GradeDec.Net 

Reference Manual 

Federal Railroad Administration 

June 2019 

GradeDec.Net Reference Manual Contents  iii

Contents 

Introduction 1

Description and Objective ...................................................................................... 1

About This Document ............................................................................................ 3

Model Overview 7

Introduction ............................................................................................................ 7

The Analysis Frame of GradeDec.Net ................................................................... 7

Benefits and Costs ...................................................................................... 7

Grade Crossing Investments ...................................................................... 8

Base Case and Alternate Case .................................................................... 8

Corridor or Region ..................................................................................... 9

The Time Horizon .................................................................................... 10

Costs and Prices ....................................................................................... 11

The GradeDec.Net Computational Model ........................................................... 11

The DOT Accident Prediction and Severity Model (APS) and the 

Resource Allocation Method ................................................................... 12

The VNTSC High Speed Rail Accident Severity Formulas .................... 13

Data and Data Organization in GradeDec.Net ..................................................... 13

The Model 17

Introduction .......................................................................................................... 17

Accident Prediction and Severity ......................................................................... 17

Forecast Highway and Rail Traffic .......................................................... 18

Exposure and Correlation of Diurnal Distributions by Highway and Rail19

Predicted Number of Accidents ............................................................... 21

Number of Accidents by Severity Category – DOT Formulas ................ 23

Number of Accidents by Severity Category – HSR formulas ................. 24

Effectiveness Multipliers ......................................................................... 26

Supplementary Safety Measures .............................................................. 27

Delay and Time-in-Queue .................................................................................... 28

Highway Traffic Re-Assignment (Corridor Model Only) .................................... 34

Grade Closures ......................................................................................... 34

Grade Separation ...................................................................................... 35

Benefits and Costs ................................................................................................ 37

Safety Benefits ......................................................................................... 37

Travel Time Savings ................................................................................ 38

Environmental Benefits ........................................................................... 39

Vehicle Operating Cost Savings .............................................................. 40

Network Benefits (Corridor Model Only) ............................................... 41
iv  Contents GradeDec.Net Reference Manual 

Local Benefits .......................................................................................... 44

Project Costs ............................................................................................ 44

Salvage Value .......................................................................................... 45

Consumer Surplus ................................................................................................ 46

Total Benefits and Benefit-Cost Indicators .......................................................... 50

Data and Data Organization 55

Introduction .......................................................................................................... 55

Corridor Data ........................................................................................................ 55

Region Data .......................................................................................................... 56

Grade Crossing Data............................................................................................. 56

Scenario Data........................................................................................................ 60

Rail Operations ........................................................................................ 60

Highway ................................................................................................... 61

Social and Other Costs ............................................................................. 61

Model Parameters and Default Values ................................................................. 62

Index 69
GradeDec.Net Reference Manual Introduction  1 

Introduction 

Description and Objective 

The Federal Railroad Administration (FRA) developed GradeDec.Net as 

an investment decision support tool for use by state and local authorities. 

The careful analysis and selection of highway-rail grade crossing 

investments serves to increase public returns for each dollar invested. 

GradeDec.Net is a web-based application that enables the analysis of 

impacts from grade crossing improvements and supports resource 

allocation and investment decisions. It allows state and local decision 

makers to prioritize highway-rail grade crossing investments based upon 

an array of benefit-cost measures. GradeDec.Net evaluates the benefitcost of grade crossing improvements while explicitly reporting the results 

for each grade crossing and each benefits category (safety, time savings, 

vehicle operating costs, reduced emissions, network and local benefits). 

Localities can use GradeDec.Net to focus on the benefit metric of greatest 

local interest. For instance, an area marked by high levels of highway 

congestion at grade crossings can identify the improvements that offer the 

prospects for congestion mitigation. For a rural area with acute safety 

issues, GradeDec.Net assists in identifying the investments that will 

promote accident reduction. 

GradeDec.Net facilitates a structured analysis. The analysis process in 

GradeDec.Net is as important as the end result. GradeDec.Net can be 

useful as a tool for managing data and partial analyses and does not 

require that users take advantage all of its features. For instance, users 

can import data and conduct safety analyses without defining alternatives 

and running a full investment analysis. 

A GradeDec.Net investment analysis finds the economic rate of return for 

a specified program of highway-rail grade crossing investments in a 

corridor or region. The economic rate of return is appropriate for 

measuring public returns because it captures a wide range of benefits that 

accrue to users of the transportation system and society as a whole, i.e., 

reductions in accidents and emissions, time and vehicle operating cost 

savings. GradeDec.Net calculates the economic rate of return by 
2  Introduction GradeDec.Net Reference Manual 

comparing the streams of expected economic benefits over time with the 

streams of investment, operating and maintenance and other life-cycle 

costs. The model discounts later year benefits and costs to reflect the 

opportunity cost of capital. This process of discounting converts all 

values to present value equivalents thus enabling the comparison of 

benefits and cost realized in different time periods. 

GradeDec.Net's analysis of grade crossing improvements is both at the 

individual grade crossing and at the corridor or regional level. Outputs 

include result metrics for the individual grade crossings and for the 

corridor or region as a whole. A series of up to 600 grade crossing 

improvements can be evaluated simultaneously. GradeDec.Net also 

reports an array of intermediate result metrics that are useful in 

interpreting the results. 

GradeDec.Net's underlying methodology is consistent with the current 

benefit-cost methodologies employed by United States Department of 

Transportation Agencies (Federal Railroad Administration, Federal 

Highway Administration, Federal Transit Administration, and Federal 

Aviation Administration) and with Executive Order 12893, which 

governs the principles of federal infrastructure investment. 

GradeDec.Net can be used to comply with the Office of Management and 

Budget's Guidelines for Benefit Cost Analysis specified in Circular No. A94. The model is transparent in all of its assumptions and model inputs 

are readily accessible to users who may wish to adjust them to more 

closely reflect local conditions. 

GradeDec.Net integrates several modeling capabilities in a single package. 

It includes separate modeling modules for corridor and regional analysis. 

The corridor analysis module evaluates crossing improvements along a 

single rail alignment. The corridor analysis accounts for impacts on the 

adjacent highway network and shifts in highway to routes with improved 

crossings. The module for regional analysis evaluates crossing 

improvements in a region (county or several counties) regardless of the 

crossings being located on a single or multiple rail alignments. 

Both the corridor and the regional analysis modules of GradeDec.Net 

include the US DOT Accident Prediction and Severity Model. The corridor 

analysis module includes as well the grade crossing risk mitigation model 

for high speed rail that was developed by the Volpe National Transportation 

Systems Center. 

GradeDec.Net includes a risk analysis modeling capability. This capability 

enables the user to accommodate the numerous uncertainties that are 

inherent in any forecast. Rather than relying on "best guess" inputs whose 

actual values may vary widely, risk analysis incorporates input ranges. For 

a designated set of operational and policy variables in GradeDec.Net, users 

can set ranges describing probability distributions. These ranges reflect best 

available data and empirical evidence combined with any expert judgments 

that the user brings to bear in the analysis. GradeDec.Net includes a 

graphical interface that facilitates data entry and the visualization of 
GradeDec.Net Reference Manual Introduction  3 

probability distributions. GradeDec.Net presents its results, the outcomes of 

risk analysis simulations, as probability distributions. These results and 

their mode of presentation support informed decision-making by providing 

the full range of possible outcomes rather than relying upon a point estimate. 

GradeDec.Net represents a major upgrade from GradeDec 2000, the 

previous release of GradeDec. It incorporates additional analytic algorithms 

and handles many more grade crossings simultaneously. GradeDec.Net 

strives to meet the needs of both experienced and novice users. Experienced 

analysts can take advantage of newer features and capabilities while less 

experienced analysts can rely upon pre-defined default values and should 

find GradeDec.Net easy to use for conducting an analysis. 

GradeDec.Net has been available to the public since January 2003. In the 

two years since its initial release, the GradeDec.Net model has undergone 

refinements that reflect experience gained from hundreds of analyses and 

feedback from the community of over 500 registered users and training 

workshop participants. 

The main refinements to the GradeDec.Net model since it was introduced 

include: 

 Ability to develop a capital program of improvements with twophased investment at each crossing (and not just assuming that all 

investment occurs prior to the period of analysis).

 Explicit segmentation of time-of-day distributions for passenger, 

freight and switch train movements (in the corridor model, and for 

through and switch train movements in the regional model).

 Increasing from one to three the number of placeholder “new 

technology” options for grade crossing devices. 

 Creating three placeholder options for “other supplementary safety 

devices” at crossings. 

In addition to these modifications, there are a number of refinements to 

the application interfaces and reporting features that should facilitate the 

development of analyses with GradeDec.Net. These refinements are 

covered in the revision the companion GradeDec.Net User’s Manual.

About This Document 

This document is the reference for the GradeDec.Net model. The 

remainder of this document presents the model components, the 

computation algorithms, and descriptions of the data inputs to the model. 

In order to best utilize the GradeDec.Net application you should refer to 

the companion volume to this document called "User's Manual for 

GradeDec.Net". 

This document is not a benefit-cost analysis manual. It assumes that 

readers are generally familiar with benefit-cost analysis, its application 
4  Introduction GradeDec.Net Reference Manual 

and some basic concepts like present value and rate of return. Useful 

references for using benefit-cost analysis can be found in NCHRP Report 

No. 342, the AASHTO Redbook and Transport Canada's Benefit-Cost 

Manual.
GradeDec.Net Reference Manual Introduction  5 

GradeDec.Net Reference Manual Model Overview  7 

Model Overview 

Introduction 

GradeDec.Net is a grade crossing investment analysis tool that includes 

both a platform for organizing the data for your analysis and a 

computational risk analysis model. This Overview presents the frame of 

analysis, the computational model and the data and their organization. 

The Analysis Frame of GradeDec.Net

The analysis frame of GradeDec.Net considers a proposed set of grade 

crossing investments on a rail corridor, or a region, over a specified time 

horizon. The analysis of benefits and costs compares the present value of 

costs and benefits in the "alternate case" (with major investment) to the 

costs and benefits in the "base case" (without major investment). 

The following are the definitions and assumptions for the GradeDec.Net

analysis frame: 

Benefits and Costs 

The benefits in a GradeDec.Net analysis are the public benefits that 

accrue from grade crossing improvements. These include: 

 Safety – the safety benefits are the reduction in predicted 

accidents and their severity. 

 Other user cost savings – other user cost savings result from 

less queuing at crossing due to grade crossing separations and 

closures. These benefits are travel time savings, reduced 

highway vehicle operating costs, reduced emissions and better 

highway network traffic flow. Closures, without other 

improvements in a corridor, will typically result in increased 

user costs and the analysis accounts for these offsetting 

impacts. 

The costs in GradeDec.Net are the costs to operate and maintain crossings 

and the capital outlays for improvements (investment). 
8  Model Overview GradeDec.Net Reference Manual 

Grade Crossing Investments 

A grade crossing investment is a one-time, capital outlay or set of 

measures that transforms grade crossings in a corridor or region in any of 

the following ways. 

 Grade crossing device type change, where "types" are 

passive, lights, gates, "new technology"1 and, as well, closure 

or grade separation. 

 Additions of supplementary measures to gated crossings. 

These supplementary measures include: four quadrant gates 

without detection, four quadrant gates with detection, four 

quadrant gates with 60 feet medians, mountable curbs, barrier 

curbs, one-way streets, and photo enforcement. 

 Changes to highway traffic flows in a corridor using traffic 

management measures like signage and signaling intended to 

re-assign traffic away from high-exposure/high-risk crossings 

during peak exposure periods of the day. 

The device type, supplementary measures and traffic management 

measures at grade crossings determine in the analysis the predicted 

number of accidents and their severity. When proposed investments 

include grade crossing closures and separations, GradeDec.Net evaluates 

any additional re-allocation of traffic that is likely to occur. 

The user has the option of a) allowing all investments at crossings to be 

implemented in the base year, or, b) developing a capital program by 

crossing in which one or two phases of improvements can be specified 

and a year of implementation for each phase (i.e., in year 3 upgrade 

crossing to gates and in year 15 grade separate the crossing). 

This capital programming feature enables the use to develop and evaluate 

multi-year grade crossing improvement strategies that accommodate the 

anticipated growth in traffic and the availability of funding. 

Base Case and Alternate Case 

The Base Case represents the "no major investment" scenario. In the 

Base Case, the analysis evaluates the operational impacts and associated 

benefits and costs over the time horizon of the analysis with the minor 

improvements. An analysis will typically include a program of modest 

investments in the Base Case where these investments are part of a 

minimal fall back position that are most likely to be undertaken in lieu of 

the more extensive investments. 

In the Alternate Case, the analysis evaluates the benefits and costs under 

the assumption that the proposed investments (in the designated years for 

cases with capital programming) have been implemented. 

 

1 New technology is a placeholder type for any prospective new device or combination of devices. The user can specify up to three 

new technologies and set a parameter that determines the effectiveness of the new technology relative to a gated crossing. 
GradeDec.Net Reference Manual Model Overview  9 

In GradeDec.Net the following parameters are set for each of the two 

cases: 

 Type of each grade crossing 

 Supplementary measures at gated crossings 

 AADT at crossings (which are the same for both cases unless 

the improvement program specifically includes traffic 

management measures for re-assigning traffic) 

 Characteristics of rail operations at crossings 

 O&M and other lifecycle costs 

 Capital investment (alternate case only). 

Corridor or Region 

 GradeDec.Net evaluates a collection of grade crossings in a single 

analysis. The user must select whether to include the crossings for 

evaluation in a corridor or in a region. GradeDec.Net has a separate 

analytic model for corridors and for regions. The corridor model provides 

greater analytic depth than the regional model. The following features are 

available in the corridor model, but not in the regional model: 

 Choice of high speed rail model or DOT model for accident 

prediction and severity, 

 Re-assignment of highway traffic at grade separated or closed 

crossings, 

 Estimation of benefits from a reduction in delay on the 

adjacent highway network. 

If the crossings for evaluation lie on a single rail alignment, then the user 

should use the corridor model. On the other hand, if the candidate 

crossings for improvement span several alignments and are grouped in a 

region, then the user should use the regional model. GradeDec.Net is 

able to extract data directly from the National Grade Crossing Inventory 

database, or other external source, and import the data directly into a 

corridor or region 

The Corridor 

The rail corridor is a single, continuous alignment of one or more railroad 

tracks. The corridor may include up to 600 grade crossings that are 

candidates for improvement. The GradeDec.Net model characterizes the 

rail corridor by several parameters: 

 The average daily number of trains by type (passenger, freight 

and switch) in the base year (see definition below). 

 The time-of-day distribution of rail traffic (there are 16 predefined, time-of-day traffic distributions) 
10  Model Overview GradeDec.Net Reference Manual 

 A Boolean (yes/no) flag that specifies whether grade crossing 

closings are synchronized with the highway traffic signaling 

system in the corridor. 

 Factors for up to three technology improvements. New 

technologies include non-conventional barriers and systems 

that provide timely notification to approaching trains of 

vehicle intrusion. Due to the absence of historical data on the 

performance of devices of these types, GradeDec.Net does 

not provide historically based estimates of new technology 

impacts. Values supplied for this factor represent the analyst's 

best judgment regarding the likely impact of new technology 

relative to conventional flashing lights and gates closure. For 

instance, a value of 0.5 for this factor will reduce by half the 

accident risk relative to flashing lights and gates. 

The corridor model analysis evaluates the impacts of closures and 

separations along the rail corridor. For closed crossings in the alternate 

case, the highway traffic from the crossing is re-allocated to adjacent 

crossings in the corridor. For grade separation improvements, the model 

estimates the attracted traffic to the grade separated crossing from 

adjacent crossings (see sections below on traffic re-assignment). 

In addition to time savings benefits for highway vehicles at the crossing, 

the corridor model calculates the impact of reduced queuing at the 

crossings on highway network delays 

The Region 

The regional analysis considers crossings in a geographic region: a 

county, several counties or any collection of crossings that may or may 

not be part of a common alignment. The regional analysis does not 

account for any re-assignment of highway traffic in the event of closure 

or separation. Because there is no accounting for re-allocated traffic if a 

crossing is closed, the analyst needs to specify a parameter in the crossing 

data entry that indicates the percent reduction in user costs for the closed 

crossing. See the discussion on this parameter ("percent benefits at 

closed crossing") in the data entry section. 

Like a corridor, a region can include for analysis up to 600 grade 

crossings.

While a regional analysis provides less depth, the analyst can import most 

of the required data directly for a designated region from the National 

Grade Crossing Inventory Database (which is accessible from within 

GradeDec.Net). 

The Time Horizon 

The time horizon of a GradeDec.Net analysis is determined by the "start 

year" and "end year" values of the input scenario. The analysis assumes 

that all investments in the corridor are executed in "year 0" (the base year) 
GradeDec.Net Reference Manual Model Overview  11

and that benefits accrue beginning in "year 1" (start year). For instance, if 

a scenario has start year 2004 and end year 2026 then the model assumes 

investments in the corridor have been completed by the end of 2003 (the 

base year) and are fully operational from the beginning of 2004. Benefits 

from the investment will accrue in the alternate case beginning in year 

2004. The analysis assumes that benefits and costs are realized at year 

end. The "present value" calculation converts dollar values over the time 

horizon of the proposed investments to their equivalent dollar value at the 

beginning of the start year (i.e., benefits in the start year are discounted). 

There are separate growth rate parameters in the model for the "near 

term" and the "far term". In many cases, planners face differing nearterm and far-term growth outlooks. For instance, a region may have 

sound forecasts for near-term rapid growth yet may view these as 

unsustainable in the far-term. By allowing the user to split the time 

horizon into a near- and far-term while determining the duration of the 

near-term, GradeDec.Net accommodates a wide range of likely growth 

paths. 

The user determines the near- and far-terms by specifying in the input 

scenario definition a year called "the last year of near term". The last year 

of near term is a year between the start year and end year. For instance, if 

the start year is 2004 and the last year is 2026, the last year of near term 

could be 2007. From the start year until and including the last year of 

near term, the model applies the near term growth rates for highway and 

rail traffic. From the year following the last year of near term and until 

the last year of the analysis, the model applies the far term growth rates. 

Costs and Prices 

The calculations of GradeDec.Net assume constant dollar values, and that 

relative prices - with the exception of fuel and oil - remain fixed over the 

time horizon of the investment. If all relative prices were fixed (i.e., if 

the ratio of the prices of any two goods or services did not change) then 

there would be no need to track prices in the model at all. Because the 

price of fuel and oil relative to other prices is allowed to vary, there is a 

need to track the general price level (inflation) and the level of the price 

of fuel and oil in order to calculate the constant dollar price of fuel and 

oil. Fuel (and oil) is singled out due to the volatility of fuel prices, and 

will likely fluctuate in comparison to other prices. In GradeDec.Net, if 

the price of fuel and oil increases faster than inflation, then the share of 

vehicle operating costs in total benefits will increase. 

The "discount rate" is a constant dollar rate, that is, it is net of general 

price inflation. 

The GradeDec.Net Computational Model 

 GradeDec.Net includes the following analytic components: 
12  Model Overview GradeDec.Net Reference Manual 

 Re-assignment of highway traffic due to closures and grade 

separation (corridor model only) 

 Calculation of safety benefits through predicted accidents and 

severity in the base and alternate cases 

 Calculation of other benefits from crossing improvements 

 Present value and benefit-cost summary including consumer 

surplus calculation for the corridor or region 

For the estimation of safety benefits GradeDec.Net employs one of two 

different computational models depending upon the user's selections. 

These are: 

 U.S. Department of Transportation (DOT) Accident 

Prediction and Severity Model (APS) and Resource 

Allocation Method 

 Volpe National Transportation System Center (VNTSC) 

High-Speed Rail (HSR) Accident Severity Model 

When using the corridor model, the user can choose which of the two 

models to use. For the regional model, only the DOT APS model is 

available. Both models estimate predicted accidents by severity category 

for the base case and alternate case. The difference between the 

quantities of incidents is then monetized (i.e., multiplied by a unit cost per 

incident) and summed by grade crossing and year to arrive at annual 

safety benefits. 

In the DOT APS the incident metrics are "fatal accidents" (accidents with 

at least one fatality), "injury accidents" (accidents with no fatalities and at 

least one injury), and "property damage only" accidents. The HSR model 

estimates fatalities and injuries for both the highway and rail modes while 

examining casualties for different types of accidents and their 

probabilities of occurrence. 

The following sections describe how the two safety models are integrated 

with the modes of usage of GradeDec.Net. 

The DOT Accident Prediction and Severity Model 

(APS) and the Resource Allocation Method 

This model is described in the document Summary of the DOT RailHighway Crossing Resource Allocation Procedure-Revisited, Office of 

Safety, Federal Railroad Administration, June 1987, Report No. 

DOT/FRA/OS-87/05. The model includes three components: a formula 

for accident prediction, a formula for severity prediction and a model for 

resource allocation. The formulas for accident prediction and severity are 

based upon regression analyses of accidents and grade crossing

characteristics. APS is applied in GradeDec.Net as described in the 

above document with one modification: GradeDec.Net corrects for the 
GradeDec.Net Reference Manual Model Overview  13

correlation between time-of-day distribution between rail and highway 

traffic. 

The DOT method for resource allocation estimates the safety at crossings 

after improvement by applying "effectiveness multipliers" to the base 

case APS model results. These multipliers were derived from separate 

analyses of grade crossings and improvements. GradeDec.Net uses the 

resource allocation method in the corridor model (when the DOT APS 

model is chosen and not the HSR model) only in cases where there is no 

re-assignment of highway traffic at a crossing due to closures or 

separation. When average annual daily traffic changes at a crossing from 

the base to alternate case due to re-assignment, then the DOT APS is 

reapplied to the improved crossing characteristics and the new level of 

highway traffic. 

The DOT APS formulas and the resource allocation method are always 

used in the regional model, using the same correction as the corridor 

model for correlation of time-of-day traffic distribution on the rail and 

highway modes. 

The VNTSC High Speed Rail Accident Severity 

Formulas 

The HSR model is an optional feature of the corridor model in 

GradeDec.Net. The model used follows procedure described in 

Assessment of Risks for High Speed Rail Grade Crossings on the Empire 

Corridor, Mark Mironer and Michael Coltman, High Speed Ground 

Transportation Division, VNTSC, April 1998. This model uses the same 

accident prediction methodology as the DOT model, but has distinct 

accident severity formulas. The model is based on an analysis of grade 

crossing accidents while focusing on the accident types (train strikes 

vehicle, vehicle strikes train), the impact of severe derailment and 

fatalities among train as well as highway vehicle occupants. 

Data and Data Organization in GradeDec.Net

This section provides a brief overview of data and their organization in 

GradeDec.Net. Data are organized into elements that correspond to their 

function in the model. 

 The four principal data elements are: 

 Corridor or region data 

 Grade crossing data 

 Scenario (risk analysis) data 

 Model parameter and default data 
14  Model Overview GradeDec.Net Reference Manual 

The corridor data include the corridor-level data covering base year rail 

operations, rail time-of-day traffic distribution, and a toggle designating 

whether there is grade crossing signal integration with the neighboring 

highway network. Corridor data also includes three technology 

parameters that represent the effectiveness of new technology at a 

crossing relative to a conventional gated crossing. The data for a region 

includes its description and technology parameter, while the rail 

characteristics are included in the crossing data. 

The grade crossing data include the physical characteristics of the grade 

crossing, crossing type for base and alternate case, accident rates and cost 

data. Accident rates are stored with the crossing data for exposition 

purposes only. Predicted accidents are recalculated for each year of the 

evaluation when a simulation is run. 

The scenario data include the policy variables and forecast values that are 

necessary for generating the forecast streams of benefits and costs. These 

data are organized into four data sets: rail operations, highway, social 

costs and price indexes. 

The model parameter and default include technical coefficients for fuel 

burn and emission rates. They also contain the default data for capital 

costs, time-of-day traffic distributions and the model parameters for the 

high speed rail accident severity model. The user can edit and modify all 

of the data and parameters described in this section. 
GradeDec.Net Reference Manual Model Overview  15

GradeDec.Net Reference Manual The Model  17

The Model 

Introduction 

This section presents the computational model that was discussed in the 

"Model Overview". For each model component, explanations and 

formulas are provided. The following section covers the data and data 

organization of GradeDec.Net. 

Accident Prediction and Severity 

The accident prediction and severity formulas in GradeDec.Net are based 

upon the two sources cited in the introduction. These equations are 

applied in accordance with the mode of usage (corridor or regional 

model). In the corridor model, the user can specify whether to use the 

HSR formulas or the DOT formulas. Moreover, in the corridor model the 

alternate case calculation of accident prediction and severity will depend 

upon whether grade crossing improvements in the corridor, through 

closures and/or separation, result in re-allocation of highway traffic 

among crossings. The procedure by which GradeDec.Net applies the 

different formulas is shown in the following figure. 
18  The Model GradeDec.Net Reference Manual 

Figure 1 Application of Accident Prediction and Severity Formulas 

The following sections describe the accident prediction and severity 

equations in GradeDec.Net. 

Forecast Highway and Rail Traffic 

 GradeDec.Net forecasts average daily highway traffic, by vehicle type, 

and number of trains, by train type, at each crossing based on base year 

traffic and traffic rates of growth for the near and the far term. 

The formula for the highway traffic forecast at a crossing is: 

Equation 1 Average Annual Daily Traffic (Highway) at Crossing 

year vtype vtype year

year year

AADT AADT

AADTftgr if year lynt

AADTntgr if year lynt

AADTgr

AADTgr

AADT AADT



























  

 ,

1

,

,

100

1

where: 

year the current year of the analysis 

AADTyear average annual daily traffic in current year (all vehicle 

types) 

AADTyear-1 average annual daily traffic in previous year (all vehicle 

types) 

Apply DOT

formulas to predct

number of

accidents in base

case

Apply DOT

formulas to predct

number of

accidents in base

case

Using HSR

formulas?

Apply DOT

formulas to

calculate accident

severity in the

base case

Apply HSR

formulas to

calculate severity

in the base case

Apply DOT

formulas to predct

number of

accidents in

alternate case

Apply HSR

formulas to

calculate severity

in the alternate

case

AADT = in

base and alt

cases?

Apply DOT

formulas to

calculate

predicted acc's in

the alt case

Apply DOT

formulas to

calculate accident

severity in the alt

case

Apply DOT

formulas

to calculate

accident severity

in the base case

no yes

Apply

effectiveness

mulipliers to calc

acc's by severity

in alt case

Apply

effectiveness

mulipliers to calc

acc's by severity

in alt case

Apply "percent

benefits" factor if

crossing closed

no

yes

Regional Model Corridor Model
GradeDec.Net Reference Manual The Model  19

AADTgr annual growth rate of AADT, percent 

AADTntgr annual growth rate of AADT in near term, percent 

AADTftgr annual growth rate of AADT in far term, percent 

lynt last year of near term 

vtype vehicle type (i.e., auto, truck or bus) 

vtype share vehicle type of total highway traffic 

AADTyear,vtype average annual daily traffic in current year by vehicle type 

Equation 2 Average Daily Trains at Crossing 



 

























 



ttype

ttype

ttype

ttypeyear year

year year

tvb

tvb

TV TV

TVftgr if year lynt

TVntgr if year lynt

TVgr

TVgr

TV TV

,

1

,

,

100

1

where: 

year the current year of the analysis 

TVyear average daily trains in current year (all train types) 

TVyear-1 average daily trains in previous year (all highway vehicle types) 

TVgr annual growth rate of average daily trains 

TVntgr annual growth rate of average annual daily trains in near term 

TVftgr annual growth rate of average annual daily trains in far term 

lynt last year of near term 

ttype train type (i.e., passenger, freight, switch) 

tvbttype trains in base year by type 

TVyear, ttype average daily trains in current year by type 

Exposure and Correlation of Diurnal Distributions 

by Highway and Rail 

The principal explanatory factor for predicting accidents at grade 

crossings is exposure. Exposure is the probability that a train and a 

highway vehicle will both arrive at a grade crossing at the same time, thus 

allowing for the possibility of an accident. Exposure, and the effects of 

grade crossings improvements, will vary significantly depending upon 

whether the time-of-day distributions of rail and highway traffic are 

highly correlated (temporal match), or, are highly uncorrelated (temporal 

mismatch). As an extreme example, if all rail traffic was at night while 
20  The Model GradeDec.Net Reference Manual 

all highway traffic was by day there would be no risk of accidents and no 

vehicles would ever stand waiting at a closed crossing. 

The two safety models used in GradeDec.Net do not account for the 

correlation between the diurnal distributions of rail and highway traffic. 

GradeDec.Net incorporates a modification to correct for this and requires 

that the user specify the time-of-day traffic distribution for the rail 

corridor, or in the case of the regional model, the user specifies the rail 

traffic time-of-day distribution for each crossing. The user also specifies 

the time-of-day distribution of highway traffic at each crossing for each 

of three traffic segments: car, truck and bus. 

The diurnal distributions in GradeDec.Net divide the daily traffic into 

twenty-four hourly periods. The user interface of GradeDec.Net lets the 

user select from among the twenty-one pre-set traffic distributions. Five 

of these are labeled: Uniform, Peak AM, Peak PM, Day Flat and Night 

Flat. These five distributions are stylized diurnal distributions that are not 

representative of a particular facility type or traffic pattern. The remaining 

sixteen are representative traffic distributions for a range of facility types 

in both urban and rural locales. 

Figure 2 Traffic Distribution Profiles 

The diurnal distributions provided in GradeDec.Net are for convenience, 

and the user can modify these values or create new distributions so as to 

more accurately correspond to time-of-day travel patterns in the corridor 

or region under consideration. 

The degree of exposure is captured in the benefits evaluation by the 

exposure correlation factor that is given by the following equation: 

Equation 3 Time-of-Day Exposure Correlation Factor 

    

































   

 

i j

j ij

i k

k ik

i j

j ij

k

k ik

Max a b

ba

EF

2 2

 , 

 

where: 
GradeDec.Net Reference Manual The Model  21

i an index designating the hour of the day 

j an index of highway vehicle type (auto, truck, bus) 

k an index of train types (passenger, freight, switch in the corridor 

model or through and switch in the regional model) 

aik the share of daily trains of train type k at the crossing in the ith 

time-of-day period 

bij the share of daily traffic of vehicle type j in the ith hour of the day 

αk the share of train type k of total trains 

j the share of vehicle type j in daily highway traffic 

Note: 

     

i j

j

k

k

i

ik ij a ,1 b ,1  ,1  1

GradeDec.Net calculates the exposure correlation factor for each crossing 

and year of the evaluation. 

GradeDec.Net integrates with the DOT Accident Prediction formula by 

calculating the daily exposure equivalent that would be realized if the 

time-of-day correlation of traffic at the grade crossing equaled the 

national average. That "national average" is the average correlation that 

is reflected in the sample that served as the basis for the estimation of 

parameters in the DOT model. GradeDec.Net calculates the exposure 

correlation factor for each crossing and year of the evaluation. 

Equation 4 Daily Exposure with Time-of-Day Correlation 

year year Expose .1 35 EF  AADT  TV

where: 

Expose base year daily exposure with time-of-day correlation, effective 

daily exposures 

EF time-of-day exposure correlation factor (see Equation 3 above)

AADT average annual daily traffic on the highway at the crossing 

TV average daily trains at the crossing 

The value 1.35 in the above equation means that if there was full time-ofday correlation between the rail and highway modes at the crossing, then 

there would 35 percent more exposure than if the correlation was equal to 

the national average2. GradeDec.Net calculates the daily exposure with 

time-of-day correlation for each crossing and year of the evaluation. 

Predicted Number of Accidents 

The predicted number of accidents at a crossing is based upon the DOT 

Accident Prediction and Severity formulas. The predicted number of 

accidents is calculated for each crossing in each year (for the base case 

 

2 35% is the opinion of a surveyed expert regarding this factor's likely value. 
22  The Model GradeDec.Net Reference Manual 

and sometimes for both base and alternate cases – see Figure 1 above). 

Note that when using the DOT Accident Prediction and Severity model, 

the predicted number of accidents is normalized to account for the 

accident history at the crossing (N is the number of accidents at the 

crossing in the previous five years). However, when using the HSR 

model, the accident history is not included as part of the formula. 

Equation 5 Predicted Number of Accidents at the Crossing 































Adja HSRfor formulas

Adj DOTfor formulas

T

NTa

NA

a

T

ka EI DT MTMS HPHL

,

,

5

0

)

0

(

.0 05

1

0

where: 

Type of Grade Crossing

Passive Flashing Lights Lights and Gates New Technology

K .0006938 .0003351 .0005745 .0001915

EI

.0 37

2.0

2.0











 Expose 

4106.0

2.0

2.0











 Expose 

2942.0

2.0

2.0











 Expose 

2942.0

2.0

2.0











 Expose 

DT

.0 1781

2.0

2.0











 dthru 

.0 1131

2.0

2.0











 dthru 

.0 1781

2.0

2.0











 dthru 

.0 1781

2.0

2.0











 dthru 

MS

ms

e

.0 0077  1 1 1

MT 1

tracks

e

.0 1917  tracks

e

.0 1512  tracks

e

.0 1512 

HL 1

lanes  )1(1826.0

e

.0 142 lanes  )1(

e

.0 142 lanes  )1(

e

HP  (5966.0 paved  )1

e

1 1 1

Adj 0.5086 0.3106 0.4846 0.4846  Tech Factor

and, 

N number of accidents in previous five years at grade crossing 

Expose daily exposure with time of day correlation, see Equation 4 above 

dthru number of day through trains per day 

ms maximum timetable speed at crossing, miles per hour 

tracks number of main tracks 

lanes number of highway lanes 
GradeDec.Net Reference Manual The Model  23

paved If highway is paved, Paved =1, if unpaved then Paved=2 

k regression coefficient

Adj Coefficient to normalize predicted accidents in year with actual 

counts (current values are normalize for year 2013) 

NA predicted number of accidents per year at the grade crossing 

Number of Accidents by Severity Category – DOT 

Formulas 

The DOT Accident Severity formulas predict the number of fatal 

accidents (accidents with at least one fatality) and the number of casualty 

accidents (accidents with at least one fatality or injury). GradeDec.Net 

calculates the number of injury accidents (accidents with at least one 

injury, but no fatality) as the number of casualty accidents less the 

number of fatal accidents. Property damage only accidents are calculated 

as predicted accidents less casualty accidents. 

The numbers of accidents by severity category are calculated from the 

following equation: 

Equation 6 Predicted Number of Accidents at Crossing by Severity 

Category (DOT Formulas) 

PA NA FA IA

IA CA FA

KC MS TK UR

NA

CA

KF MS TSTT UR

NA

FA

urban UR e

tracks TK e

MS ms

KC

urban UR e

TS switch

TT thru

MS ms

KF

CA CA

CA

CA





























 













1

1

2960.0

1153.0

.4 481

3571.0

( )1

)1(

440 9.

.0 343

0872.0

0872.0

9981.0

where: 

ms maximum timetable train speed, miles per hour 

thru through trains per day 
24  The Model GradeDec.Net Reference Manual 

switch switch trains per day 

urban if crossing is urban, Urban=1, else Urban=0 

tracks number of railroad tracks 

NA predicted number of accidents per year at the grade crossing 

FA predicted number of fatal accidents per year at the grade crossing 

CA predicted number of casualty accidents per year at the grade 

crossing 

IA predicted number of injury accidents per year at the grade 

crossing 

PA predicted number of PDO accidents per year at the grade crossing 

Number of Accidents by Severity Category – HSR 

formulas 

While the DOT formulas calculate the predicted accidents by severity, the 

high speed rail model calculates the predicted number of fatalities among 

highway vehicle and train occupants. GradeDec.Net calculates the 

number of injuries as a fixed ratio to the number of fatalities. 

The following figure shows the calculation flow for the high-speed rail 

accident severity formulas. The following equations show the calculation 

of fatalities at grade crossing accidents based upon: accident type (train 

strikes vehicle or vehicle strikes train), vehicle type (auto, truck or truck 

trailer), and occupants by mode (rail or highway). 
GradeDec.Net Reference Manual The Model  25

Figure 3 Accident Severity with High Speed Rail Formulas 

Equation 7 Predicted fatalities by mode of occupancy for accident 

given train strikes highway vehicle (HSR) 

   

















    

ttype vtype

occ ttype ttype vtype atype occvtype vtype occvtype

Ftsv sp P sd s

,, ,

2

  )(

and, 

sp sp occfor Train occupants

occfor Highway vehicle occupants

spsp sp

spsp sp

sp

ttype ttype

ttype

ttype ttype

ttype

 



















,

,

,

,

max max

max

Equation 8 Predicted fatalities for accident given highway vehicle 

strikes train (HSR) 

    

ttype vtype

occ ttype vtype atype occvtype

Fvst

,,

 

where: 

Ftsvocc predicted fatalities when train strikes vehicle, by occupancy mode 

Train into highway vehicle

Auto

Train severity /highway vehicle

severity

Derailment

Additiional train severity

No derailment

Truck

Train severity /highway vehicle

severity

Derailment

Additiional train severity

No derailment

Truck-trailer

Train severity /highway vehicle

severity

Derailment

Additiional train severity

No derailment

Highway vehicle into train

Auto

Train severity /Highway vehicle

severity

Derailment

Addition train severity

No derailment

Truck

Train severity /Highway vehicle

severity

Derailment

Addition train severity

No derailment

Truck-trailer

Train severity /Highway vehicle

severity

Derailment

Addition train severity

No derailment

GRADE CROSSING ACCIDENT
26  The Model GradeDec.Net Reference Manual 

Fvstocc predicted fatalities when vehicle strikes train, by occupancy mode 

occ occupancy mode of fatality (e.g., train occupants, highway vehicle 

occupants) 

atype accident type (e.g., train strikes vehicle, vehicle strikes train) 

vtype vehicle type (e.g., auto, truck, truck trailer) 

ttype train type (passenger, freight, switch) 

atype,vtype,occ model coefficient by accident type, highway vehicle type 

and occupancy mode of casualties 

vtype share of vehicle type in highway traffic 

ttype share of train type in total rail traffic 

spttype average train speed, for train type 

spmax train speed of maximum impact on highway fatalities 

P(sd)vtype probability of severe derailment 

sd added severity with severe derailment (model coefficient) 

Equation 9 Total Predicted Fatalities (HSR) 

   

occ

occ

occ

occ PtsvF Ftsv Ptsv )1( Fvst

where: 

F total predicted fatalities 

Ftsvocc predicted fatalities when train strikes vehicle, by occupancy mode 

Fvstocc predicted fatalities when vehicle strikes train, by occupancy mode 

Ptsv probability that accident is of type train strikes highway vehicle 

Equation 10 Total Predicted Injuries (HSR) 

 FuI

where: 

I total predicted injuries 

F total predicted fatalities 

u ratio of predicted injuries to fatalities 

Effectiveness Multipliers 

The DOT resource allocation method recommends that the following 

effectiveness multipliers be applied to predicted accidents in the base case 

in order to arrive at the estimate for safety risk at the grade crossing with 

the proposed improvements. 

Note that in using the effectiveness multipliers, predicted accidents in the 

alternate case equal the base case predicted accidents times one minus the 

effectiveness multiplier. 
GradeDec.Net Reference Manual The Model  27

If a device is upgraded to one of the new technology types, then the 

upgrade effectiveness factor is equal to 1 minus the “upgrade to gates” 

effectiveness factor, times 1 minus the corresponding technology 

effectiveness factor. 

Table 2 Effectiveness Values for Crossing Warning Devices 

Total trains per day

10 or less More than 10

Improvement 

Action

Single 

Track

Multiple 

Track

Single 

Track

Multiple 

Track

Passive to Flashing 

Lights 0.75 0.65 0.61 0.57

Passive to Lights 

and Gates 0.9 0.86 0.8 0.78

Flashing Lights to 

Gates 0.89 0.65 0.69 0.63

Supplementary Safety Measures 

The “Rule for the Use of Locomotive Horns at Highway-Rail Crossings” 

seeks to require the sounding of a horn at every crossing and provides 

detailed provisions for the establishment of "quiet zones" that are exempt 

from the requirement. As part of its provisions, the proposed rule allows 

for jurisdictions to add supplementary measures to crossings that have the 

equivalent effect on predicted accidents as the use of a locomotive horn. 

The rule incorporates a number of research findings that allow for the 

evaluation of estimated impacts from a range of improvements at grade 

crossings.

The table below shows the estimated effectiveness of supplementary 

measures at gated crossings (where the effectiveness rate is the rate of 

reduction in the number of predicted accidents with the supplementary 

device as opposed to a gated crossing). 

Supplementary measures are applied to gated crossings only. In the 

alternate case, if a crossing is upgraded from a non-gated crossing to a 

gated crossing with supplementary measures, then the two effectiveness 

multipliers are applied serially. 

Table 3 Effectiveness Multipliers for Supplementary Safety Measures 

Supplemental Safety 

Measures Effectiveness Rate

4 quadrant - no detection 0.82

4 quadrant – with detection 0.77

4 quadrant – with 60' medians 0.92
28  The Model GradeDec.Net Reference Manual 

Supplemental Safety 

Measures Effectiveness Rate

Mountable curbs-with channelized 

devices 0.75

Barrier curbs-with or without 

channelized devices 0.8

One-way street with gate 0.82

Photo enforcement 0.78

Source: Federal Register, January 13 , 2000, 49 CFR Parts 222 and 229, 

Use of Locomotive Horns at Highway-Rail Grade Crossings; Proposed 

Rule. Appendix A, pp. 2251-2255. 

GradeDec.Net allows for the re-routing of highway traffic in the corridor 

via changes in signage and signals, which can be effective in directing 

traffic away from high-risk/high-exposure crossings in the corridor. If the 

user has entered data indicating changes in AADT by traffic segment or 

changes in the time-of-day distribution of traffic segments, these changes 

will be reflected in the calculations of exposure. 

Delay and Time-in-Queue 

Accurate estimates of the non-safety benefits due to grade crossing 

investments depend upon properly quantifying the time that highway 

vehicles spend queued behind closed gates (or, waiting for a train to pass 

at ungated crossings). While the time-in-queue measure is the basis for 

the non-safety benefits (incremental emissions and vehicle operating costs 

while idling), the measure of time savings benefit is best measured as a 

function of highway vehicle delay. Delay differs from time-in-queue 

because it captures the total time impact of a closure, including the time it 

takes for vehicles to return to regular traffic flow. 

GradeDec.Net employs techniques from recent research3 that have 

remapped the conventional time-space queuing model into a graphical 

construct plotting the cumulative vehicles in queue against time. With 

some relatively unrestrictive simplifying assumptions, time-in-queue is 

derived as a multiple of delay. Both highway delay and time in queue are 

readily calculated using easy-to-obtain data. The analysis framework is 

shown in the figure below. 

The figure shows the blockage of highway traffic flow that occurs at a 

blocked grade crossing. Referring to the figure, at point L the blockage 

begins, it ends at point J and the queue begins to disperse, at point K the 

last vehicle joins the queue and at point M all the queued vehicles have 

resumed free flow speed. 

 

3 Using Input-Output Diagram to Determine Spatial and Temporal Extents of Queue Upstream of a Bottleneck, Tim Lawson, David J. 

Lovell, and Carlos F. Daganza, Transportation Research Record 1572. pp. 140-147. 
GradeDec.Net Reference Manual The Model  29

Time is plotted on the x-axis and the y-axis shows the cumulative number 

of affected vehicles. Curve V(t) is the "virtual" graph of traffic in free 

flow. The curves B1(t) and B2(t) show the number of queued vehicles. 

D2(t) shows the number of dispersed vehicles that have returned to free 

flow speed. 

The following set of equations describes the calculation of delay and 

time-in-queue in GradeDec.Net. 

The crossing blockage time is calculated from the train speed and the 

train length. The model calculates the average crossing block time as 

follows: 

Figure 4 Analysis of Delay and Time-in-Queue 

Equation 11 Average Crossing Closure Time (minutes) 



 











i

i

i

ii

i

ii

i

CBT

ACBT

spd cf

cl nc el

CBT





60

36

where: 

i index indicating the type of train: passenger, freight or switch 

CBTi crossing block time for train of type i , minutes 

cli average car length for train of type i, feet 

K M

V(t)

B1(t)

D2(t) 0

NK

N

L t tJ tK

B2(t) 

D1 J (t) 


32  The Model GradeDec.Net Reference Manual 

 arrival rate of vehicles, vehicles per second

 dispersal rate of vehicles, vehicles per second 

(constant value of 0.5) 

ACBT average crossing block time in minutes

The total vehicle delay in the time-of-day period is given by: 

Equation 17 Total Vehicle Delay per Period by Traffic Direction 

(vehicle-hours) 

per

k

K

blocks

N lanes

Nw ACBT 























 



















 

2 3600

11 1

60



where: 

 arrival rate of vehicles, vehicles per second

 dispersal rate of vehicles, vehicles per second 

(constant value of 0.5)

ABCT average crossing block time in minutes

NK the number of affected vehicles at closure

lanes number of highway lanes by direction

blocksper number of crossing blocks per period

The line B1(t) in the above figure represents the back of the queue. Its 

slope is given by: 

Equation 18 Slope of the Back-of-Queue Function 











jf

jf

kv

kv

z

where: 

 arrival rate of vehicles, vehicles per second 

vf freeflow speed of highway vehicles (constant value of 45 mph 

converted to feet per second) 

kj traffic density in vehicles per feet at speed 0 (set to constant 0.05) 

The above equation was derived from the flow-density relationship. 

The time-in-queue per time-of-day period is given by: 

Equation 19 Time-in-queue per Time-of-Day Period by Direction 

(vehicle-hours) 

per

k

Kq

blocks

N lanes

z

Nt ACBT 























 



















 

2 3600

11 1

60


GradeDec.Net Reference Manual The Model  33

where: 

z slope of the back-of-queue function 

 dispersal rate of vehicles, vehicles per second (constant value of 

0.5) 

ACBT average crossing closure time in minutes 

NK the number of affected vehicles at closure 

lanes number of highway lanes 

blocksper number of crossing blocks per period 

GradeDec.Net allocates delay and time-in-queue to each of the three 

traffic segments (auto, truck, bus) according to the shares of each traffic 

segment in total traffic for the time-of-day period. Delay and time-inqueue are summed for each traffic segment over the four daily periods to 

arrive at average daily delay and time-in-queue (for each segment). 

These metrics are used in the calculation of non-safety benefits. 

Delay and time-in-queue per traffic segment per time-of-day period is 

given by: 

Equation 20 Delay for Traffic Segment in Time-of-Day Period 

(vehicle-hours) 













per

per

veh

veh

ww

,

,

where: 

w total vehicle-hours delay in time-of-day period 

veh,per number of vehicles of type  (auto, truck, bus) in period 

Equation 21 Time-in-Queue for Traffic Segment in Time-of-Day 

Period (vehicle-hours) 













per

per

qq

veh

veh

tt

,

,

where: 

tq total time-in-queue in time-of-day period (vehicle-seconds) 

veh,per number of vehicles of type  (auto, bus, truck) in period 

The average daily delay for each traffic segment is the sum of the delay 

for the traffic segment in the four time-of day periods. The average daily 

time-in-queue for each traffic segment is the sum in the four time-of day 

periods. 
34  The Model GradeDec.Net Reference Manual 

Highway Traffic Re-Assignment (Corridor Model Only) 

With the corridor model, GradeDec.Net re-assigns highway traffic at the 

grade crossing in two instances: 1) a grade crossing closure and, 2) a 

grade separation. The rationale for the re-assignment is that with closure 

forecast traffic will take alternate routes and will cross the rail lines at 

other points of crossing in the corridor in order to reach their destination. 

With grade separation, the grade-separated route will have less traffic 

impedance than it would have had without the improvement. Travelers 

will have a greater propensity to choose the route with less impedance 

and, therefore, some diversion of traffic to the grade-separated route is 

anticipated. Re-assignment of traffic at grade separated crossings is a 

feature that the user can turn on or off when running a simulation. 

Highway traffic is re-assigned in GradeDec.Net model prior to the 

calculation of all benefit categories. 

Grade Closures 

The re-assigned AADT for the crossing adjacent below (i.e., lower 

milepost number) to the closed crossing is given by: 

Equation 22 Diversion from Closure to Lower Adjacent Crossing 

















 

 



 

1 1

1

1 1

1

i i

ii

i i i

mp mp

mpmp

aadt aadtb aadt

where: 

aadti-1 average annual daily traffic at the crossing adjacent and below the 

closure, after re-assignment 

aadti average annual daily traffic at the closed crossing before reassignment 

aadtbi-1 average annual daily traffic at the crossing adjacent and below the 

closure, before re-assignment 

mpi the milepost value of the ith crossing, the closed crossing from 

which traffic is diverted 

The re-assigned AADT for the crossing adjacent above (i.e., higher 

milepost number) to the closed crossing is given by: 

Equation 23 Diversion from Closure to Upper Adjacent crossing 

















 

 



 

1 1

1

1 1

1

i i

i i

i i i

mp mp

mp mp

aadt aadtb aadt

where: 

aadti+1 AADT at the crossing adjacent and above the closure, after reassignment 

aadti AADT at the closed crossing before re-assignment 
GradeDec.Net Reference Manual The Model  35

aadtbi+1AADT at the crossing adjacent and above the closure, before reassignment 

mpi the milepost value of the ith grade crossing 

Grade Separation 

After re-assigning traffic due to closures GradeDec.Net looks for grade 

separations and re-assigns traffic to account for the reduced traffic 

impedance at separated crossings. The model can be run without reassigning traffic due to grade separations. On the simulation screen of the 

model, uncheck the box that says "Re-assign traffic if grade separated". 

The potential AADT diverting from an adjacent crossing to a grade 

separated crossing is given by: 

Equation 24 Potential AADT Diverted from Adjacent Crossing to 

Grade Separated Crossing 

( )

1

1

min (max )min

D

e

pAADTd PD PD PD





   



where: 

pAADTd percent of potential AADT diverting from the crossing 

due to a grade separation at an adjacent crossing (a function of the 

distance to the nearest major highway intersection) 

min PD minimum percent of potential AADT diverting from the crossing 

due to a grade separation at an adjacent crossing (independent of the 

distance to the nearest highway intersection). This value is set to 5. 

max PD maximum percent of potential AADT diverting from the 

crossing due to a grade separation at an adjacent crossing (independent of 

the distance to the nearest highway intersection). This value is set to 15. 

 equation parameter set to 4.783. This parameter and the 

following one are set to meet two conditions: 1) if distance of crossing is 

.1 miles from closest major highway intersection then the value of F in 

the above equation is 0.99, and 2) if distance of crossing is 5 miles from 

closest major highway intersection then the value of F in the above 

equation is 0.01. 

 equation parameter set to -1.876 and meeting the conditions 

described above. 

D percent of potential AADT diverting from the crossing due to a 

grade separation at an adjacent crossing 
36  The Model GradeDec.Net Reference Manual 

Figure 5 Potential Diversion due to Grade Separation 

Equation 25 Percent AADT Diverted from Crossing to adjacent 

Grade Separated Crossing 













 

 

max MP

MP

pcAADTdive rt pAADTd 1

where: 

pcAADTdivert percent of diversion of AADT from the traffic at the 

crossing to the adjacent, grade separated crossing 

pAADTd percent of potential AADT diverting from the crossing 

due to a grade separation at an adjacent crossing (see above equation) 

MP distance between the adjacent crossing and the grade separated 

crossing 

max MP the maximum distance between adjacent crossings, 

beyond which there is no diversion due to grade separation. This value is 

set to 10 miles in the model. 

 an equation parameter reflecting the diminishing impact of grade 

separation on the route choice as the position of the adjacent crossing is 

further from the grade separated crossing. The parameter determines the 

concavity and the pace at which the impact diminishes with distance from 

grade separation. In the model and in below the parameter is set at 1.5. 

0 1 2 3 4 5 6

AVERAGE SHORTEST DISTANCE TO HIGHWA Y (MI.)

0

5

1 0

1 5

% M AX I M U M A A D T D IV E R T E D

POTENTIAL AADT DIVERTING
GradeDec.Net Reference Manual The Model  37

Figure 6 Diversion due to Grade Separation 

Benefits and Costs 

The following sections describe the calculation of benefits and costs in 

GradeDec.Net.

Safety Benefits 

The accident prediction and severity sections above describe the 

procedures for calculating predictions by severity type, with the DOT 

formulas, and fatalities and injuries, with the HSR formulas. 

GradeDec.Net calculates the safety benefits as: 

Equation 26 Safety Benefits (for each year and crossing – with DOT 

formulas) 

   

i

i i i

SB ( AccB AccA ) CPAcc

where: 

SB safety benefit, constant dollars 

i accident severity type (fatal, injury, PDO) 

AccBi number of accidents in base case, type i 

AccAi number of accidents in alternate case, type i 

CPAcci cost per accident, type I 

Equation 27 Safety Benefits (for each year and crossing – with HSR 

formulas) 

SB CasB CasA CPCas NAB NAA OPCAcc

i

i i i

  [(  )  (] ) 

where: 

SB safety benefit, constant dollars 

0 2 4 6 8 1 0 1 2

MILEPOST DISTANCE FROM GRADE SEPARATION

0

5

1 0

1 5

2 0

P E R C E N T A A D T D IV E R T ED

DIVERSION TO GRADE SEPARATION FROM ADJACENT GCXs

DIV ERSION WITH HIGHWAY AT M INIM UM 

DIS TA NCE FROM G CX

DIV ERSION WITH HIGHWAY AT M AX IMUM 

DIS TA NCE FROM G CX
38  The Model GradeDec.Net Reference Manual 

i casualty severity type (fatal, injury) 

CasBi number of accidents in base case, type i 

CasAi number of accidents in alternate case, type i 

CPCasi cost per casualty, type I 

NAB predicted number of accident, base case 

NAA predicted number accidents, alternate case 

OPCAcc average out-of-pocket cost, dollars 

Travel Time Savings 

GradeDec.Net computes travel time benefits based on the delay 

experienced by the highway vehicles at the highway-rail grade crossings. 

See the section on delay for a complete discussion. 

The model calculates the probability that an individual highway vehicle 

will be blocked at a highway-rail grade crossing and the minutes of delay 

per vehicle. The product of these two quantities provides the average 

delay that each highway vehicle endures. This quantity is then multiplied 

by the total number of highway vehicles that arrive at the blocked grade 

crossing to obtain the total vehicle hours of delay. The highway vehicle 

delay hours are divided into passenger vehicles and trucks based upon the 

percentage of trucks data entry for the crossing. 

The delay per blocked vehicle is equal to the time per train converted to 

hours. The probability that a vehicle is blocked equals the total daily 

block time (time per train times number of trains per day) times the 

exposure correlation factor (a number between 0 and 1 representing the 

correlation between the time-of-day distributions of rail and highway 

traffic). 

The vehicle hours of delay are calculated at each crossing and for each 

year of the evaluation. 

Equation 28 Time Savings Benefits (for each year and crossing) 

base alt

bus

truck

auto

TTSB DCA DCA

DCA PVDC TDC BDC AF

vottr avgoccbus votpx

w

BDC

vottr

w

TDC

avgocc votpx

w

PVDC

 

 

 

 



( )

( )

60

60

60

where: 

PVDC average daily passenger vehicle delay time cost, dollars 

wauto average daily passenger vehicle delay, vehicle-minutes 

avgocc average passenger vehicle occupancy, passengers per vehicle 
GradeDec.Net Reference Manual The Model  39

votpx value of passenger time, dollars per hour 

BDC average daily bus delay time cost, dollars 

wbus average daily bus delay, vehicle-minutes 

vottr value of truck time (driver time), dollars per hour 

TDC average daily truck delay time cost, dollars 

wtruck average daily truck delay, vehicle-minutes 

DCA annual delay costs, dollars 

AF annualization factor 

TTSB annual travel time savings benefit, dollars 

Environmental Benefits 

GradeDec.Net calculates the reduction in highway vehicle emissions due 

to reduced idle time at the grade crossings. There will be reduced 

emissions with grade separations and closures. However, the reductions 

in emissions at the closed crossing will typically be offset by increases in 

emissions at the crossings that absorb traffic diverted from the closed 

crossings. 

There are emission rate tables for automobiles, transit vehicles, and trucks 

for six emission types: carbon monoxide, volatile organic compounds, 

nitrous oxide, articulate matter, sulfur oxide, and carbon dioxide. The 

model uses these values to calculate emissions from idling vehicles at 

grade crossings. Emission costs for highway vehicles are calculated by 

multiplying the appropriate emission rate (by vehicle type) by the time 

spent by each vehicle type at the grade crossing. This calculation is 

performed for the base and alternate cases, the net difference being the 

change in vehicle emission. 

Equation 29 Average Daily Emissions at Crossing by Vehicle Type 

  

Vtype

Etype Vtype Etype Vtypeq

EM RE t

907185

60

,

where: 

Etype emission type: VOC, CO, NOx, PM, SOx, CO2 

Vtype type of vehicle: car, truck or bus 

ERVtype, Etype emission rate (grams per minute) 

tq Vtype time-in-queue by vehicle type, vehicle-hours 

EMEtype emissions by type (tons per day) 

The value 907185 is the number of grams per ton 

Equation 30 Environmental Benefits (for each year and crossing) 

EB EM EM  VOE AF

Etype

Base Etype EtypeAlt Etype   [   ] , ,
40  The Model GradeDec.Net Reference Manual 

where: 

Etype emission type: HC, CO, NOx 

EMBase, Etype emissions by type in base case, tons 

EMAlt, Etype emissions by type in alternate case, tons 

VOEEtype emissions cost, dollars per ton 

AF annualization factor 

EB environmental benefit, dollars 

Vehicle Operating Cost Savings 

GradeDec.Net computes the vehicle operating cost savings as a result of 

the improvements at the highway-rail grade crossing. Savings are 

generated from the reduction in delay at the grade crossing following the 

grade crossing upgrade. Between the base and alternate cases, a reduction 

in delay will lead to decreased consumption of fuel and oil by the vehicles 

operating on the highways. Vehicle consumption of fuel and oil is 

calculated for each vehicle type using the rates of idling consumption of 

fuel and oil. The time delay for each vehicle type is multiplied by the 

consumption rate to derive the fuel or oil consumed by the vehicles at the 

grade crossing. 

Vehicle operating cost savings are then calculated by aggregating the 

change in gasoline, diesel and oil consumption for the different vehicle 

types and multiplying by their respective costs. 

Equation 31 Average Daily VOC at Crossing by Vehicle Type 

  

Vtype

Ftype Vtype VtypeqFtype

FCI RB t 60

,

where: 

Ftype fuel or oil type: gasoline, diesel, oil 

Vtype passenger vehicles, buses, trucks 

BRVtype, Ftype fuel burn rate rate - gallons (gas and diesel) or quarts (oil) 

per minute 

tq Vtype time-in-queue by vehicle type, vehicle-hours 

FCIFtype fuel/oil consumed idling during delays , gallons (gas and diesel) 

or quarts (oil) 
GradeDec.Net Reference Manual The Model  41

Equation 32 Vehicle Operating Cost Benefits (for each year and 

crossing) 

Base Alt

Ftype

Ftype

Ftype Ftype Ftype

year

year

Ftype year Ftype year

VOCB FCIC FCIC

FCIC FCIC AF

FCIC FCI FCOST

cpirg

fpirg

FCOST FCOST

 

 

 





 





1( )

1( )

, 1,

where: 

FCOSTFtype, year the constant dollar price of fuel in forecast year 

fpirgyear the fuel price index rate of growth 

cpirgyear the general price rate of growth 

FCICFtype fuel cost by fuel type 

FCIFtype average quantity of fuel consumed per day idling at crossing 

AF annualization factor 

VOCB vehicle operating cost benefit 

Network Benefits (Corridor Model Only) 

GradeDec.Net computes the estimated impacts of crossing investments 

on delay reduction on the neighboring highway network. The calculation 

relies on the average queue length on the approaching highway segments 

and the distance to the nearest major highway intersection. 

The model assumes that network delay is negligible when the queue does 

not extend to within one-half the distance to the nearest highway. As the 

queue lengthens beyond the half-way, the network delay increases until it 

reaches a value of 10 vehicle-minutes at the point where the queue 

extends to the nearest highway crossing. The network delay will continue 

to increase at a declining rate as the queue length reaches and extends 

beyond the intersection. If the grade crossing signal is synchronized with 

the highway traffic signals, then network delay from the grade crossing is 

reduced by 50%. The calculation of network delay for each crossing in 

each year is as follows: 
42  The Model GradeDec.Net Reference Manual 

Equation 33 Network Delay (for crossing, year) 



































 

















per

per

per

per

j

perj

ND ND

if sp true

DQLA BPP ndpfq

if sp false

DQLA BPP ndpfq

ND

if QL dth th

QL dth ifth QL dth th

DQL

BPP TV a

Lanes

vl VAPB

QL

ACBT

VAPB VAPH

AADT b

VAPH

,

60

5.0

,

60

,0 )(

( ), )(

5280

60

6







where: 

ACBT average crossing block time, minutes (see Equation 11) 

AADT average annual daily traffic at crossing 

VAPH average number of vehicles arriving at crossing per hour in timeof-day period 

bj,per share of daily highway traffic of vehicle type j in time-of-day 

period 

j share of vehicle type j in daily traffic

VAPB average number of vehicles arriving at crossing during block 

QL queue length at blocked crossing, miles 

vl average length of vehicle (set at 22 feet) 

TV average number of trains per day 

BPP average number of blocks per period 

aper share of daily trains in time-of-day period 

DQL the portion of the queue length that contributes to network delay, 

miles 

dth distance of crossing to nearest highway intersection, miles 

th the distance from major intersection such that if queue extends 

beyond this point network delay begins to accrue. Set at half of dth. 
GradeDec.Net Reference Manual The Model  43

NDPer network delay in time-of-day period, vehicle-hours 

A a value calibrated so that network delay equals 10 vehicle-minutes 

when queue reaches the intersection 

 elasticity of network delay with respect to queue length, set to 0.7 

sp true/false flag designating whether grade crossings are 

synchronized with signal progression on the highway network 

ndpfq the number of vehicle-hours of network delay caused by a queue 

extending to the nearest major intersection. Set at one-sixth vehicle-hours 

(equal to 10 vehicle-minutes) 

ND daily network delay in vehicle-hours 

Figure 7 Network Delay as a Function of Queue Length (when 

intersection is 0.5 miles from crossing) 

As with the other benefits categories, network delay is calculated in the 

base and the alternate cases. The savings times the appropriate cost value 

is the network delay benefit. 

Equation 34 Network Benefits (for each crossing and year) 

NDSB NDCA base NDCA alt

NDCA NDPC NDBC NDTC AF

NDTC ND strucks vottr

NDBC ND sbus vottr avgoccbus votpx

NDPC ND strucks sbus avgocc votpx

 

   



 

 

( )

( )

1( )

where: 

NDPC average daily cost of network delay, passenger vehicles, dollars 

ND average daily network delay, vehicle-hours 

avgocc average passenger vehicle occupancy, passengers per vehicle 

votpx value of passenger time, dollars per hour 

strucks share of highway traffic that is trucks 

sbus share of highway traffic that is buses 

NDBC average daily cost of network delay, buses, dollars 
44  The Model GradeDec.Net Reference Manual 

avgoccbus average bus occupancy, passengers per bus 

NDTC average daily cost of network delay, trucks, dollars 

vottr value of truck time, dollars per hour 

NDCA annual network delay costs, dollars 

AF annualization factor 

NDSB annual network delay savings benefit, dollars 

Local Benefits 

Local benefits in the corridor are calculated as a percentage of the 

benefits from all the preceding benefits categories summed over all the 

grade crossings. These benefits represent the value of the grade crossing 

improvements to the local community or communities. These include 

benefits not conventionally counted like: improved mobility for residents 

(due to easier, safer crossings), reduced noise, economic benefits from 

improved access, etc. The local benefits are equal to the sum of all the 

previously discussed benefits times the local benefits factor. 

Equation 35 Local benefits (for each year) 

LB SB TTSB VOCB EB lbfNDB

GCX GCX GCX GCX GCX



















         

where: 

LB Annual local benefits in the corridor, dollars 

SB Annual safety benefits, dollars 

TTSB Travel time savings benefits, dollars 

VOCB Vehicle operating cost savings benefits, dollars 

EB Environmental benefits, dollars 

NDB Network delay savings benefits, dollars 

lbf Local benefits factor (exogenously determined factor) 

Project Costs 

There are three components of project costs. First, there are capital 

outlays that are incurred in the alternative case. Second, annual operating 

and maintenance costs for each crossing. Third, other lifecycle costs for 

each of the grade crossings in the corridor. The following is the formula 

for costs: 
GradeDec.Net Reference Manual The Model  45

Equation 36 Total and Net Project Costs (for each year) 

Alt Base

Alt Alt Alt

Alt Alt Alt

Alt Alt Alt Alt

Alt

Base Base Base Base Base

NC TC TC

OMss LCss CCss dr if year

OM LC CC dr

OM LC OMss LCss if year

TC

TC OM LC OMss LCss













    

 

   



   

,)1( 1

)1(

, 1

where: 

TC total project costs in year (for each case, base and alternate), 

dollars 

OM operating and maintenance costs (for each case, base and 

alternate), dollars 

LC other life-cycle costs (for each case, base and alternate), dollars 

CC capital costs (alternate case only, presumed executed in year 0 - 

the base year), dollars 

OMss operating and maintenance costs (for each case, base and 

alternate) for supplementary safety measure (for gated crossings only), 

dollars 

LCss other life-cycle costs (for each case, base and alternate) for 

supplementary safety measure (for gated crossings only), dollars 

CCss capital costs (alternate case only, presumed executed in year 0 - 

the base year), for supplementary safety measure (for gated crossings 

only) dollars 

dr discount rate 

NC net project costs, dollars 

Salvage Value 

In an analysis of the benefits and costs of infrastructure investments, it is 

customary to “add back” the residual or salvage value of the investments 

at the end of the time horizon of the analysis. In principle, this represents 

the value of the remaining useful life of the capital improvements. 

In GradeDec.Net the analysis assumes that the value of the invested 

capital declines by 5% per year. The salvage value is calculated at the 

end of the analysis period. In the benefit-cost summary it is discounted to 

present value terms. 

 









cr

lyr

t t

InvYr

Salvage IVal

IVal IVal

IVal CapCost

1

1

 )1(
46  The Model GradeDec.Net Reference Manual 

where: 

IValInvyr Value of the improvement in the year of its 

implementation 

CapCost capital cost of the improvement 

IValt Value of the improvement in year t 

IValt-1 Value of the improvement in year t-1 

 rate of depreciation, set at 5 percent per year 

Consumer Surplus 

The benefit components described above include only the benefits 

accruing to current users of the roadway network. With grade crossing 

improvements, the generalized cost of travel by car in the corridor or 

region will decline. As a result, we expect that grade crossing 

improvements will induce some additional highway traffic. The 

consumer surplus includes both the consumer surplus from the base case 

auto trips as well as from the induced trips (see Figure 7 below). The 

model assumes that bus and truck traffic in the corridor or region are not 

sensitive to the changes in generalized cost from grade crossing 

improvements. 

Figure 8 Consumer Surplus 

In addition to incremental consumer surplus, induced trips will also 

generate external costs. GradeDec.Net calculates these external costs and 

G e n e ra liz e d C o s t

AADT

P B

P A

Q AQ B

CS 2 - Consumer

surplus from

induced trips

CS 1 - Consumer

surplus from

base case trips
GradeDec.Net Reference Manual The Model  47

deducts them from the total benefits. The following are the model 

equations for the calculation of consumer surplus and the external costs 

from induced trips. 

Equation 37 Base Case Auto Travel Demand in the Corridor or 

Region 

 

i

B i i Q  AADT

where: 

i index of the crossing (i.e., each of n crossings in the corridor or 

region is indexed from 1 to n) 

i auto share of traffic at the crossing 

AADTi average annual daily traffic at crossing i 

The costs that influence the traveler's decision to make additional trips are 

the internal costs, namely: safety risk, travel time and vehicle operating 

cost. 

Equation 38 Base case Generalized Cost of Auto Trips 

B

i

i BiBi Bi

B

pTC Q

sr tt voc

P









/( 100 )

( )

where: 

PB imputed average generalized trip cost in the corridor 

i auto share of traffic at the crossing 

srBi auto cost of accidents at crossing i, dollars 

ttBi auto travel time delay costs at crossing i, dollars 

vocBi auto vehicle operating cost at crossing i, dollars 

pTC percent share of trip costs at the crossing 

QB auto AADT at crossings in the corridor or region 

GradeDec.Net represents highway auto travel demand with a standard, 

Cobb-Douglas functional form, which has a fixed elasticity of demand 

with respect to generalized cost. 

Equation 39 Auto Highway Travel Demand as a Function of 

Generalized Cost 



 PAQ

where: 

Q daily trips that traverse the crossings in the corridor or region as 

measured by AADT at the grade crossings 
48  The Model GradeDec.Net Reference Manual 

P the generalized average cost of auto trips traversing crossings in 

the region or corridor 

 elasticity of demand for auto trips with respect to generalized cost 

A a constant, derived by substituting QB, PB and solving 

The alternate case generalized cost is based on the imputed cost in the 

base case and the change in cost at the crossing. 

Equation 40 Alternate Case Generalized Cost of Auto Trips 



















  



 

B

i

i BiBi Bi

i

i AiAi Ai

BA

Q

sr t t voc sr t t voc

PP

( ()  )

where: 

PB the imputed average generalized trip cost in the corridor in the 

base case 

i auto share of traffic at the crossing 

srAi cost of accidents at crossing, alternate case, dollars 

ttAi travel time delay at crossing i, alternate case, dollars 

vocAi the auto vehicle operating cost at crossing i, alternate case, dollars 

srBi the cost of accidents at crossing i, base case, dollars 

ttBi travel time delay at crossing i, base case, dollars 

vocBi the auto vehicle operating cost at crossing i, base case, dollars 

QB auto AADT at crossings in the base case 

The travel demand in the alternate case is derived by applying the auto 

travel demand function from Equation 39. 

Equation 41 Alternate case auto travel demand 



A A

Q  AP

where: 

PA alternate case average generalized cost of travel in the corridor or 

region elasticity of auto travel demand with respect to generalized cost 

A constant of demand function 

Consumer surplus is estimated in the conventional way as the area 

beneath the demand curve. Since the demand curve is based on daily 

traffic, the result is annualized. 
GradeDec.Net Reference Manual The Model  49

Equation 42 Total Consumer Surplus (in each year) 

 PP  AF

A

CS PA dP AF B A

P

P

B

A





 

 



1 1

1

  



where: 

PA alternate case average generalized cost of travel in the corridor or 

region 

PA base case average generalized cost of travel in the corridor or 

region 

A demand function constant 

 elasticity of demand with respect to generalized cost 

AF annualization factor 

The consumer surplus from base case trips, and which is already included 

in the calculation of the benefit components, is given by: 

Equation 43 Consumer Surplus from Base Case Trips (in each year) 

CS PPQ AF ABB)(  1

where: 

QB auto AADT at crossings in the base case 

PB imputed average generalized trip cost in the corridor in the base 

case 

PA imputed average generalized trip cost in the corridor in the 

alternate case 

AF annualization factor 

The consumer surplus from the induced trips is the difference between the 

total consumer surplus and the consumer surplus from base case trips. 

Equation 44 Consumer Surplus from Induced Trips 

2 CSCSCS 1



The disbenefit that is generated by induced trips is equal to the external 

costs (congestion and emissions) that each induced trip generates. This 

disbenefit is estimated by the following equation. 

Equation 45 Disbenefit from Induced Trips 











 















 











  

A

BA

i

Ai Ai

Q

QQ

pTC

AF

DisBen ec ndc

100/

( )

where: 

eci emission costs at crossing i, alternate case, dollars 

ndci network delay costs due to queuing at crossing i, alternate case 

dollars 

pTC percent share of trip costs at the crossing 
50  The Model GradeDec.Net Reference Manual 

QB auto AADT at crossings in the base case 

QA auto AADT at crossings in the alternate case 

AF annualization factor 

Total Benefits and Benefit-Cost Indicators 

GradeDec computes the corridor (or regional) level benefits from grade 

crossing improvements by aggregating the benefits estimated for each 

individual crossing and then adding the consumer surplus from induced 

trips and subtracting the disbenefit (in the form of external costs) from 

these trips. A simple sum is used to aggregate the safety benefits, travel 

time benefits, vehicle operating cost benefits, environmental benefits and 

network delay benefits. 

Equation 46 Total benefits (excluding local) in corridor (for each 

year) 

DisBen Salvage

SB TTSB VOCB EB NDB CS

TB

GCX GCX GCX GCX GCX

 

    



     2

where: 

TB total annual local benefits in the corridor, dollars 

SB annual safety benefits, dollars 

TTSB travel time savings benefits, dollars 

VOCB vehicle operating cost savings benefits, dollars 

EB environmental benefits, dollars 

NDB network delay savings benefits, dollars 

CS2 consumer surplus from induced trips 

DisBen disbenefit from induced trips 

Salvage Salvage value of investments (last year only) 

The net benefits for the corridor or region are calculated as follows: 

Equation 47 Net benefits (excluding local) in corridor (for each year) 

NB TB  NC

where: 

NB net benefits, dollars 

TB total benefits, dollars 

NC net project costs, dollars 

The following formulas give the present value calculations of benefits, 

costs and net benefits. 
GradeDec.Net Reference Manual The Model  51

Equation 48 Present value benefits 







year

year

year

dr

TB

PVB

)1(

where: 

PVB present value of benefits, dollars 

TB total benefits, dollars 

dr discount rate 

Equation 49 Present Value Costs 







year

year

year

dr

NC

PVC

)1(

where: 

PVC present value of project costs, dollars 

NC net costs, dollars 

dr discount rate 

Equation 50 Net Present Value 

NPV PVB  PVC

where: 

NB net present value, dollars 

PVB present value benefits, dollars 

PVC present value costs, dollars 

The following is the benefit-cost ratio calculation. 

Equation 51 Benefit-Cost Ratio 

PVC

PVB

BCR 

where: 

BCR benefit-cost ratio 

PVB present value benefits, dollars 

PVC present value costs, dollars 

The following is the project rate of return calculation. 

Equation 52 Project Rate of Return 

( )

year year PRR  IRR TB  NC

where: 

PRR project rate of return 
52  The Model GradeDec.Net Reference Manual 

IRR designates a function that returns the discount rate for which the 

present value of the net benefit stream is equal to zero. 

TByear Total benefits, dollars 

NCyear Net project costs, dollars 
GradeDec.Net Reference Manual The Model  53

GradeDec.Net Reference Manual Data and Data Organization  55

Data and Data Organization 

Introduction 

There are four principal data elements in GradeDec.Net and these were 

described in the Model Overview section above. The following sections 

include detailed descriptions of the data in each of the data elements. 

Corridor Data 

The following are the corridor data variables. Except where noted, the 

variable descriptions are self-explanatory.

Number of Passenger Trains per Day 

Number of Freight Trains per Day 

Number of Switch Trains per Day 

Rail Traffic Daily Distribution 

The user can choose from one of five daily traffic distributions: uniform, 

AM peak, PM peak, day flat, night flat. These distributions of traffic 

divide the daily traffic into four six-hour periods. These are early AM 

(12AM-6AM), late AM (6AM- 12PM), early PM, (12PM-6PM), and late 

PM (6PM-12AM). The traffic distributions are each represented as a 

vector of four values that sum to 1. For example, the uniform distribution 

is given by (.25,.25,.25,.25). The GradeDec.Net default distributions are 

given in the "Time-of-Day Distributions" section of "Model 

Components". The user can modify these distributions to reflect 

conditions in the corridor under evaluation. 

Signal Synchronization with the Highway Network (yes/no) 

This yes/no variable indicates whether the grade crossing signaling is 

synchronized with the signaling system of the adjacent highway network.

Technology Impact Factor 

The accident incidence of the "new technology" crossing type will be 

determined by the Technology Impact Factor. This factor determines the 

safety risk of new technology relative to conventional lights and gates 

crossing barriers, i.e., a value of 0.5 for this factor will yield safety risk 

half that of a lights and gates crossing. 
56  Data and Data Organization GradeDec.Net Reference Manual 

Region Data 

Besides its description, the following are the two parameters associated 

with a region: 

Technology Impact Factor 

See the description above under Corridor Data. 

Percent Benefit from Closure 

The regional model, unlike the corridor model, does not reassign traffic at 

the crossing when the crossing is closed. When a crossing is closed, 

there are no longer highway user costs at the crossing. However, the trips 

of highway users who used the route with the crossing in the base case 

did not simply disappear. Most likely, the highway trips at the crossing 

will divert to another crossing and new user costs will be realized at that 

crossing. This "percent benefits" parameter determines the percent of 

base case user costs that will be realized as a benefit. For instance, if the 

parameter is set to 0 this is equivalent to all highway users finding 

alternate routes that have exactly the same user costs as the base case. If 

this parameter is set to a value greater than 0 (say, 10) this implies that 

users find lower cost alternatives in the alternate case when the crossing is 

closed and 10 percent of the base case cost is realized as benefit. 

Conversely, if the parameter is set to –10 then users find alternatives that 

are 10% more costly than the base case and there is a net disbenefit from 

the closure. 

Grade Crossing Data 

The following are the crossing data variables. The variables noted below 

are either common to both corridors and regions, or are unique to one or 

the other as noted. Except where noted, the variable descriptions are selfexplanatory.

Milepost (corridor and region) 

The Milepost is a decimal number (i.e., 153.7) that identifies the crossing 

and specifies its geographic location within the rail corridor. The 

difference between the mileposts of two consecutive crossings should 

equal the distance between them in miles. The data for crossings in a 

corridor should be entered in a linear sequence (i.e., with mileposts in 

either ascending or descending order). This order has no significance for 

a region and the milepost only serves as an additional identifier of the 

crossing. 

Crossing ID (region only) 

This is the unique crossing ID corresponding to the 7-character crossing 

identifier in the National Inventory of Grade Crossings. 

Paved/Unpaved (corridor and region) 
GradeDec.Net Reference Manual Data and Data Organization  57

This yes/no variable designates whether the highway at the crossing is 

paved or unpaved.

Urban/Rural (corridor and region) 

A yes/no variable that designates whether the crossing is in an urban or 

rural 

 Grade Crossing Base Type (corridor and region) 

This variable designates the type of crossing in the base case. 

There are six types of grade crossings used in GradeDec.Net: passive, 

flashing lights only, flashing lights and gates, closure, grade separation 

and new technology. The "new technology" type of grade crossing is a 

hypothetical type of crossing that may involve advanced traffic 

management and information systems and/or new kinds of barriers. 

The crossing types correspond to the crossing types in the National 

Inventory of Grade Crossings database. GradeDec.Net maps these types 

into the types used by its model as follows: 

Table 4 Mapping of Crossing Types 

National Inventory 

Crossing Type

 GradeDec.Net Crossing 

Type

No Device

Stand Stop

Crossbucks

Special Procedure

Passive

Flashing Lights Flashing Lights

Wigwags

Gates

Lights and Gates

Region crossing types also include closure, grade separation and new 

technology. These are the same types as in the corridor model. 

Grade Crossing Alternate Type (corridor and region) 

This variable designates the type of crossings in the alternate case. See 

the descriptions for crossing types in the base case. 

Safety Supplement Base Type (corridor and region, only 

available for gated crossings) 

This variable specifies whether a supplementary safety measure is 

deployed at the crossing in the base case. Supplementary safety measures 

include the following: four quadrant gates – no detection, four quadrant 

gates with detection, four quadrant gates with 60 foot medians, mountable 

curbs, barrier curbs, one-way streets, and, photo enforcement. 

Safety Supplement Base Type (corridor and region, only 

available for gated crossings) 

This variable specifies whether a supplementary safety measure is 

deployed at the crossing in the base case. Supplementary safety measures 
58  Data and Data Organization GradeDec.Net Reference Manual 

include the following: four quadrant gates – no detection, four quadrant 

gates with detection, four quadrant gates with 60 foot medians, mountable 

curbs, barrier curbs, one-way streets, and, photo enforcement. 

Safety Supplement Alternates Type (corridor and region, only 

available for gated crossings) 

This variable specifies whether a supplementary safety measure is 

deployed at the crossing in the alternate case. See the Base Type 

description above. 

Number of Highway Lanes (corridor and region) 

Highway Traffic (AADT) (corridor and region) 

This is the bi-directional average annual daily highway traffic at the 

crossing.

Of the Highway Traffic, the Percent of Vehicles that are Trucks 

(corridor and region) 

Of Trucks, the Percent that are Truck Trailers (corridor) 

Of the Highway Traffic, the Percent of Vehicles that are Buses 

(corridor and region) 

Auto Time-of-Day Traffic Distribution (corridor and region) 

This variable represents the distribution of auto traffic at the crossing in a 

typical 24-hour period. 

The user can choose from one of five daily traffic distributions: uniform, 

AM peak, PM peak, day flat, night flat. These distributions of traffic 

divide the daily traffic into four six-hour periods. These are early AM 

(12AM-6AM), late AM (6AM- 12PM), early PM, (12PM-6PM), and late 

PM (6PM-12AM). The traffic distributions are each represented as a 

vector of four values that sum to 1. For example, the uniform distribution 

is given by (.25,.25,.25,.25). The GradeDec.Net default distributions are 

given in the "Exposure and Correlation of Time-of-Day Distributions by 

Highway and Rail" subsection of "The Model" section. The user can 

modify these distributions to reflect conditions in the corridor or region 

under evaluation.

Truck Time-of-Day Traffic Distribution (corridor and region) 

This variable represents the distribution of truck traffic at the crossing in a 

typical 24-hour period. See the discussion under auto time-of-day traffic 

distribution. 

Bus Time-of-Day Traffic Distribution (corridor and region) 

This variable represents the distribution of bus traffic at the crossing in a 

typical 24-hour period. See the discussion under auto time-of-day traffic 

distribution. 

Yes/No Flag Indicating whether Alternate Case includes Traffic 

Management Measures for Re-assigning Traffic at the 

Crossing (corridor and region) 
GradeDec.Net Reference Manual Data and Data Organization  59

This flag determines that the user specifies alternate case values for 

AADT by traffic segment and the time-of-day distribution of traffic 

segments. These new values represent the projected impact of proposed 

traffic management measure on highway traffic at the crossing. 

Highway Traffic (AADT), Of the Highway Traffic, the Percent 

of Vehicles that are Trucks, Of the Highway Traffic, the 

Percent of Vehicles that are Buses, Auto Time-of-Day 

Traffic Distribution, Truck Time-of-Day Traffic 

Distribution, Bus Time-of-Day Traffic Distribution – 

Alternate Case (corridor and region) 

These data are entered in the Alternate Case only if the flag indicating the 

presence of traffic management measures is set. 

Number of Railroad Tracks (corridor) 

This is the number of traffic-bearing tracks at the crossing. 

Number of Main Railroad Tracks (region) 

This is the number of daily traffic-bearing tracks at the crossing. 

Number of Other Railroad Tracks (region) 

Other tracks at the crossing are special use tracks. 

Maximum Schedule Train Speed (corridor and region) 

Average Number of Day Through Trains (region) 

This includes both passenger and freight trains. 

Average Number of Night Through Trains (region) 

This includes both passenger and freight trains. 

Average Number of Day Switch Trains (region) 

Average Number of Night Switch Trains (region) 

Distance from Highway (corridor only) 

This is the distance, measured in miles, from the crossing to the nearest 

major highway intersection. 

Number of Accidents at Crossing in Past Five Years 

Crossing Costs 

The cost data for the crossing include O&M costs and other lifecycle 

costs for the base and alternate cases and capital costs for the alternate 

case. O&M and other lifecycle costs are annual outlays that are repeated 

every year. Capital costs (i.e. the cost of improving the crossing) is a 

one-time outlay that is expended in the year prior to the start year of the 

analysis 
60  Data and Data Organization GradeDec.Net Reference Manual 

Scenario Data 

The scenario data include those variables to which probability 

distributions can be assigned. There are distinct scenarios for the two 

models, as the set of variables for the corridor model differs slightly from 

that of the regional model. In the descriptions below, the variables 

belonging to each model are shown. 

A simulation engine solves the GradeDec.Net model for a specified 

number of trials. For each trial, a randomly sampled value is selected 

from each of the probability distributions as its input value. The 

collection of model solutions represents a probability distribution of the 

model's result variables. 

The scenario variables are divided into four data sets, namely: Rail 

Operations, Highway, Social Costs and Price Indexes. For each of the 

variables in the scenario data the user can specify whether the value is 

fixed or, is one of four types of probability distributions. These 

distributions types are: 

 uniform probability distribution, which requires the 

specification of two end points of an interval to define the 

distribution. 

 normal probability distribution, which requires that the user 

specify the mean value and the standard deviation of the 

distribution, and 

 a skewed-bell distribution that is normal when symmetric, but 

allows for skew and which requires three defining points 

corresponding to its 10, 50 and 90 percentiles. 

 A triangle distribution, where the user specifies a minimum 

value, maximum value and the most likely value. 

Rail Operations 

These variables are used to define the rail operations in the corridor. The 

variables are: 

Annual Rate of Growth in Train Traffic, Near Term, Percent 

(corridor and region) 

Annual Rate of Growth in Train Traffic, Far Term, Percent 

(corridor and region) 

Number of Rail Cars per Freight Train (corridor) 

Number of Rail Cars per Passenger Train (corridor) 

Number of Rail Cars per Switch Train (corridor and region) 

Average Length of Freight Rail Cars, Feet (corridor) 

Average Length of Passenger Rail Cars, Feet (corridor) 
GradeDec.Net Reference Manual Data and Data Organization  61

Average Length of Switch Train Cars, Feet (corridor and 

region) 

Number of Rail Cars per Through Train (region) 

Average Length of Through Train Rail Cars, Feet (region) 

Highway 

The following variables define the corridor-level highway characteristics. 

The highway data are required for the forecasting of highway-related 

benefits. 

Annual Rate of Growth of Highway Traffic, Near Term, Percent 

(corridor and region 

Annual Rate of Growth of Highway Traffic, Far Term, Percent 

(corridor and region) 

Annualization Factor (corridor and region) 

This is a factor for converting daily benefits to annual benefits.

Average Auto Vehicle Occupancy (corridor and region) 

This is the average number of occupants per vehicle. 

Average Bus Vehicle Occupancy (corridor and region) 

This is the average number of passenger occupants on a bus. 

Elasticity of Auto Travel Demand with respect to Generalized 

Cost of Travel (corridor and region) 

This variable is the percent change in corridor or region AADT per 

percent change in generalized cost. For instance, if a 10% increase in 

travel cost results in a 1% decrease in AADT then the elasticity of 

demand with respect to cost is –0.1. Many travel demand studies show 

that the value for the variable is many cases about –0.1. The "generalized 

cost of travel" includes all of the internal costs of auto travel that are 

perceived by users including: vehicle operating costs, travel time and 

safety risk. 

Average Percent of Auto Trip Costs that are Crossing-Related, 

Percent 

This is the corridor or region average of the percent of total trip costs at 

the crossing. For instance, if an average trip has a generalized cost of 

$8.00 and $0.80 are the average trips costs at the crossing, then the value 

for this variable should be 10. This factor is used in the consumer surplus 

calculation. 

Social and Other Costs 

The variables represent the monetized value of social costs and the market 

value of other costs. 
62  Data and Data Organization GradeDec.Net Reference Manual 

The Discount Rate 

This variable is the real discount rate for the analysis. This rate is applied 

to future constant dollar cost and benefit streams (i.e., the benefits and 

costs have been adjusted to account for forecast inflation). 

Cost of a Fatal Accident, $'000 (corridor and region) 

Cost of an Injury Accident, $'000 (corridor and region) 

Cost of a Property Damage Accident, $'000 (corridor and 

region) 

Cost per Fatality, $'000 (HSR formulas) 

Cost per Injury, $'000 (HSR formulas) 

Average Out-of-Pocket Cost per Accident, $"000 (HSR 

formulas) 

Value of Time (auto) ($/person-hr.) 

Value of Time (truck – driver time)) ($/truck-hr.) (corridor and 

region) 

Cost of HC Emissions, $'000/Ton 

Cost of NOx Emissions, $'000/Ton 

Cost of CO Emissions, $'000/ Ton 

Base Fuel Cost, $/Gallon 

This variable refers to the cost of fuel (dollars per gallon) in the base year.

Base Oil Cost, $/Quart 

Fuel Cost, Annual Rate of Change, Percent 

Inflation, Annual Rate, Percent 

This variable refers to the cost of motor oil (dollars per quart) in the base 

year. 

Sources for social cost default data included in the scenarios provided 

with GradeDec.Net for the values of time, crash costs and emissions 

costs were derived from: 

TIGER Benefit-Cost Analysis (BCA) Resource Guide, updated 

4/18/2014, U.S. Department of Transportation, http://www.dot.gov/tiger 

Model Parameters and Default Values 

The following parameters and default values are used in the model to 

calculate: accident costs, capital and maintenance costs, emission rates 

by vehicle type, railroad emissions by engine type, and the rate fuel and 

oil are consumed by vehicle type per minute. 

Grade crossing types used in the following data tables are: 
GradeDec.Net Reference Manual Data and Data Organization  63

1. Passive Grade Crossing 

2. Flashing Lights 

3. Flashing Lights and Gates 

4. Grade Closure 

5. Grade Separation 

6. New Technology 

Table 4 Project Costs

Crossing 

Type

Initial Capital 

Cost

(thous. of $)

O and M 

Costs 

(thous. of 

$)

Other 

Life Cycle 

Costs

(thous. of 

$)

Passive 1.6 .2 0.0

Lights 74.80 1.8 0.0

Gates 106.10 2.5 0.0

Closure 20.00 0.0 0.0

Separation 1,500.00 .5 0.0

New Technology 180.00 .5 0.0

Based on FRA internal data 

Table 5 Costs for Supplementary Safety Measures

Measure 

Type

Initial Capital 

Cost

(thous. of $)

O and M 

Costs 

(thous. of 

$)

Other 

Life Cycle 

Costs

(thous. of 

$)

4-quadarnt gates

without detection

244 3.5 0.0

4-quadarnt gates

with detection

260 5 0.0

4-quadarnt gates

with 60' medians

255 25 0.0

Mountable curbs 15 3.5 0.0

Barrier curbs 15 3.5 0.0

One-way street 5 3.5 0.0

Photo 

enforcement

65 25 0.0

Based on FRA internal data 
64  Data and Data Organization GradeDec.Net Reference Manual 

Table 6 Emission Rates by Type of Vehicle, Grams per Minute

VehType

ID

VEH VOC CO NOX PM SOX CO2

1 Cars 0.0447 1.1871 0.0586 0 0 31.0652

2 Buses 0.1083 2.5317 0.0888 0 0 87.5789

3 Tucks 0.0576 0.4271 0.5627 0.0383 6.9937 107.4107

Sources: CO2 emissions per gallon of fuel consumed EPA Emission 

Facts, Calculating Emissions of Greenhouse Gases: Key Facts and 

Figures (February 2005) 

Non-carbon emission rates per hour EPA, Idling Vehicle Emissions for 

Passenger Cars, Light-Duty Trucks, and Heavy-Duty Trucks (October 

2008)

Table 7 Rates of Fuel and Oil Consumption 

Type of

Vehicle

Fuel

gallons/minute

Oil

quarts/minute

1-car .00969 0.000626

2-bus 0.0184 0.000119

3-truck 0.02067 0.00134

Sources: "Passenger Car Fuel Economy - A Report to Congress", January 

1980, EPA 

HERS Technical Report v3.26 Appendix H: A Numerical Example, 

FHWA, June 2000 

"Technology Options to Reduce Truck Idling", F. Stodolsky, L. Gaines, 

A. Vyas, Transportation Technology, R&D Center - Argonne National 

Laboratory 

Table 8 High Speed Rail Model Parameters – Accident Breakout by 

Type 

Percent Breakout of accidents by type

Train Strike Highway Vehicle 84

Highway Vehicle Strikes Train 16

Table 9 High Speed Rail Model Parameters – Coefficients for Train 

Strikes Highway Vehicle Accident 

Name Auto Truck Trailer

Highway Fatalities 0.000127 0.000111 0.00004

Train Fatalities 0.000005 0.00001 0.000044

% Accidents with Severe 

Derailment

0.0001 0.001 0.007
GradeDec.Net Reference Manual Data and Data Organization  65

Added Severity with Severe 

Derailment

0.00022 0.00022 0.00022

Speeds of maximum severity 

(highway)

70 70 65

Table 10 High Speed Rail Model Parameters – Coefficients for 

Highway Vehicle Strikes Train Accident 

Name Auto Truck Trailer

Highway Fatalities 0.000127 0.000111 0.00004

Train Fatalities 0.000005 0.00001 0.000044

% Accidents with Severe 

Derailment

0.0001 0.001 0.007

Added Severity with Severe 

Derailment

0.00022 0.00022 0.00022

Speeds of maximum severity 

(highway)

70 70 65

Highway Fatalities 0.217 0.16 0.091

Train Fatalities 0.01 0.01 0.01

Source: Assessment of Risks for High Speed Rail Grade Crossings on the 

Empire Corridor, Mark Mironer and Michael Coltman, High Speed 

Ground Transportation Division, VNTSC, April 1998 

Table 11 Default Values for Diurnal Traffic Distribution 

Diurnal Distributions (Share of daily traffic in hour)

Name/Description 12 1 2 3 4 5 6 7 8 9 10 11

Uniform / Uniform

AM 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167

PM 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.167 4.159

AM Peak / AM Peak

AM 1.667 1.667 1.667 1.667 1.667 8.333 8.333 8.333 8.333 8.333 8.333 8.333

PM 5.833 5.833 5.833 5.834 5.834 0.833 0.833 0.833 0.833 0.833 0.834 0.834

PM Peak / PM Peak

AM 0.833 0.833 0.833 0.833 0.833 5.833 5.833 5.833 5.833 5.833 5.833 5.833

PM 8.333 8.333 8.333 8.333 8.334 8.334 1.667 1.667 1.667 1.667 1.668 1.668

Day Flat / Day Flat 

AM 1.667 1.667 1.667 1.667 1.666 1.666 6.667 6.667 6.667 6.667 6.666 6.666

PM 6.667 6.667 6.667 6.667 6.666 6.666 1.667 1.667 1.667 1.667 1.666 1.666

Night Flat / Night Flat
66  Data and Data Organization GradeDec.Net Reference Manual 

Diurnal Distributions (Share of daily traffic in hour)

Name/Description 12 1 2 3 4 5 6 7 8 9 10 11

AM 6.667 6.667 6.667 6.667 6.666 6.666 1.667 1.667 1.667 1.667 1.666 1.666

PM 1.667 1.667 1.667 1.667 1.666 1.666 6.667 6.667 6.667 6.667 6.666 6.666

AM Peak FR WD LC / AM Peak, Freeway Weekday, Traffic Distribution Profile for Low Congestion 

AM 1.000 0.500 0.500 0.500 1.000 2.490 6.470 9.450 6.970 4.980 4.980 4.480

PM 4.980 5.470 5.970 6.470 6.970 6.970 5.470 3.980 3.480 2.990 2.490 1.440

AM Peak Non-FR WD LC / AM Peak, Non-Freeway Weekday, Traffic Distribution Profile for Low Congestion

AM 0.990 0.490 0.490 0.490 2.990 2.460 4.430 8.370 6.900 4.930 4.930 5.420

PM 6.400 6.400 6.400 6.900 6.900 6.400 4.930 4.430 3.450 2.960 2.460 1.480

PM Peak FR WD LC / PM Peak, Weekday, Traffic Distribution Profile for Low Congestion

AM 1.000 .500 .500 .500 1.000 1.500 3.500 5.500 5.000 4.500 4.500 5.000

PM 5.500 5.500 6.500 8.000 9.500 9.500 6.500 4.500 3.500 3.000 3.000 2.000

PM Peak Non-FR WD LC / PM Peak, Non-Freeway, Traffic Distribution Profile for Low Congestion 

AM 0.980 0.490 0.490 0.490 0.490 0.980 2.450 4.410 4.410 4.410 4.900 5.880

PM 6.860 6.370 6.860 8.330 9.310 9.310 6.370 4.900 3.920 2.940 2.450 2.000

AM Peak FR WD MC / AM Peak. Freeway Weekday, Traffic Distribution Profile for Moderate Congestion

AM 1.010 0.500 0.500 0.500 1.010 2.510 6.530 9.050 7.540 5.530 5.030 5.030

PM 5.030 5.530 5.530 6.530 7.040 6.530 5.030 4.020 3.020 3.020 2.510 1.470

AM Peak Non-FR WD MC/ AM Peak, Non-Freeway Weekday, Traffic Distribution Profile for Moderate Congestion

AM 1.010 0.500 0.500 0.500 1.010 1.510 4.520 7.540 7.040 5.030 5.030 5.030

PM 6.530 6.530 5.53- 7.040 7.040 7.040 5.530 4.520 3.520 3.020 2.510 1.470

PM Peak FR WD MC / PM Peak, Freeway Weekday, Traffic Distribution Profile for Moderate Congestion

AM 1.010 0.500 0.500 0.500 0.500 1.500 4.000 6.000 5.500 4.500 4.500 5.000

PM 5.500 5.500 6.500 7.500 9.000 9.000 6.500 4.500 3.500 3.500 3.000 2.000

PM Peak Non-FR WD MC / PM Peak, Non-Freeway, Traffic Distribution Profile for Moderate Congestion

AM 1.020 0.510 0.510 0.510 0.510 1.020 1.520 4.570 4.570 4.570 5.080 6.090

PM 6.600 6.600 6.600 7.610 9.140 9.140 6.600 5.080 4.570 3.550 2.540 1.490

AM Peak FR WD SC / AM Peak, Freeway Weekday, Traffic Distribution Profile for Severe Congestion

AM 1.020 0.510 0.510 0.510 0.510 2.030 5.580 7.610 7.110 6.090 5.580 5.580

PM 5.580 5.580 6.090 6.600 6.600 6.600 5.580 4.570 3.050 3.050 2.540 1.520

AM Peak Non-FR WD SC / AM Peak, Non-Freeway Weekday, Traffic Distribution Profile for Severe Congestion 

AM 1.030 0.520 0.520 0.520 0.520 2.060 3.090 7.220 6.190 5.150 5.670 5.680
GradeDec.Net Reference Manual Data and Data Organization  67

Diurnal Distributions (Share of daily traffic in hour)

Name/Description 12 1 2 3 4 5 6 7 8 9 10 11

PM 6.190 6.190 6.700 7.220 7.220 7.220 5.670 4.640 3.610 3.090 2.580 1.510

PM Peak FR WD SC / PM Peak, Freeway Weekday, Traffic Distribution Profile for Severe Congestion 

AM 1.000 0.500 0.500 0.500 0.500 1.500 4.500 6.500 6.000 5.000 5.000 5.500

PM 5.500 5.500 6.500 7.000 7.500 7.500 6.500 5.000 3.500 3.500 3.000 2.000

PM Peak Non-FR WD SC / PM Peak, Non-Freeway Weekday, Traffic Distribution Profile for Severe Congestion

AM 0.990 0.500 0.500 0.500 0.500 1.490 3.470 5.450 5.450 4.950 4.950 5.450

PM 6.440 6.440 6.930 7.430 7.430 7.430 6.440 4.950 4.460 3.470 2.480 1.900

FR WE / Freeway Weekend Traffic Distribution Profile

AM 2.000 1.500 1.000 0.500 0.500 1.000 2.000 3.000 3.500 5.000 5.500 6.500

PM 7.000 7.000 8.000 7.000 7.500 7.000 6.500 5.000 4.500 3.500 3.500 2.500

Non-FR WE / Non- Freeway Weekend Traffic Distribution Profile

AM 1.980 1.490 0.990 0.500 0.500 0.990 1.490 2.480 3.470 4.950 5.940 6.930

PM 7.430 7.430 7.430 7.430 7.430 6.930 5.940 4.950 4.460 3.470 2.970 2.420

FR WD SC SS / Freeway Weekday Traffic Distribution Profile for Severe Congestion and Similar Speeds

AM 1.490 0.990 0.990 0.500 0.500 1.490 5.450 6.930 6.440 5.450 5.450 5.450

PM 5.450 5.940 5.940 6.440 6.930 6.440 5.450 4.460 3.470 3.470 2.970 1.910

Non-FR WD SC SS / Non-Freeway Weekday Traffic Distribution Profile for Severe Congestion and Similar Speeds

AM 1.460 0.980 0.980 0.490 0.980 2.930 5.370 6.340 5.370 4.880 4.880 5.370

PM 5.370 5.370 5.370 5.850 6.340 6.340 5.850 4.880 4.390 4.390 3.410 2.410

Source: TTI’s 2012 Urban Mobility Report, David Schrank, Bill Eisele 

and Tim Lomax, Texas A&M Transportation Institute, Texas A&M 

University System, December 2012 
68  Data and Data Organization GradeDec.Net Reference Manual 

Table 11 Default Values for Diurnal Shares of Highway Traffic in 

Principal Direction at Crossing (Principal Direction of Highway 

Traffic is where the Lower Railroad Milepost is to Highway Vehicle 

Traffic’s Left) 

Traffic Direction (Share of hourly traffic in principal direction in hour)

Name/Description 12 1 2 3 4 5 6 7 8 9 10 11

Balanced / 

AM 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0

PM 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0

AM Peak / AM Peak

AM 50.0 50.0 50.0 50.0 50.0 50.0 60.0 60.0 60.0 60.0 50.0 50.0

PM 50.0 50.0 50.0 50.0 50.0 50.0 40.0 40.0 40.0 40.0 50.0 50.0

PM Peak / PM Peak

AM 50.0 50.0 50.0 50.0 50.0 50.0 40.0 40.0 40.0 40.0 50.0 50.0

PM 50.0 50.0 50.0 50.0 50.0 50.0 60.0 60.0 60.0 60.0 50.0 50.0

Data in table are illustrative, and may or may not be representative of 

traffic direction at a specific crossing 
GradeDec.Net Reference Manual Index  69

Index 

A

AADT 9, 19, 21, 28, 34, 35, 36, 42, 47, 48, 49, 

50, 58, 59, 61

accident rate 14 

alternate case 7, 9, 10, 11, 12, 13, 14, 17, 22, 26, 

27, 37, 38, 39, 40, 43, 45, 48, 49, 50, 56, 

57, 58, 59 

average delay 38 

B

base case 7, 12, 13, 21, 26, 37, 38, 40, 46, 48, 

49, 50, 56, 57 

benefit-cost 1, 2, 3, 12, 45, 51 

summary 12, 45 

benefit-cost ratio 51 

C

capital costs 14, 45, 59 

closure 8, 10, 28, 30, 33, 34, 35, 56, 57 

corridor 1, 2, 3, 7, 8, 9, 10, 12, 13, 14, 17, 20, 

21, 28, 34, 44, 46, 47, 48, 49, 50, 55, 56, 

57, 58, 59, 60, 61, 62 

corridor model 3, 9, 10, 12, 13, 17, 21, 34, 56, 

57, 60 

D

default values 3, 62 

demand 47, 48, 49, 61 

device 8, 27 

discount rate 11, 45, 51, 52, 62 

discounting 2 

distributions 2, 3, 19, 20, 38, 55, 58, 60 

E

economic 1, 44 

elasticity 43, 47, 48, 49, 61 

emissions 1, 7, 28, 39, 40, 49, 62 

F

facility type 20 

FRA 1, 12, 63 

freeflow speed 32 

G

gates 8, 10, 27, 28, 55, 57, 58, 63 

grade crossing 1, 2, 3, 7, 8, 9, 10, 12, 13, 14, 17, 

19, 21, 22, 23, 24, 26, 27, 28, 34, 35, 38, 

39, 40, 41, 43, 44, 46, 47, 50, 55, 57 

grade separation 8, 10, 12, 34, 35, 36, 39, 57 

H

high speed rail 2, 9, 14, 24 

HSR 12, 13, 17, 22, 24, 25, 26, 37, 62 

I

intersection 35, 41, 42, 43, 59 

L

lanes 22, 32, 33 

last year 11, 19, 50 

lifecycle costs 9, 44, 59 

N

net present value 51 

normal 60 

O

operating and maintenance costs 44, 45 

P

parameters 9, 11, 14, 21, 56, 62 

period of analysis 3 

base year 8, 9, 10, 14, 18, 19, 21, 45, 62 

end year 10, 11 

Present Value 51 
70  Index GradeDec.Net Reference Manual 

R

rate of return 1, 4, 51 

region 1, 2, 7, 8, 9, 10, 11, 12, 13, 14, 20, 46, 47, 

48, 49, 50, 56, 57, 58, 59, 60, 61, 62 

regional model 3, 9, 12, 13, 17, 20, 21, 56, 60 

risk analysis 2, 7, 13 

trial 60 

S

safety 1, 3, 7, 12, 13, 20, 26, 28, 33, 37, 44, 45, 

47, 50, 55, 57, 58, 61 

scenario 8, 10, 11, 14, 60 

Signal 14, 41, 43 

Simulation 14, 34, 35, 60 

social costs 14, 61 

start year 10, 11, 59 

T

traffic distributions 9, 14, 20, 55, 58 

traffic management measure 8, 9, 59 

travel time 7, 38, 39, 47, 48, 50, 61 

triangle 60 

U

uniform 20, 55, 58, 60 

user costs 7, 10, 56 

V

vehicle operating costs 1, 7, 11, 28, 61