; 

condition; mobility; 

agility; travel speed; 

breathing volume; 

incapacitation dose; 

response time; drive; 

patience

Choices based on 

rules and heuristics 

derived from 

statistical analysis of 

human behavior 

studies

Individual adaptation

possible

Heat, smoke, toxicity 

info entered from 

calculations done by a 

hazard development 

model
44

Table 4. Key Features of Egress Computer Models in Relation to Passenger Rail Car Egress Scenarios – Sheet 3

MODEL 

NAME

EGRESS 

CHARACTERISTICS

CONTROLLED 

EGRESS

OCCUPANT CHARACTERISTICS DECISIONMAKING

FIRE 

CONDITIONS Entry Method Demographics

maritime

EXODUS

Availability of an exit 

can change during the 

evacuation, based on 

fire conditions, 

awareness, congestion

or User selection

Yes Individual Sex; age; weight; 

condition; mobility; 

agility; travel speed; 

breathing volume; 

incapacitation dose; 

response time; drive; 

patience

Choices based on 

rules and heuristics 

derived from 

statistical analysis of 

human behavior 

studies

Individual adaptation

possible

Heat, smoke, toxicity 

info entered from 

calculations done by a 

hazard development 

model

FDS_Evac

Availability of an exit 

can change during the 

evacuation

Yes Individual Sex; response time;

speed; age

Choices based on 

function, modified by 

proximity and exit 

selection

Heat, smoke, toxicity 

info entered from 

calculations done by a 

hazard development 

model

GRIDFLOW

Availability set for entire 

simulation

Yes Individual Initial delay, speed, 

FED characteristics 

Exit selection, local 

navigation

Heat, smoke, toxicity 

info entered from 

calculations done by a 

hazard development 

model

LEGION Not enough information Yes Individual Not enough 

information

Not enough 

information

Not enough 

information

MAGNETIC 

SIMULATION

Availability set for entire 

simulation

No Individual and 

global

Maximum walking 

speed

Not modeled Not modeled

MYRIAD

Availability set for entire 

simulation

No Global and 

individual

Walking speed Limited decisionmaking based on 

congestion 

experienced along 

egress route

Not modeled

NOMAD

Demand for a given exit 

can be time dependent

Not enough 

information

Individual Walking speed, body 

size, trip purpose, 

etc.

Pedestrians interact 

with each other and 

obstacles based on 

observational studies

Not modeled
45

Table 4. Key Features of Egress Computer Models in Relation to Passenger Rail Car Egress Scenarios – Sheet 4

MODEL 

NAME

EGRESS 

CHARACTERISTICS

CONTROLLED 

EGRESS

OCCUPANT CHARACTERISTICS DECISIONMAKING

FIRE 

CONDITIONS Entry Method Demographics

PATHFINDER

Availability set for entire 

simulation, although 

agent may select 

between them based on 

congestion

Yes Global Age; sex, impairment;

speed; size; profile;

initial delay; task

Decision-making

based on steering, 

congestion 

experienced along 

egress route, 

procedure

Not modeled

PEDROUTE No No Global Not enough 

information

Not modeled Not modeled

SIMULEX

Availability set for entire 

simulation

No User can choose 

individual or global

Building familiarity 

(e.g., office staff 

versus visitor); body 

type; response time; 

exit bias

Reevaluation of 

egress path based on 

obstructions 

Not modeled

STEPS

Availability can change 

during simulation

Not enough 

information

Individual Familiarity with 

structure; walking 

speed; patience; 

body size; fitness 

levels

Occupants change 

egress routes based 

on familiarity, 

queuing, patience, 

and fitness levels

Not enough 

Information

WAYOUT Availability set for entire 

simulation

No Global Not considered Not modeled Not modeled
46

5.3.1 Egress to Adjacent Car or Station Platform (Including Fire)

Typically, the simplest egress scenario is the situation, with no fire or smoke inside the passenger 

rail car, where passenger egress is from one rail car end door into the adjacent car. The next 

simplest type of egress scenario from a rail car is passenger egress from the side doors when a 

train is located at a high- or low-platform station. Passengers are usually able to exit via the side 

doors, which are the normal entrance points. For these scenarios, the majority of the calculation 

methods, including hand calculations, are appropriate. The parameters that have the greatest 

impact on the results produced for rail car egress are essentially the same as for building 

evacuations; e.g., aisle (corridor) width; door quantity, width, and location; occupant load; travel 

distance; and travel speed. Without obstacles in the egress path and possible interruptions to 

egress that are associated with many accident scenarios (e.g., finding a blocked exit and needing 

to decide on a new route), the effects of individual decision-making are small.

In contrast, if a fire occurs in the rail car to be evacuated, more factors must be considered to 

obtain an accurate depiction of the evacuation. Fire and smoke can potentially block access to 

the preferred exits and egress route. In addition, decreased visibility and the effects of toxic 

products can slow the decision-making and movement of occupants. Therefore, fire hazard 

development and its effect on the tenability of the space must also be modeled. 

Although it is theoretically possible to use hand and spreadsheet calculations to track hazard 

development, people movement, and the effect of fire and smoke on passenger rail car 

occupants, computer models can perform these simultaneous calculations more efficiently. 

Among the models reviewed, CRISP calculates fire hazard development and ASERI, EVA, 

EVAC, EVACSIM, EXIT89, EXITT, FDS-Evac, GRIDFLOW, and the three EXODUS models

all have the capability to import the time-based data from computer fire models and integrate 

their effect on the evacuation event. Documentation for some of the other models suggests that 

the User can complete the fire and egress modeling independently and then compare times to 

determine if tenability thresholds are reached before egress is complete, in which case, persons 

remaining on board the car are assumed to be dead. Although this latter practice has some value, 

it does not lend itself to incorporation of injuries and the influence on evacuation (travel speed 

and decisions to change route) of smoke and toxic products before the lethal threshold is reached. 

Of the nine models that can incorporate fire conditions into egress calculations, seven (ASERI, 

CRISP, EVA, EXITT, and the three EXODUS models) use the individual-movement approach, 

while EVACSIM and EXIT89 are hydraulic models. Moreover, ASERI, EVA, EXITT, FDSEvac, EVA, GRIDFLOW, and the three EXODUS models give the User the option to assign 

detailed physical attributes (such as smoke tolerance) to individuals or types of individuals. This 

feature allows potential modeling of individual differences in physiological response to fire, 

smoke, and toxic products. It is not clear from the available literature if CRISP has this 

capability. 

5.3.2 Egress to ROW (Track) Level

Evacuation from a passenger train located away from the station platform introduces the 

influence of the operating environment and a greater degree of decision-making. If passengers 

exit via the end door and a stairway is not available; or exit via side doors and cannot use the side 

stairway steps at all; there is a drop from the door sill to track level of about 4 ft (1.2 m). Having 
47

to jump a distance of 4 ft from the rail car to nonlevel ground with a potentially steep slope can 

be intimidating for some people and virtually impossible for those that are physically impaired. 

Disorientation from being in a dark tunnel with knowledge that a high-voltage third rail may be 

nearby, or the fear induced by being suspended on a railroad bridge over water, are further 

complications. 

None of the egress models reviewed in this chapter explicitly addresses the difference in egress 

path characteristics when occupants exit from a building-like structure compared with exiting 

from a passenger rail car. Instead, the last step from the building door to the exterior is usually 

considered a trivial matter. However, in some of the models, it is possible to account for the 

delays that can result during egress from particular exits. CRISP allows the User to assign 

different degrees of difficulty to the use of each exit. AirEXODUS attaches time delays to the 

use of emergency exit elements, such as slides, based on observations taken during certification 

testing of aircraft. ASERI, EVA, EXIT89, SIMULEX, and STEPS also have specific features 

that allow inclusion of this variable factor. 

Three selected papers describe the use of building egress models to develop passenger rail car 

egress time estimates for different exit paths to a variety of locations. 

A 2011 paper describes the use of the STEPS model to develop egress time predictions for egress 

from two high-speed trainsets, based on the actual data obtained from the 2009 Spanish Railroad 

RENFE high-speed trainset evacuation drills, as described in Chapter 2 [31]. The STEPS model 

was selected due to its capability to change the availability of exits that can be used by occupants 

during the simulation. Fourteen various scenarios were simulated, which included different fire 

locations on the train (and thus car exit locations) and evacuation to either a tunnel walkway 

platform or the ROW. A major focus of the analysis was the effect of train crew instructions on 

the egress time. Before completion of this report, the authors were unable to complete a 

quantitative analysis of the 2011 study (and other related Spanish studies cited in that paper). 

However, since the study used data from actual passenger trainset evacuation drills as input to 

the STEPS model, the study recognizes the important effect on egress time of train crew 

directions, passenger behavior, and the unique railroad operating environment, including train 

design and exit locations such as tunnels. 

A 2007 paper describes the results of a study using the NOMAD model to develop egress time 

predictions from a variety of rail cars to a side walkway in a tunnel [103]. The study results 

include evacuation time estimates as a function of car type and capacity, number of doors, and 

load factors. The NOMAD study also described the option to include different transit times 

through a doorway depending on the different elevations in the door threshold and the walkway. 

For example, a 19.6-in (50-cm) difference in height from the door threshold to the walkway was 

assumed to take 2 seconds for the average person to traverse. With a door width of 4.3 ft 

(1.3 m), the study assumption was that 1.5 persons could exit simultaneously through the door, 

thus producing an egress flow rate of .75 pps (45 ppm). 

A 2001 paper describes the results of SIMULEX runs for exiting from 4- and 8-car trains to 

walkways located adjacent to the trains in a 2-track tunnel; and from the end door of an 8-car 

train to the track level of a 1-track tunnel [104]. The model simulations were based on 150 

persons (4-car train) or 200 persons (8-car train) exiting from each car, with a walking speed of

3.3 fps (200 fpm) (based on NFPA 130, 2000 edition [95]). The paper concluded that that there 
48

was very little benefit associated with increasing the cross passage width because queuing 

occurred on the 36-inch (.9-meter)-wide walkway. However, the paper did indicate that a

meaningful reduction in total egress time for the 1,600-passenger 8-car train could be achieved if 

an end-door “gangplank” were provided to allow occupants to promptly exit the car down to the 

track level and then walk out to the portal. The egress flow rate was estimated to be 1.66 pps 

(95 ppm), if a 16-foot (4.8-meter)-long, 4-foot (1.2-centimeter)-wide ramp were available for 

passengers to descend to the ROW (track level) for the 1,600 passengers. Use of this gangplank 

could reduce train egress time from 29.5 minutes to less than 17 minutes. However, the 

logistical challenges of storing and deploying a 16-foot (4.8-meter)-long, 4-foot (1.2-meter)-wide 

gangplank on the train or in train tunnels were not addressed.

NOMAD was previously validated by laboratory walking speed experiments for normal walking 

conditions; however, neither the SIMULEX nor the NOMAD egress time predictions were based 

on observations of persons actually exiting from a passenger rail car. In addition, neither of the 

of the two cited studies considered the effect of occupant mobility impairments which could 

impact the amount of time necessary for persons to exit from a passenger rail car, depending on 

its location. 

For any model to realistically simulate the railroad operating environment, observational data 

regarding what people do when actually exiting from a passenger rail car are necessary. Most of 

the body of knowledge about people movement from passenger trains to the outside environment 

is contained in NTSB and other investigation reports. However, this information is inadequate 

for modeling purposes because those reports do not typically contain the necessary detailed data 

for model input, such as the average time for people to climb down from an end or side door 

located 4 ft (1.2 m) above the ground or jump down from an emergency window located 

7 ft (2.1 m) above the ground. In addition, for these “inconvenient” egress environments,

mobility-impaired, as well as injured passengers (as a result of a collision or derailment), will be 

slow to or unable to exit the car without assistance. 

The reciprocal of the occupant flow rate from the emergency exit comprises the egress time, in 

which case a hand-calculation or hydraulic model may provide adequate accuracy in predicting 

that time, if the population size is known. However, decision-making and other occupant 

characteristics are likely to have a significant impact on passenger rail car egress time. 

Accordingly, the use of individual-movement models is necessary to simulate complex passenger 

train emergency scenarios. 

5.4 EGRESS FROM RAIL CARS THAT HAVE OVERTURNED ONTO THEIR 

SIDES

Perhaps the most difficult scenario to model is egress from a car overturned on its side. The 

University of Greenwich study cited earlier in this report [23] included two evacuation trials 

involving a passenger rail car on its side. According to that study, flow rates through the end 

doors (which become narrow doorways 5 ft (1.5 m) above the ground) could be as little as 

10 percent of the values specified in building exit standards. In addition, flow rates decreased an 

additional 50 percent in the presence of nontoxic smoke. With the car turned on its side, 

passengers had to walk on an irregular surface (e.g., windows, seats) since the available side 

doors and emergency exit windows were now located 10 ft (3 m) off the ground. In an actual 

emergency, such as a collision or derailment, the passenger rail car is also likely to contain 
49

debris, such as luggage. None of the existing egress computer models consider any of these 

factors, particularly egress from passenger rail cars through an opening that could be located 

10 ft (3 m) above the ROW (track).

5.5 MODEL REFERENCES

Two comprehensive modeling survey reports contain reviews of a variety of hydraulic and 

individual-movement computer egress models [100] [101] [102]. In addition, the following list 

contains references for the models reviewed in Table 3 and Table 4. 

The following specific references for the different computer models are listed by type of model

(in alphabetical order), Web site/email contact, model documentation, and author (in alphabetical 

order) of article or other document.

ALLSAFE

William Heskestad: awh@interconsult.com

Heskestad, A.W., et al., IGP AS Consulting Engineers. “Allsafe – An Engineering Tool for 

Evacuation Safety Design.” Proceedings of the Fire Safety by Design Conference, Oslo, 

Norway, July 10, 1995. 1996. Norway.

Heskestad, A.W., et al. IGP AS Consulting Engineers. “Systematic Fire Safety Design and 

Documentation by the Allsafe Tool,” Proceedings of Interflam ‘96: Seventh International Fire 

Science and Engineering Conference, Cambridge, England, March 26‒28, 1996. United 

Kingdom.

ASERI

IST-HSK@t-online.de

ASERI – Users’ Guide and Technical Reference (hard copy and complete online documentation).

Schneider, V. and Konnecke, R., Integrierte Sicherheits-Technik (I.S.T.). Simulating Evacuation 

Processes with ASERI. Frankfurt. 1996. Germany.

Schneider, V., I.S.T. “Application of the Individual-Based Evacuation Model ASERI in 

Designing Safety Concepts,” 2nd International Symposium on Human Behaviour in Fire, 

March 26‒28, 2001, Massachusetts Institute of Technology, Cambridge, MA. pp. 41‒51. 

Interscience Communications, London. 2001. United Kingdom.

BGRAF

Ozel, F. New Jersey Institute of Technology. Simulation of Processes in Buildings as a Factor 

in the Object Representation of Built Environments. Proceedings of Building Simulation '91,

August 20‒22, 1991, Nice, France. 1991. 
50

CRISP

http://www.bre.co.uk

Boyce, K., et al. “Survey Analysis and Modeling of Office Evacuation using the CRISP Model,” 

First International Symposium on Human Behaviour in Fire, University of Ulster, August 31, 

September 2, 1998. Ed: Shields, T.J, pp. 411‒420. 1998. Textro, Inc., Northern Ireland. United 

Kingdom.

Fraser-Mitchell, J.N., Fire Research Station (FRS), British Research Establishment (BRE). “An 

Object-Oriented Simulation (CRISP II) for Fire Risk Assessment,” Proceedings of the Fourth 

International Association for Fire Safety Science Symposium. Ottawa, Ontario, Canada, June 

13‒15, 1994. pp. 793‒804. 1994. 

Fraser-Mitchell, J.N. FRS, BRE. “Simulated Evacuations of an Airport Terminal Building, 

Using the CRISP Mode.” Proceedings of the Second International Symposium of Human 

Behaviour in Fire March 26‒28, 2001, Massachusetts Institute of Technology, Cambridge, MA. 

Interscience Communications, Inc. pp. 89‒100. 2001. United Kingdom.

EESCAPE

Kendik, E. Assessment of Escape Routes in Buildings and a Design Method for Calculating 

Pedestrian Movement. Society of Fire Protection Engineers (SFPE). SFPE Technology Report 

85.4. Boston, MA. 1985.

EGRESS

neil.ketchell@aeat.co.uk 

AEA Technology. AEA EGRESS User’s Manual. August 1993. United Kingdom.

AEA Technology. Modeling of Crowd Evacuation: Guidance on the Method. Report no.

AEA/CS/16405219/5/A, August 1995.

Ketchell, N., et al., AEA Technology. “The EGRESS Code for Human Movement and 

Behaviour in Emergency Evacuations.” Engineering for Crowd Safety, London, 

17‒18 March 1993. Institution of Civil Engineers. Ed: R.A. Smith, et al. pp. 361‒370. 

Elsevier, 1994. United Kingdom.

Ketchell, N., et al., AEA Technology. “Assessment and Simulation of Crowd Evacuation 

Issues.” Fire Engineering and Emergency Planning - Research and Applications. Paper 

presented at Eurofire '95, Nimes, France, March 25‒27, 1995. Ed: R Barham, et al. 1996. 

Ketchell, N., AEA Technology. A Technical Summary of the AEA Egress Code. AEA 

Technology. AEAT/NOIL/27812001/002(R), Issue 1. 2002. United Kingdom.

AEA Technology. Modeling of Crowd Evacuation: Guidance on the Method. Report no.

AEA/CS/16405219/5/A. August 1995. United Kingdom.
51

EVA

Chang, C-J, et al., Rutgers University. “Computer Simulations on Egress Assistant Devices

During Aircraft Emergency Evacuation,” Proceedings of the Fifth International Aircraft Fire 

and Cabin Safety Research Conference, Atlantic City, NJ, October 29‒November 1, 2007. 

Report no. DOT/FAA/AR-08/16. March 2008.

Chang, C-J, et al., Rutgers University. “Study of Optimal Passenger Flow Pattern During 

Emergency Evacuation,” Proceedings of the Fifth International Aircraft Fire and Cabin Safety 

Research Conference, Atlantic City, NJ, October 29‒November 1, 2007. Report no. 

DOT/FAA/AR-08/16. March 2008.

Gea, H.C., Rutgers University. “Genetic Algorithm Based Simulation Model for Cabin 

Evacuation, Proceedings of the Fourth International Aircraft Fire and Cabin Safety Research 

Conference, Lisbon, Portugal. November 15‒18, 2004. Report no. DOT/FAA/AR-04/48. 2005.

EVACNET4

Kisko, T.M., et al. EVACNET4 User’s Guide. University of Florida. 1998.

EVACS

Takahashi, K. and T. Tanaka. An Evacuation Model for Use in Fire Safety Design of Buildings.

Fujita Corporation and Building Research Institute. 1988. Japan.

EVACSIM

Drager, K.H., et al. “EVACSIM: A Comprehensive Evacuation Tool.” Proceedings of the 

Emergency Management and Engineering Conference, Managing Risk with Computer 

Simulation. Ed: M. Chinni, pp. 101‒108. 1994. 

Poon, L.S., Victoria University of Technology (VUT), Melbourne, Australia. “EvacSim: A 

Simulation Model of Occupants with Behavioral Attributes in Emergency Evacuation of HighRise Building Fires,” Proceedings of the Fourth International Association for Fire Safety 

Science Symposium, Ottawa, Canada, 1994. Ed: T.L. Kashiwagi, pp. 681‒692.

Poon, L.S. and V.R. Beck, VUT. “Numerical Modeling of Human Behavior During Egress in 

Multi-Story Office Building Fires Using EvacSim – Some Validation Studies,” 1st Proceeding 

for the International Conference on Fire Science and Engineering, Asiaflam'95, Hong Kong, 

March 15‒16, 1985. Eds: W.K. Chow, et al., pp. 163‒174. 1985.

EXIT89

Fahy, R.F., National Fire Protection Association (NFPA). “EXIT89: An Evacuation Model for 

High Rise Buildings,” Proceedings of the Third International Association for Fire Science 

Symposium, Edinburgh, Scotland, July 8-12, 1991. Eds: B. Cox and G. Langford, pp. 815‒823. 

Elsevier Scientifics Publishers. 1991.
52

Fahy, R.F., NFPA. “EXIT89: An Evacuation Model for High Rise Buildings – Model 

Description and Example Applications,” Proceedings of the Fourth International Association for 

Fire Science Symposium, Ottawa, Canada, July 13‒17, 1994. Ed: T. Kashiwagi, pp. 657‒668. 

1994.

Fahy, R.F., NFPA. “EXIT89: An Evacuation Model for High-Rise Buildings – Recent 

Enhancements and Example Applications,” Proceedings of the Seventh International Fire 

Research and Engineering Conference, March 26‒28, 1996. Interflam ‘96. 1996. Ed: C.

Franks and S. Grayson, pp. 1001‒1105. Interscience Communication, Limited, London. 1996.

EXITT

Levin, B.M. EXITT – A Simulation Model of Occupant Decisions and Actions in Residential 

Fires: Users Guide and Program Description. National Bureau of Standards (U.S.). Report no. 

NBS 87-3591. 1987.

Levin, B.M., National Bureau of Standards (U.S.). “EXITT – A Simulation Model of Occupant 

Decisions and Actions in Residential Fires,” Proceedings of the Second International 

Association for Fire Science Symposium, Tokyo, Japan, June 13‒17, 1988. Ed: T Wakamatsu, 

et al., pp. 561‒570. 1989.

EXODUS

http://fseg.gre.ac.uk/exodus

Bukowski, R.W., et al., National Institute of Standards and Technology (NIST). “Sensitivity 

Examination of the airExodus Aircraft Evacuation Simulation Model,” International Aircraft 

Fire and Cabin Safety Research Conference Proceedings, November 16‒20, 1998, Atlantic City, 

NJ. FAA/U.S. DOT. http://www.fire.tc.faa.gov/1998Conference/index.html. 1998. 

Filippidis, L., et al., University of Greenwich. Representing the Influence of Signage on 

Evacuation Behaviour within buildingEXODUS. Report no. 04/IM/119, CMS Press. December 

2004. United Kingdom.

Galea, E.R., et al., University of Greenwich (London). “Brief Description of the EXODUS 

Evacuation Model,” Proceedings of the 18th International Conference on Fire Safety, San 

Francisco, CA, January 1993, pp.149‒162. 1993.

Galea, E.R. and Perez Galparsoro, J.M., University of Greenwich. EXODUS: An Evacuation 

Model for Mass Transport Vehicles. UK CAA Paper 93006. 1993. United Kingdom.

Galea, E.R., et al., University of Greenwich. “The airExodus Evacuation Model and Its 

Application to Aircraft Safety,” Third Triennial Fire and Cabin Safety Conference, Atlantic City, 

NJ, October 22‒25, 2001. FAA/U.S. DOT. www.fire.tc.faa.gov/2001Conference. 2001.
53

Galea, E.R., et al., University of Greenwich, “The Development of an Advanced Ship 

Evacuation Simulation Software Product and Associated Large Scale Testing Facility for the 

Collection of Human Shipboard Behaviour Data,” Proceedings of the Conference on Human 

Factors in Ship Design and Operation, October 2‒3, 2002, The Royal Institution of Naval 

Architects, London, pp. 37‒50. 2002. United Kingdom.

Galea, E.R., et al., University of Greenwich. “Predicting the Evacuation Performance of 

Passenger Ships using Computer Simulation,” Proceedings of the 9th International Fire Science 

and Engineering Conference, Edinburgh, Scotland, September 17‒19 2001, Interflam '01, Vol. 2, 

pp. 853‒864. Interscience Communications Ltd, London. 2001. United Kingdom.

Galea, E.R., et al., University of Greenwich. “Collection of Evacuation Data for Large 

Passenger Vessels at Sea,” Proceedings of 5th International Conference on Pedestrian and 

Evacuation Dynamics, March 8-10, 2010, Gaithersburg, MD. Eds: Peacock, R.D., et al., pp.

163-172. Springer, New York. 2011.

Galea, E.R., et al., University of Greenwich. “Investigating the Impact of Aircraft Exit 

Availability on Egress Time Using Computer Simulation,” Proceedings of Pedestrian and 

Evacuation Dynamics, February 27‒29, 2008, Wuppertal University. Eds: W.W.F. Kligsch, et 

al., pp. 411‒424. Springer-Verlag Berlin Heidelberg. 2010. Germany.

Galea, E.R., et al., University of Greenwich. “Optimising Vessel Layout Using Human Factors 

Simulation,” Proceedings of Pedestrian and Evacuation Dynamics, February 27-29, 2008,

Wuppertal University, Germany. Eds: W.W.F.Kligsch, et al. pp. 597‒604. Springer-Verlag,

Berlin Heidelberg, pp. 597‒604. 2010. Germany.

Galea E.R., et al., University of Greenwich. “Fire/Evacuation Analysis of the Station Nightclub 

Fire,” 9th International Association of Fire Safety Science Symposium, Karlsruhe, Germany, 

September 21-26, 2008. Eds: D. Gottuk and B. Lattimer, pp. 465‒476. 

Gwynne S., et al., University of Greenwich. “Analysing the Evacuation Procedures Employed 

on Thames Passenger Boat Using the maritimeEXODUS Evacuation Model,” Fire Technology, 

Vol. 39, No. 3, pp. 225‒226. 2003. United Kingdom

Gwynne, S., et al., University of Greenwich. Simulating Occupant Interaction with Smoke Using 

buildingExodus, University of Greenwich, London. United Kingdom.

Gwynne, S., et al., University of Greenwich. “Adaptive Decision-Making in buildingExodus in 

Response to Exit Congestion,” Proceedings of the Sixth International Association for Fire

Science Symposium, Poitiers, France, July 5‒9, 1999. Interscience Communication, Limited, 

London, 1999. United Kingdom.

Owen, M., et al., University of Greenwich. “The Exodus Evacuation Model Applied to Building 

Evacuation Scenarios,” Journal of Fire Protection Engineering. Vol. 8, No. 2, pp. 65‒84. May 

1996. United Kingdom.
54

Owen, M., et al., University of Greenwich. “Advanced Occupant Behavioural Features of the 

buildingEXODUS Evacuation Model,” Proceedings of the 5th International Symposium on Fire 

Safety Science, Melbourne, Australia, March 3‒7, 1997. Interscience Communication, Limited, 

London. 1997.

Veeraswamy, A., et al. “Wayfinding Behaviour within Buildings – An International Survey,”

Proceedings of the Tenth International Symposium on Fire Safety Science, University of 

Maryland, June 19‒24, 2011, pp. 735‒748. 

Hui Xie, et al., University of Greenwich. “Experimental Study of the Effectiveness of 

Emergency Signage,” Proceedings of the 4th International Symposium on Human Behaviour in 

Fire, Robinson College, Cambridge, UK, 13‒15 July 2009, pp. 289‒300.

FDS_Evac

Hostikka, et al. Technical Research Centre of Finland, (Valtion Teknillinen Tutkimuskesku)

(VTT)). Development and Validation of FDS+Evac for Evacuation Simulations. Research 

Notes 2421. 2008. Finland.

Hostikka, et al.,VTT. Evacuation Experiments in Offices and Public Buildings. VTT Working 

Papers 85. 2007. Finland.

GRIDFLOW

Purser, D. “Implications of Modelling and Experimental Studies of Evacuation Behaviour on 

Stairs for Multi-storey Building Design,” Human Behaviour in Fire, Robinson College, 

Cambridge, UK, 13‒15 July, 2009, pp. 147‒160. 2009. United Kingdom.

LEGION

Legion International. http://www.legion.biz/system/research.cfm.

Legion Studio 2006 User Manual. 2006.

Berrou, J.L., et al. “Calibration and Validation of the Legion Simulation Model using Empirical 

Data,” Proceedings of the Third International Conference on Pedestrian Evacuation Dynamics 

(PED) September 28‒30, 2005, Vienna, Austria. 2007.

Kagarlis, M.A. Movement of an Autonomous Entity through an Environment. WO

2004/023347 A2. Patent. 2004. 

Still, G.K. Crowd Dynamics. PhD Thesis, University of Warwick. 2000. United Kingdom.

MAGNETIC SIMULATION

Okazaki, S., and S. Matsushita, S., Kyoto University and Fukui University. A Study of 

Simulation Model for Pedestrian Movement with Evacuation and Queuing. Engineering for 

Crowd Safety, London, March 17‒18, 1993. Ed: Smith, R.A. and J. Dickie, pp. 367‒370. 

Elsevier. 1993.
55

MYRIAD/VEGAS

Crowd Dynamics Limited: http://www.crowddynamics.com/Main%20Page.htm

Still, G.K. Crowd Dynamics. PhD Thesis, University of Warwick. 2000. United Kingdom.

Still, G.K. Introduction to Myriad. Personal Correspondence with the Author (Hughes). 

December 2002.

Still, G.K. “Review of Pedestrian and Evacuation Simulations,” International Journal of 

Critical Infrastructures, Ed: D. Teodorović. Vol. 3, No. 3/4, pp. 376‒388. Special Issue on 

Transportation Disaster and Degradation Management. 2007.

NOMAD

Daamen, W. and S. Hoogendoorn, Delft University of Technology. “Evacuation Simulation of 

Passengers in Railway Tunnels,” Transportation Research Board (TRB) Annual Meeting.

Washington, DC. 2007. 

Daamen, W. et al., Delft University of Technology. “Passengers Evacuating in Rail Tunnels: A 

Simulation Study to Predict Evacuation Times,” 11th World Conference on Transport Research 

Safety (WCTR), Berkeley, CA, June 24‒28, 2007. 2007.

PATHFINDER

Rolf Jensen & Associates: http://www.rjainc.com

Cappucio, J. Rolf Jensen & Associates. “Pathfinder: A Computer-Based, Timed Egress 

Simulation,” Fire Protection Engineering, Vol. 8, pp.11‒12. 2000.

Thornton, C, et al. “Introducing Pathfinder: An Agent-Based Egress Simulator,” Human 

Behaviour in Fire, Robinson College, Cambridge, UK, July 13‒15, 2009. pp. 567-572. 2009. 

United Kingdom.

PEDROUTE

Halcrow Group Limited: http://www.halcrow.com/pdf/urban_reg/pedrt_broch.pdf

Transport Strategies Limited: http://www.tsl.dircon.co.uk/dempedroute.htm

SIMULEX

Integrated Environment Solutions (IES): http://www.iesve.com

IES. Simulex Technical Reference and User Manual.

Olsson, P.A. and M.A. Regan. “A Comparison between Actual and Predicted Evacuation 

Times,” 1st International Symposium on Human Behaviour in Fire, University of Ulster, 

August 1998. United Kingdom.
56

Thompson, P.A. and E.W. Marchant, University of Edinburgh, UK. “Computer and Fluid 

Modelling of Evacuation, Journal of Safety Science, Volume 18, pp. 277‒289. 1995.

Thompson, P.A. and E.W. Marchant, University of Edinburgh. “A Computer Model for the 

Evacuation of Large Building Populations,” Fire Safety Journal, Vol. 24, pp. 131–148. 1995.

Thompson, P.A. and E.W. Marchant, University of Edinburgh. “Simulex: Developing New 

Computer Modeling Techniques for Evaluation,” Proceedings of the Fourth International 

Association for Fire Science Symposium, Ottawa, Canada, July 1994. Ed: T. Kashiwagi, 

pp. 613‒624. 1994.

Thompson, P.A., et al., University of Edinburgh. “Simulex 3.0: Modeling Evacuation in MultiStory Buildings,” Proceedings of the Fifth International Association for Fire Science 

Symposium, Melbourne, Australia, March 3‒5, 1997. pp. 551‒560. 1997.

Kennedy, W.D., et al. Parsons Brinckerhoff. “Simulation of Escape from Rail Tunnels Using 

Simulex,” APTA Rail Transit Conference, Boston, Massachusetts, June 2001. 2001.

STEPS

Mott MacDonald Group: 

www.mottmac.com/html/06/software.cfm?projectid=2&project=products

MacDonald, M. STEPS User Manual. Croydon, UK.

Capote, J.A., et al. “Human Behavior during Train Evacuation: Data Collection and Egress 

Modelling,” Proceedings of the Advanced Research Workshop: Evacuation and Human 

Behavior in Emergency Situations. GIDAI Fire Safety Group, University of Cantabria. 2011. 

Spain 

Hoffmann, N.A., et al. “Analysis of a Crush Loaded Train in a Tunnel.” Proceedings from the

3rd International Conference, Safety in Road and Rail Tunnels, Nice, France, March 9‒11, 2007. 

pp. 677–687. 2007.

Rhodes, N. and N.A. Hoffman. “Virtual Reality and Visualisation Tools to Assess Evacuation 

Times from Trains and Stations,” Escape from Trains, Two Day Seminar, June 9‒10, 1997, 

Heathrow, U.K. Independent Technical Conferences Limited. United Kingdom.

Scalici, S.P. and H. Pham, STV Inc. “Enhancing and Providing Safety in Transit Facility Design 

Using Pedestrian Simulation,” APTA Rail Conference, San Francisco, CA, June 1‒4, 2008. 

WAYOUT

Fire Modeling and Computing: firecomp@mpx.com.au.

Shestopal, V. and Grubits, S.J. “Evacuation Model for Merging Traffic Flow in Multi-room and 

Multi-Story Buildings,” Proceedings of the 4th International Symposium for Fire Safety Science, 

Ottawa, Canada, July 13‒17, 1994. Ed: T. Kashiwagi, pp. 625‒632. 1994.
57

Shestopal, V. FIREWIND Computer Software for the Engineering Professional, User’s Manual. 

Fire Modeling and Computing, Wahroonga, Australia. 2000. Australia. 
58

6. POTENTIAL COMPUTER MODEL INPUTS FOR PASSENGER RAIL 

CAR EGRESS TIME ESTIMATION

Classes of passenger rail car egress scenarios have been developed to identify the potential 

effects of different variable factors (data inputs) and their interaction on egress time for each 

scenario. However, actual passenger rail experiments are required to obtain the specific data of 

interest for a passenger rail car egress computer model. 

6.1 EGRESS SCENARIOS

Analysis of all passenger rail egress scenarios based on combinations of all the variable factors 

within each category listed in Chapter 2 would result in an impractical number of data inputs.

Therefore, classes of scenarios were developed using only the first three categories: rail car type, 

rail car orientation, and operating environment. The scenarios are listed in Table 5. Many are 

similar to historical accident conditions. Within each scenario class, there are several potential 

egress scenarios. 

The passenger rail car type (single-level intercity, multilevel, sleeping, and single-level 

commuter) were the initial variable factors selected because of their differences in exit size, exit 

location, and interior layouts through which passengers travel to reach the exits. 

Many single-level commuter and intercity passenger rail cars differ in the size and location of 

exits within the car. Some commuter rail car side-door exits are typically wider and are directly 

adjacent to the seating area. However, during an emergency evacuation, it is preferable or it may 

be necessary for passengers to exit the seating area along a narrow aisle, and then through the 

interior end door(s) into a separate vestibule area, where the side and end doors are located; thus 

limiting the exit flow rate. Interior doors leading to the vestibule and side-end doors in intercity 

rail cars are narrower compared to some commuter rail side doors, and a single vestibule in this 

type of rail car typically serves the two adjacent cars, potentially limiting the egress flow at this

type of exit. 

Evacuations from passenger rail cars overturned on their sides, as well as upright cars, were 

included as additional scenarios because of the dramatic differences in the exit locations, 

accessibility, and passenger movement capability. Several NTSB accident reports indicated that 

when rail cars are overturned on their sides, exits are more difficult to reach and occupants 

encountered obstacles, such as seats and luggage, as they made their way to exit (see Section 3.1

and Section 3.3).

Table 5 includes egress to five common operating environments: to the next adjacent car, 

outside to high-platform and low-platform stations, outside the car to ROW (track) level, outside 

the car while on a bridge, and outside the car while within a tunnel.

In passenger rail car-to-car and car-to-platform egress situations, upright orientations are most 

common, whereas rail cars in accidents along the ROW often roll onto their sides. This latter 

situation provides another egress variable that multiplies data inputs for both the upright and 

overturned rail car scenario conditions, as does egress into confined, dimly-lit tunnel conditions. 
59

Table 5. Passenger Rail Car Emergency Egress Scenarios

EGRESS 

PATH/OPERATING 

ENVIRONMENT

SCENARIO 

CLASS 

NUMBER

PASSENGER 

RAIL CAR 

TYPE

PASSENGER 

RAIL CAR 

ORIENTATION

1. Car to Next 

 Adjacent Car

1 a

Single Level

Upright

Commuter car

1 b Intercity coach

1 c Intercity sleeping car 

1 d Food service car

1 e, f, g, h

Multilevel

See above

2. Car to High-

 Platform 

 Station 

2 a, b, c, d

Single Level

See above

2 e, f, g, h

Multilevel 

See above

3. Car to ROW

3 a, b, c, d

Single Level

See above

3 e, f, g, h

Multilevel

See above

4. Car within 

 Tunnel

4 a, b, c, d Single Level

See above

4 e, f, g, h

Multilevel

See above

5. Car on Bridge

5 a, b, c, d

Single Level

See above

5 e, f, g, h

Multilevel

See above

6. All

 (Various

 Combinations)

1, 2, 3, 4, 5, 6

a, b, c, d

Single Level 

Overturned

Onto its

Side

See above

1, 2, 3, 4, 5, 6

e, f, g, h,

Multilevel

See above
60

The combination of rail car types, car orientations, and egress environments considered in these 

egress scenarios provides a “structural” basis for modeling passenger rail car egress. 

For all passenger rail car types, exit availability, both initially and later in the evacuation, can be 

altered (opened or closed); study of the passenger choice of exit would provide data on egress

flow rates through each individual exit type, delays associated with operating closed exits, and 

exit selection. Egress scenarios could also incorporate variable factors, such as car orientation, 

specific exit configuration, emergency exit signage, interior lighting levels, passenger density, 

occupant characteristics and decision-making, train crew and emergency responder decisionmaking and actions, and hazardous conditions including overturned cars and fires. This 

parametric series of egress scenarios could identify the effects of locating and accessing exits 

with different types of exit signage and different levels of interior car lighting, as well as their 

effect on egress time.

However, the scope of possible scenarios that can be tested in passenger rail car egress 

experiments is constrained by the potential for injury to the participants involved. Egress 

through doors to station platforms or an adjacent car at normal walking speeds poses minimal 

risk. In contrast, rapid egress to the ROW, by use of end or side doors (particularly if there are 

no side-stairway steps), or from rail cars that have overturned onto their sides, has a potentially 

higher risk of injury. 

This potential risk is very evident in precautionary emergency evacuations from aircraft that 

resulted from cases in which crew members or passengers believed the probability of fire to be 

high, although no fire actually developed. Of 109 such incidents identified by FAA in the mid1990s, 19 resulted in injuries to passengers; almost all (86 percent) of the 193 injured persons 

required medical assistance and most (67 percent) were treated at a hospital. The then-estimated 

cost to the airlines was approximately $10,000 per injured passenger for processing and 

compensation [105].

Even when extraordinary measures are taken to minimize the risk of injury in aircraft evacuation 

certification trials, significant numbers of participants have been injured. In the most recent

large-scale trials [106], which also had the most elaborate safety measures, more than 2,500 

participants stepped through “over-wing” (Type III exits) to a padded surface simulating a wing 

27-in (6.6-m) below the exit sill. Fifty-eight participants (approximately 2 percent) sustained 

some type of injury, and eleven of those were serious, requiring a visit to an emergency room or 

a personal physician. The lesser injuries (e.g., cuts, abrasions, bruises, and sprains) were treated 

by nursing staff at the experiment site.

In recognition of the potential hazards, federal regulations require that any experiment with 

human participants be examined and approved by an Institutional Review Board (IRB) [107]. 

These regulations require that subjects be fully informed of the purpose of the research, what 

procedures will be followed in the experiment, what benefits will accrue to the subjects or to 

society, what records will be kept, and any foreseeable risks or discomforts they may experience. 

Risks must be minimized and must be reasonable in relation to the benefits of the research. 

There are also various requirements related to protection of the privacy of personal data.

Because of experience with aircraft evacuations and other egress tests, an IRB may not approve 

passenger rail car egress experiments that include higher-risk scenarios (cars extremely tilted on 
61

their sides, drops from windows, etc.). Moreover, it is preferable that experience with minimalrisk scenarios be gained before planning for higher risk egress conditions.

6.2 INPUT DATA FOR ESTIMATING EGRESS TIME

Potential input data for a computer model capable of simulating occupant egress from a 

passenger rail car were identified from the review and analysis discussed in the previous chapters 

of this report and from an APTA PRESS-conducted Emergency Systems survey [108]. The 

APTA PRESS survey focused on the dimensions and locations of passenger rail doors and 

emergency window exits—and related signage, as well as the location of emergency lighting.

Table 6 provides a list of potential input data. Specific data required by any egress model 

depends on the calculation method and the details of the egress scenario of interest. The 

majority of the models use only subsets from this list, as only the most comprehensive 

individual-movement models can incorporate all variable factors of potential interest. Some 

input data will have a more significant impact on egress time than other data. The relative 

importance of the variable factors must be established through passenger rail car egress 

experiments, the results from which could potentially reduce this list. Because very few egress 

experiments have been conducted using passenger rail cars, the input data required for a 

particular egress prediction method will also depend on the assumptions inherent in the model. 

Comprehensive egress models require engineering drawings of the passenger rail cars, as well as 

measurements or photographs with scaling factors, for the specific railroad environment at which 

egress will occur.

6.2.1 Input Data for Hydraulic Models

Hydraulic models (see Subsection 4.2.2.1) require simplified input data for passenger rail car 

geometry and global occupant characteristics. Most of these models represent the occupant 

population in a generic sense. However, some of the models reviewed (e.g., EXIT89) are 

capable of defining multiple occupant subgroups, so that important characteristics of occupants 

can be considered. For example, definition of occupant subgroups, based on mobility 

characteristics or age, may produce results more representative of the occupant group as a whole. 

A list of variables for potential use in hydraulic models is included in Table 7. Some of these 

variables may appear somewhat repetitive; this is because the input data (variables) used depend 

on the specific model. For example, some models may use a fixed-flow rate through a door, 

while others calculate the flow rate from door dimension, occupant density, and physical size of 

occupants. 

As noted previously, hydraulic models do not typically include occupant decision-making or 

account for general assistance from passenger train crew or emergency responders, although 

these models may include some specific effects of crew assistance and emergency responders, 

such as assistance at, or opening of, exits. For example, a door may be inaccessible until 

emergency responders open it, thus making it usable for only part of the evacuation. Such 

assistance would be incorporated in the models as an increase in the flow rate through the exit 

only in the latter stages of an evacuation, based on changing input by the User. 
62

Table 6. Potential Input Data for Calculating Egress from Upright Passenger Rail Cars

CATEGORY INPUT DATA

Rail Car Type and 

Geometry

Single or multilevel

Car interior dimensions

Seating layout

Aisle/exit path width and height

Stair location, width, height, step rise, and run

Obstructions – size and location

Passenger Loading Number of passengers

Passenger locations within rail car just prior to egress

Operating Environment Width and height of operating environment egress path

Visibility and fire conditions external to rail car

Exit Type

Door locations and dimensions

Emergency window locations and dimensions

Other emergency exits – description, location, and dimension

Exit Accessibility

Open, closed and need to be manually opened, or blocked 

Time to manually open exit

Location of manual opening directions relative to exit

Fire Conditions

Visibility 

Gas temperature

Gas toxicity

Emergency Signage Location and size of signs 

Light emitting or light reflecting

Lighting Levels

Illumination levels

Duration of power to lights 

Occupant 

Characteristics

Gender

Age

Mobility (able-bodied, disabled, injured), ability to reach exit

Movement time through aisles, doors, windows

Hesitation time at exits

Decision-making

Pre-movement time (detection, frequency of false alarm, notification)

Willingness to assist, responsibility

Social affiliation

Commitment

Familiarity

Alertness and limitation

Patience/competitiveness

Crew Actions

Training

Verbal assistance – public address system

Physical assistance

Emergency Responder 

Actions

Number of responders

Training

Amount and type of gear on emergency responder

Physical assistance (aiding egress through exits, opening/unblocking exits, 

ladder to windows, cutting car body)
63

6.2.2 Input Data for Individual-Movement Computer Models

Individual-movement models, as discussed in Subsection 4.2.2.2, allow more flexibility in 

defining rail car geometry and occupant characteristics and require more data inputs than the 

hydraulic models. Individual-movement models could potentially make use of all the input 

variables listed in Table 7. 

These models are capable of including significant detail regarding passenger rail car geometry 

and occupant characteristics, as well as obstacles that make some routes more difficult or 

impossible to traverse. Some models will define occupant characteristics in a stochastic manner 

(i.e., based on the probability distribution) based on limited input data or allow the User to define 

the characteristics of each individual passenger.

In addition, some of these models are capable of incorporating significant data, including a 

decision -making aspect that is not present in most hydraulic or network type models. The rules 

of the decision-making are embedded within the model and are a function of the decision-making 

characteristics of the occupant. Occupant characteristics may be represented stochastically 

within a broad category, based on limited differences in input data, or discretely defined by the 

User in terms of individual occupant characteristics. The algorithmic rules of such decisionmaking are embedded within the model and are a function of decision-making behaviors 

displayed by occupants in empirical egress studies or actual emergencies. Examples include 

decisions related to how the motivation and assertiveness of a passenger may affect how long a 

passenger is willing to wait in line for a specific exit before trying to seek another exit or 

attempting to push past other passengers also waiting to exit. As with occupant characteristics, 

decision-making characteristics may be defined in a stochastic manner or by the User. 
64

Table 7. Potential Input Data for Hydraulic and Individual-Movement Models

CATEGORY INPUT DATA

Passenger Rail Car 

Type and Geometry

Single or multilevel

Car interior dimensions

Seating layout

Aisle/exit path width and height

Stair location, width, height, step rise and run

Obstructions – size and location

Rail Car Orientation Upright or on side

Operating Environment

Drop from railcar exit to operating environment egress path

Width and height of operating environment egress path

Visibility and fire conditions external of rail car

Exit Type

Door locations and dimensions

Emergency window locations and dimensions

Other emergency exits – description, location and dimension

Exit Accessibility

Open, closed and need to be manually opened, or blocked 

Time to manually open exit

Location of manual opening directions relative to exit

Fire Conditions Some hydraulic models include provision for inputs from an external fire model

Lighting Levels General and exit location illumination level

Passenger Loading

Number of passengers

Passenger locations within rail car just prior to egress

Occupant 

Characteristics

Gender

Age

Mobility (able-bodied, disabled, injured)

Movement time through aisles, doors, windows (including hesitation times)

Train Crew Actions Physical assistance

Emergency Responder 

Actions

Physical assistance (aiding egress through exits, opening/unblocking exits, 

ladder to windows, cutting car body)
65

6.3 SUMMARY

Passenger rail car egress scenarios have been developed to identify the potential effects of 

different variable factors (data inputs) and their effect on egress time for each scenario. Analysis 

of all passenger rail emergency egress scenarios based on combinations of all potential variable 

egress factors would result in an impractical number of data inputs. 

Specific data required by any egress model depends on the calculation method and the details of 

the passenger rail car egress scenario of interest. Some input data will have a more significant 

impact on egress time than other data. The relative importance of the variable factors must be 

established through passenger rail car egress experiments, the results from which could 

potentially reduce this list. However, the scope of possible scenarios that can be tested in 

passenger rail car egress experiments is constrained by the potential for injury to the participants 

involved. 

Individual-movement egress models allow more flexibility in defining passenger rail car 

geometry and occupant characteristics but require more data inputs than hydraulic egress models.
66

7. SUMMARY

7.1 OVERVIEW

The safe and timely emergency evacuation of occupants from passenger trains has been 

addressed by FRA regulations for emergency preparedness and emergency systems for passenger 

rail equipment, as well as by APTA PRESS safety standards, which were developed to respond 

to lessons learned from major accidents and emergencies. 

A systems approach is necessary to ensure the safety of train crew and passengers during 

passenger train emergency situations, and to enable the use of emergency systems on board the 

train to facilitate passenger and crew egress to a point of safety when evacuation is necessary. 

These requirements function to control the design of specific passenger rail car elements, such as 

emergency exits. This systems approach must take into account as many of the variable factors 

of passenger rail car design and operation as possible, including interactions among the factors 

that work to affect occupant egress capability. 

Several limited passenger train egress experiments have been conducted in the United States, as 

well as in Europe. However, the majority of passenger rail car egress experiment trials have not 

involved regular passengers as volunteer participants and do not consider the unique operating 

railroad operating environment. Furthermore, the majority of data from these experiments either 

have not been made publicly available, or have not been documented in a consistent manner that 

permits comparison between the different types of rail cars and the different exit routes that were

studied. 

7.2 EMERGENCY EGRESS VARIABLES

Emergency egress from a passenger train is a complex process that depends on a number of 

dynamic factors and conditions. Many variables that affect the time necessary for passengers to 

exit from a passenger train in an unusual or emergency situation must be considered. Important 

variables to consider in evaluating passenger train egress time include the following: 

• Passenger characteristics;

• Rail car geometry and configuration; 

• Operating environment; 

• Train crew (and emergency responder) training;

• Passenger awareness;

• Assistance to passengers in exiting; and 

• Assistance from emergency responders. 

7.3 EGRESS TIME PREDICTION AND USE OF EGRESS COMPUTER MODELS

An assessment of passenger rail car equipment, with a focus on emergency egress systems, as 

well as car equipment design and function, is required to understand the full context of the 
67

passenger train operational environment, in terms of egress time. This type of assessment has 

had a significant history in building design and in the aviation and maritime industries. The 

evacuation capability of aircraft and ship configurations and operational environments has been 

evaluated through numerous research studies that have provided a large body of empirical data 

for emergency egress. However, those emergency evacuation “demonstrations” and experiments 

have significant cost, as well as safety and health issues (for example, participant slipping, 

tripping, or falling that may result in injuries).

Several methods have been used to establish transportation vehicle occupant egress time: 

1) complete a “back of the envelope” hydraulic hand-calculation and analysis, based on the 

number of occupants and simple exit routes; 2) conduct simulated emergency evacuations or 

egress experiments, during which occupants exit from the actual vehicle; or 3) complete an 

analysis using an egress computer model. The hand-calculation hydraulic model method and the 

hydraulic and individual-movement computer egress model analytical methods typically use 

passenger density, effective aisle width, pitch of stairs, etc., and have been accepted for use in 

building egress time estimates. However, the application of these calculation methods directly to 

passenger rail car egress is problematic for the following reasons: 1) different methods estimate 

quite different egress flow rates and egress times for specified exit openings and 2) the widths of 

aisles and pitches of passenger rail car stairways are outside the ranges observed in buildings. 

Building occupant egress data are readily applicable for use with the analytical tools mentioned 

above (e.g., hand calculations and computer models are available for estimating emergency 

egress times). However, to Volpe Center’s knowledge, the applicability of the hand calculations 

or computer models which use these building-based data to simulate realistic occupant 

emergency evacuation within the passenger train operational environment has not yet been 

accurately demonstrated. None of the building models have been validated using actual 

passenger rail car occupant data. 

In addition, individual agility and physical obstacles have a significant impact on the amount of 

time necessary for persons to exit from a passenger rail car, depending on its location. One of 

the challenges of conducting a valid test of egress behavior using members of the public is how 

to create a realistic test without putting individuals at significant risk of injury. Accordingly, the 

use of models that simulate egress behavior could reduce the number of actual egress tests that 

need to be performed to predict egress times for various passenger rail car designs. 

However, because of the inherent risk of injury to participants, passenger rail car egress 

experiments that provide new egress-related time data involving higher-risk emergency scenarios 

(egress from cars overturned or extremely tilted on their sides, egress from exit windows, egress 

of severely mobility-impaired occupants, etc.) to validate computer models that simulate egress 

may not be feasible due to safety considerations or may be very expensive to conduct.

FRA funded the development of a new prototype passenger rail car egress computer model by 

the University of Greenwich, United Kingdom, under the direction of Volpe Center [109]. 

Calibration of this model required a great quantity of detailed data regarding the timing of all the 

movements of each individual occupant during egress from the rail car. Data from the Volpe 

Center 2005 and 2006 commuter rail car egress experiments provided a key means, when 

combined with the known physical characteristics of each type of individual, the physical 
68

characteristics of the rail car, and the operating environment at the time the data were recorded, 

to validate the passenger rail car egress time predictions generated by the new prototype model.
69

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73

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74. NTSB. Collision of Northern Indiana Commuter Transportation District Train 102 with 

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76. American Public Transportation Association (APTA). APTA SS-013-99, Rev. 1, 

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77. Kecklund, L., et al., MTO Psykolgi and Brandskyddslaget AB. Funded by Banveket 

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79. NTSB. Derailment of Amtrak Auto Train P052-18 on the CSXT Railroad near Crescent 

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report in preparation. 2013. 

85. NTSB. Derailment and Subsequent Collision of Amtrak Train 82 with Rail Cars on 

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87 NTSB. Derailment of Northern Indiana near Russell, Iowa 18, 2002. Adopted on 

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77

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98. Hathaway, W., S. Markos, and J. Baker. Review of BART “C” Car Fire Safety 

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99. McLean, G.A., et al. Aircraft Evacuation onto Escape Slides and Platforms II: Effects of 

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102. Kuligowski, E.D. and R.D. Peacock. A Review of Building Evacuation Models. National 

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103. Daamen, W. and S. Hoogendoorn, Delft University of Technology. “Evacuation 

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104. Kennedy, W.D., et al. Parsons Brinckerhoff. “Simulation of Escape from Rail Tunnels 

Using Simulex,” APTA Rail Transit Conference Proceedings, Boston, Massachusetts, 

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105. Hynes, M., Hynes and Associates. Evacuee Injuries and Demographics in Transport 

Airplane Precautionary Emergency Evacuations. Prepared for Office of Aviation 

Medicine, CAMI/FAA/U.S. DOT. Final Report. Report no. DOT/FAA/AM-00/11. 

March 2000. 

106. Corbet. C.L., et al. Access-to-Egress II: Subject Management and Injuries in a Study of 

Emergency Evacuation through the Type-III Exit. OAM/CAMI/FAA/USDOT. Final 

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108. APTA PRESS. Survey of Commuter Rail Car Emergency Evacuation-Related Features. 

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109. University of Greenwich. Development of New Prototype railEXODUS Software. 

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editorial review process.
79

APPENDIX. BIBLIOGRAPHY

This bibliography contains selected U.S. and other international agency transportation vehicle 

requirements, guidelines, and research relating to emergency preparedness, emergency systems, 

and emergency evacuation. (Note that reference information for the various egress simulation 

computer models is listed in Chapter 5.)

A1. U.S. DOT MODAL AGENCIES

A1.1 Federal Aviation Administration (FAA)

A. Regulations

Code of Federal Regulations, Title 14 (14 CFR), Aeronautics and Space, Part 25 

Airworthiness Standards: Transport Category Airplanes. U.S. DOT. National

Archives and Records Administration. Washington, DC. As of January 1, 2012.

B. Advisory Circulars (AC) 

AC 25.803.1. Emergency Evacuation Demonstrations. 11/13/89. 

AC 121-34C. Passenger Safety Information Briefing and Briefing Cards. 7/1/03.

AC 20-38A. Measurement of Cabin Interior Emergency Illumination in Transport 

Aircraft. 2/8/66. 

AC 121-34C. Passenger Safety Information Briefing and Briefing Cards. 7/1/03

AC 20/47. Exterior Color Band Around Exits on Transport Airplanes. 2/8/66

AC 25.807-1. Uniform Distribution of Exits. 8/13/90.

AC 25 812-1A. Floor Proximity Emergency Escape Path Marking. 5/22/89.

AC 25 812-2. Floor Proximity Emergency Escape Path Marking Systems 

Incorporating Photoluminescent Elements. 7/22/97. 

C. Office of Aviation Medicine/Civil Aerospace Medical Institute (CAMI) Research 

Reports

Rasmussen, P.G. and C.B. Chittum. The Influence of Adjacent Seating on Egress 

through a Type III Emergency Exit. Report no. DOT/FAA/AM-89/14. December 

1989.

McLean, G.A., et al. Effects of Seating Configuration and Number of Type III Exits 

on Emergency Aircraft Evacuation. Report no. DOT/FAA/AM-92/27. August 1992.

McLean, G.A., et al. Evacuation Through the Type-III Exits 1: Effects of Seat 

Placement at the Exit. Report no. DOT/FAA/AM-95/22. July 1995.
80

McLean, G.A., et al. Evacuation Through the Type-III Exits II: Effects of Individual 

Subject Differences. Report no. DOT/FAA/AM-95/25. August 1995.

McLean, G.A., et al. Aircraft Evacuation onto Escape Slides and Platforms I: Effects 

of Passenger Motivation. Report no. DOT/FAA/AM-96/18. June 1996.

McLean, G.A., et al. Aircraft Evacuation onto Escape Slides and Platforms II: 

Effects of Exit Size. Report no. DOT/FAA/AM-99/10. April 1999.

McLean, G.A. Access to Egress: A Meta-Analysis of the Factors that Control 

Emergency Evacuation through the Transport Airplane Type-III Over Wing Exit. 

Report no. DOT/FAA/AM-01/02. January 2001.

McLean, G.A., et al. Access to Egress I: Interactive Effects of Factors that Control 

the Emergency Evacuation of Naïve Passengers Through the Type-III Exit. Report 

no. DOT/FAA/AM-02/16. August 2002.

Corbet, C., et al. Access to Egress II: Subject Management and Injuries in a Study of 

Emergency Evacuation Through the Type-III Exit. Report no. DOT/FAA/AM-03/15. 

October 2003. 

McLean, G.A., et al. Access to Egress III: Repeated Measurement of Factors that 

Control Emergency Evacuation Through the Transport Airplane Type-III Exit. 

Report no. DOT/FAA/AM-04/2. January 2004.

Rasmussen P.G., et al. Readability of Self-Illuminating Signs in a Smoke-Obscured 

Environment. Report no. DOT/FAA/AM-79-22. November 1979.

Rasmussen, P.G., et al. Readability of Self-Illuminating Signs in Black Fuel Fire 

Smoke. Report no. DOT/FAA/AM-80-13. July 1980. 

Chesterfield, B., et al. Emergency Cabin Lighting, Installation: An Analysis of 

Ceiling- vs. Lower Cabin Mounted Lighting during Evacuation Trials. Report no. 

DOT/FAA/AM-81-7. February 1981.

McLean, G.A., et al. Performance Demonstrations of Zinc Sulfide and Strontium 

Photoluminescent Floor Proximity Escape Path Marking Systems. Report no. 

DOT/FAA/AM-98/2. February 1998.

Polk, E.D., et al. GPSS/360 Computer Models to Simulate Aircraft Passenger 

Emergency Evacuation. Report no. DOT/FAA/AM-72/30. September 1972.

Garner, J.D., et al. GPSS/360 Computer Simulations of Aircraft Passenger 

Emergency Evacuation. Report no. DOT/FAA/AM-78-23. 1978.

Marcus, J.M. A Review of Computer Evacuation Models and Their Data Needs. 

Report no. DOT/FAA/AM-94/11. May 1994. 
81

Court, M. and J. Marcus. Use of Object Oriented Programming to Simulate Human 

Behavior in Emergency Evacuation of an Aircraft’s Passenger Cabin. . Report no. 

DOT/FAA/AM-97/20. August 1997.

D. FAA/CAA - Cranfield University (UK) Research

Muir, H. Aircraft Evacuation: The Effect of Passenger Motivation and Cabin 

Configuration Adjacent to the Exit. Cranfield Institute of Technology. CAA Paper no. 

92005. November 1989. United Kingdom.

Muir H, Cranfield Institute of Technology. “The Effect of Passenger Motivation on 

Aircraft Evacuation.” Flight Safety Digest. Flight Safety Foundation. June 1991. 

Muir, H. and A. Corbett. Influence of Cabin Behavior in Emergency Evacuations at 

Floor Level Exits. Part A. And Part B. Experimental Data. Report no. FAA 

DOT/FAA/AR-95/52. July 1996. CAA paper 95006. Cranfield University. United 

Kingdom.

A.1.2. Federal Railroad Administration 

A. Regulations

49 CFR, Transportation. Parts 238, Passenger Equipment Safety Standards. U.S. 

DOT. Office of the Federal Register, National Archives and Records Administration. 

Washington, DC. As of October 1, 2012.

49 CFR, Transportation, Parts 239, Passenger Equipment Emergency Preparedness. 

U.S. DOT. Office of the Federal Register, National Archives and Records 

Administration. Washington, DC. As of October 1, 2012.

B. Research

FRA. Research Results: Passenger Rail Car Egress – TRB Workshop. RR-11-23. 

November 2011. Washington, DC. Website: 

http://www.fra.dot.gov/downloads/Research/rr1123.pdf

FRA. Research Results: Passenger Rail Car Egress Time Prediction. RR-06-04. 

May 2006. Washington, DC. Website: 

http://www.fra.dot.gov/downloads/Research/rr0604.pdf.

FRA. Research Results: Passenger Rail Car Egress – Computer Simulation 

Software Development. RR 13-XX. 2013. Washington, DC.

Markos, S.H. Recommended Emergency Preparedness Guidelines for Passenger 

Trains. Prepared by Volpe Center/USDOT for FRA/U.S. DOT. Final Report. 

Report No. DOT/FRA/ORD-93 23. December 1993.
82

Markos, S.H. and M.L. Lyons. Passenger Train Emergency Systems: Application of 

New Prototype railEXODUS Software to U.S. Passenger Rail Car Egress Scenarios. 

Prepared by Volpe Center/U.S. DOT for FRA/U.S. DOT. Draft final report in 

preparation. 2013.

Markos, S.H. and J.K. Pollard. Passenger Train Emergency Systems: Single-Level 

Commuter Rail Car Egress Experiments. Prepared by Volpe Center/U.S. DOT for 

FRA/U.S. DOT. Final Report. In FRA approval process as of May 2013.

Markos, S.H. and J.K. Pollard. Passenger Train Emergency Systems: Evaluation of 

New Technologies for Enhancing Emergency Egress. Prepared for FRA/U.S. DOT. 

Various presentations provided to FRA Railroad Safety Advisory Committee 

(RSAC), 2003-2009. Draft final report in preparation. 2013.

Markos, S.H. and J.K. Pollard. Passenger Train Emergency Systems: Passenger Rail 

Car Egress Simulator (Roll-Over Rig) Demonstrations. Prepared for FRA/U.S. DOT. 

Draft final report in preparation. 2013. 

University of Greenwich. (United Kingdom). Development of New Prototype 

railEXODUS Software. Funded by FRA /USDOT, under contract to Volpe 

Center/USDOT. Contract no. DTRT57-07-C-10063. Awarded 2007. Completed 

2011. FRA/U.S. DOT version of final report in FRA editorial review process.

A1.3. National Highway Traffic Safety Administration (NHTSA)

A. Regulations

49 CFR. Part 571, Federal Motor Vehicle Safety Standards (FMVSS), Subsection 

571.217, FMVSS No. 217, Bus Emergency Exits and Window Retention and Release. 

U.S. DOT. National Archives and Records Administration, Washington, DC. As of 

October 1, 2012.

B. Research

Markos, S.H. and Pollard, J.K. Human Factors Issues in Motorcoach Emergency 

Egress. Summary Report. Prepared for NHTSA/U.S. DOT by Volpe Center/ 

U.S.DOT. June 2010. In NHTSA review process.

Purswell, J.L.; et al. Escapeworthiness of Vehicles and Occupant Survival. Prepared 

for Federal Highway Administration (FHA)/NHTSA/U.S. DOT by School of 

Industrial Engineering, University of Oklahoma Research Institute (OKRI). Norman, 

OK. Final Report. Part 1, Report no. DOT-HS-800-428. Parts 2 and 3, Report no. 

DOT-HS-800-429. December 1970.

Purswell, J.L., et al. Evacuation of Intercity Buses. Prepared for Federal Highway 

Administration/U.S.DOT, by School of Industrial Engineering, OKRI. Norman, OK. 

Final Report. January 1978.
83

Sliepcevich, C.M.; et al. Escapeworthiness of Vehicles for Occupancy Survivals and 

Crashes. Prepared for NHTSA/U.S.DOT, by School of Industrial Engineering, 

OKRI. Norman, OK. Final Report. Part 1: Report no. DOT-HS 800 736. Part 2: 

DOT-HS 800-737. July 1972. 

A1.4 United States Coast Guard (USCG). 

46 CFR, Shipping. Various Parts. Department of Homeland Security. Office of the 

Federal Register, National Archives and Records Administration. Washington, DC. As 

of October 1, 2012.

A2. RAIL SAFETY STANDARDS BOARD (RSSB)/ASSOCIATION OF TRAIN 

OPERATING COMPANIES (ATOC) UNITED KINGDOM (UK)

A2.1 Railway Group Standards (RGS)/Codes of Practice

Incident Response Planning &Management, Issue I. GORT3118. October 2008.

Accident and Incident Investigation, Issue 1. GO/RT3119. October 2008.

Accident and Incident Investigation, Issue 2. GO/RT3119. September 10, 2010 

(Effective April 12, 2011.)

Vehicle Fire, Safety and Evacuation. Issue 2. GMRT2130. August 2009.

Vehicle Fire, Safety and Evacuation. Issue 3. GMRT2130. December 2010. (Effective 

May 3, 2011)

Traincrew Access to and Egress from Railway Vehicles, Issue 1. GMRT2162. 

November 1995. 

Traincrew Access to and Egress from Railway Vehicles, Issue 2. GMRT2162. December 

2010. (Effective May 3, 2011.)

Requirements for Rail Vehicle Structures. GMRT2100. Issue 3. October 2000.

Requirements for Rail Vehicle Structures. GMRT2100. Issue 4. December 2010. 

(Effective May 3, 2011.) (Certain sections effective March 2011.)

A2.2 Guidance Notes/Recommendations/Codes of Practice

Guidance Note - The Training of On-Train Staff in On-Train Emergency Procedures. 

ATOCGN003, Issue 4.

Recommendations for Rail Vehicle Fire Safety. GMRC2530. June 2008. (Effective 

August 2008.)

Recommendations for Rail Vehicle Emergency Lighting. GMRC253. June 2008. 

(Effective August 2008.)
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Recommendations for Communication of Rail Vehicle Emergency & Safety Information. 

GMRC253. June 2008. (Effective August 2008.)

Recommendations for Rail Vehicle Emergency Evacuation. GMRC25. June 2008. 

(Effective August 2008.) 

A2.3 Research Study Reports 

Thomas, L.J., et al. Evacuation and Communication: Strategies to Encourage 

Appropriate Passenger Behaviour in a Range of Safety Related Situations. Cranfield 

University. 2005.

Thomas, L.J., et al. Evacuation and Communication: The Human Factors of Passenger 

Behaviour and Management in a Range of Safety Related Situations. Cranfield 

University. 2004.

Thomas, L.J., et al. Evacuation and Communication in a Range of Transport and Built 

Environments: A Literature Review. Cranfield University. 2003. 

Project T052: ‘Snap Wands’ and Low Location Marking Systems for Emergency 

Lighting on Passenger Vehicles – Higgs, G. “Low Location Marking Systems and their 

Potential Use on Railway Vehicles.” Prepared by Interfleet Technology, Limited. 

Report no. LLMS/T11275/006. January 2003.

Project T052a: Improvements to Safety Signage on Passenger Trains –

Gamble. W. “Report on Passenger Safety Signage.” Prepared by Interfleet Technology 

and Davis Associates for RSSB. Report ITLR-T11274-003. December 2003.

“Graphics Guidelines for Safety Signs.” Prepared by Davis Associates for Interfleet 

Technology and RSSB. Report ITL/GN0001. April 2003.

“Guidelines for Symbol Design and Testing.” Prepared by Davis Associates for 

Interfleet Technology and RSSB. Report ITL/GN0002. April 2003.

Project T052b: Hammers for Breaking Carriage Windows Prior to Emergency Egress –

Gamble, W. “Railway Safety Research Project No. 7, Research into Emergency 

Hammers.” Prepared by Interfleet Technology. Report No ITLR-T11273-005. January 

2003. 

Project T052c: Signage and Illumination of Emergency Door Release Mechanisms in 

Passenger Vehicles – Gamble, W. “Railway Safety Research Project No. 6 – Research 

into Emergency Door Release.” Prepared by Interfleet Technology Limited. Report 

ITLR-T1127-005. January 2003.

Project T052d: Communication Technology and Functionality in Passenger Vehicles –

Wilson, C.A. “Railway Safety Accident and Survivability Project 4 Communication 

Technology.” Report no. ITLR/T11272/002. December 2002.
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Project T052e: Windows and Hatches for Emergency Egress from Railway Carriages;

Recommendations 81 and 83 – Stage 1 – Bickeley, A. and A. Seaton. “Research into 

New Escape Routes from Railway Carriages: LGRI/1 Recommendations 81 and 83 -

Stage 1.” Report no. ITR-T1270. Interfleet Technology Limited. January 2003.

Project T66a: Development of a Train Evacuation Risk Model – Dunbar, I. Train 

Evacuation Risk Model – Stay or Go. Prepared by Risk Solutions, Limited. Report no. 

D4123/01. June, 2002.

Project T121: Communication for Effective Passenger Behaviour Immediately Following 

an Incident–- In Progress

Project T122.: Human Factors and Injury Information to be Collected during Accident 

Investigations –

Cokayne, S.P. “Data to be Collected for Investigations of Railway Accidents.” 

Prepared by the Engineering Link. Report No. 09/T122/Enge/003/TRT. (Original 

Issue – January 2003) Issue 4, March 2004.

Cokayne, S.P. “Review of Information Collected Following Recent Railway Accidents 

within the UK.” Prepared by the Engineering Link. Report No. 

09/T122/Enge/001/TRT. Issue 4, March 2004. 

Cokayne, S.P. “Review of Information Collected by Other Railway Administrations.” 

Prepared by the Engineering Link. Report No. 09/T122/Enge/002/TRT. Issue 3, 

February 2004. 

Project T129: Design Study for Conversion of Emergency Exit on MKIII Vehicle 

Windows – Haworth, A. “Design Study: Conversion of Fixed Sidelight to an Emergency 

Exit on MK III Coaching Stock.” Prepared by the Engineering Link. Report no. 

TEL/14882/0028. January 2003.

Project T161: Managing Large Events and Perturbations at Stations –

Davis Associates. “Literature Review,” Revision 1.1. RS021/R.01/01-T161. June 

2003.

Davis Associates. “Initial Research Report,” Revision 1.2. RS021/R.04/01-20-T161. 

October 2003.

Davis Associates. “Stakeholder and Domain Expert Interviews,” Revision 1. 

RS021/R.02/03-T161. June 2003.

Davis Associates. “Crowd Relocation Risk Evaluation Framework,” Revision 1.1. 

RS022/R.01/24-T161. November 2003.

Davis Associates. “Passenger Flow Modelling Technical Review,” Revision 4. 

RS021/R.03/34-T161. July 2005.

Davis Associates. “Crown Management at Stations -Good Practice Guide.” October 

2004.
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Davis Associates. “Pedestrian Flow Modelling Process Definition,” Revision 2. 

RS023/R.02/30-T161. May 2004.

Project T246: Development of Common Passenger Safety Signs. .Gamble, W, “Report 

on Passenger Safety Signs – “Toolbox to Signs.” Prepared by Interfleet Technology and 

Davis Associates. Report no. ITLR-T12379-004. December 2003. 

Project T310: Review of Injury Causation and Human Factors in Recent Vehicle 

Accidents – Freeman, J. “Project 310 Review of Injury Causation and Human Factors in 

Recent Vehicle Accident – Detailed Data Analysis.” Prepared by Delta Rail. 2009.

Project T314. Requirements for Emergency Lighting on Passenger Rail Vehicles –

Freeman, J. “Project 314 Phase 2 - Validation of Emergency Lighting Specification.” 

Prepared by AEA Technology Rail. October 2007. 

Freeman, J. “Project 314 Phase 1- Requirements for Emergency Lighting.on Passenger 

Rail Vehicles.” Prepared by AEA Technology Rail. June 2005.

Project T422: Completing the Set of Passenger Train Safety Signage to Improve

Legibility and Comprehension – “Final Summary Report.” Prepared by Davis 

Associates. Report no. DA/RS051/R.06. February 2006.

A3. International Union Of Railways (UIC) / European Committees for Centralization 

(UIC)(CEN) Codes

UIC Code 564.2 OR, Regulations Relating To Fire Protection and Firefighting Measures 

in Passenger Carrying Railway Vehicles or Assimilated Vehicles Used on International 

Services. 3rd edition of January 2001 and 2 amendments. 

UIC Code 555 OR, Electric Lighting in Passenger Rolling Stock. 1st Edition, January 1978 

and 7 amendments. 

UIC Code 565.1 O, Special Design And Fittings Features ff Vehicles Accepted for Use in 

International Passenger Night Traffic. 4th Edition, March 2007.

UIC Code 560 OR, Doors, Footboards, Windows, Steps, Handles and Handrails of 

Coaches and Luggage Vans. 12th edition, March 2002. 

UIC Code 564.1 OR, Windows Made from Safety Glass. 6th edition, January 1979. 

UIC Code 440 OR, Public-Address Systems in Coaches (RIC). 4th Edition, December 

2001. 

UIC Code OR, Loudspeaker and Telephone Systems in RIC Coaches; Standard Technical 

Characteristics. 3rd edition, January 1996.

UIC Code 561 OR, Means of Intercommunication for Coaches. 8th edition January 1991 

and 1 amendment.
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A4. Safety of Life at Sea (SOLAS) / International Maritime Organization (IM0)

IMO. International Convention for the Safety of Life at Sea (SOLAS). Consolidated 

Edition. 2009.

IMO. Guidelines for Evacuation Analysis for New and Existing Passenger Ships. MCS.1/ 

Circular 1238. October 30, 2007.