State-of-the-Art Technologies for

Intrusion and Obstacle Detection for

Railroad Operations

Highway-Rail Grade Crossing Safety Research

U.S. Department

of Transportation

Federal Railroad

Administration

Office of Research

and Development

Washington, DC 20590

DOT/FRA/ORD-07/06

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Final Report

February 2007

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Final Report 

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4. TITLE AND SUBTITLE

State-of-the-Art Technologies for Intrusion and Obstacle Detection for Railroad Operations

6. AUTHOR(S) 

Marco P. daSilva and William Baron

5. FUNDING NUMBERS 

RR97/CB071 

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

U.S. Department of Transportation 

Research and Innovative Technology Administration 

John A. Volpe National Transportation Systems Center 

Cambridge, MA 02140 

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DOT-VNTSC-FRA-07-04 

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Washington, DC 20590 

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Highway-Rail Grade Crossing Safety Research series 

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13. ABSTRACT (Maximum 200 words) 

This report provides an update on the state-of-the-art technologies with intrusion and obstacle detection capabilities for rail rights 

of way (ROW) and crossings. A workshop entitled Intruder and Obstacle Detection Systems (IODS) for Railroads Requirements 

was held in 1998, and the Volpe National Transportation Systems Center published the proceedings in 2001. A suite of possible 

alternative detection technology systems were then field-tested; the results were published in 2003. A host of novel approaches to 

detection involving existing and emerging technologies have since appeared. This report identifies these new non-track circuitbased approaches and methods of identifying obstacles and intruders on the ROW and at crossings. The results obtained from this 

analysis provide a technology update for the Federal Railroad Administration, as well as recommend potential technology concepts 

for future field testing. The application of intrusion and obstacle detection or remote sensing technologies would serve to improve 

the safety of rail passengers and road users, as well as protect the general population and environment from the risks associated 

with hazmat shipments, and aid in the relief of congestion by reducing the number of incidents and delays due to those incidents. 

15. NUMBER OF PAGES 

44

14. SUBJECT TERMS 

Obstacle detection, obstacle intrusion systems, intrusion detection, alternative detection 

technology systems 

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ii 
Acknowledgments 

Under sponsorship from the US DOT Federal Railroad Administration’s (FRA) Office of 

Research and Development, the U.S. DOT Research and Innovative Technology 

Administration’s John A. Volpe National Transportation Systems Center (Volpe Center) 

conducted research into state-of-the-art intrusion and obstacle detection technologies for 

rail applications. The authors of this report are Mr. Marco P. daSilva and Mr. William 

Baron. The authors wish to thank Jim Smailes and Len Allen, Track Safety Research 

Division, and Dr. Magdy El-Sibaie, Acting Director, Office of Research and 

Development, for their guidance and support. 

The authors gratefully acknowledge the overall direction provided by Anya A. Carroll, 

Principal Investigator, Highway-Rail Grade Crossing Safety Research, Volpe Center. 

iii 

Table of Contents 

 

Acknowledgments..............................................................................................................iii 

List of Figures.................................................................................................................... vi 

Executive Summary............................................................................................................ 1 

1. Introduction................................................................................................................. 3 

1.1 Previous Work .................................................................................................... 3 

1.2 Current Effort...................................................................................................... 4 

2. Problem Definition...................................................................................................... 5 

2.1 Problem............................................................................................................... 6 

2.2 Functional Concepts of Intrusion and Obstacle Detection Systems................... 6 

3. Sensor and Platform Technologies ............................................................................. 9 

3.1 Sensor Technologies........................................................................................... 9 

3.2 Studies, Concepts, Prototypes, and Systems..................................................... 10 

4. Reliability and Redundancy Issues........................................................................... 29 

5. Conclusions and Recommendations......................................................................... 31 

References......................................................................................................................... 33 

Acronyms.......................................................................................................................... 37 

v
List of Figures 

Figure 1. IODS Data Flow [1, p.15] .................................................................................. 4 

Figure 2. Highway-Rail Incidents, Injuries, and Fatalities 1994-2004 [5] [6] .................. 5 

Figure 3. Signal-Caused Highway-Rail Incidents 1994-2004 [6] ..................................... 5 

Figure 4. Potential Solutions.............................................................................................. 6 

Figure 5. ITS Architecture: Integration of Railroad and Traffic Management 

Systems [8].......................................................................................................... 7 

Figure 6. Locomotive/Infrastructure Cooperation ............................................................. 7 

Figure 7. Four-Quadrant Gate in Groton, CT [10]........................................................... 10 

Figure 8. Long Island Railroad Intelligent Grade Crossing Variable Message Sign on 

Roadway in New Hyde Park, NY [10] ............................................................. 11 

Figure 9. Pittsford Trespassing Detection System Schematic [11].................................. 11 

Figure 10. Laser Radar System for Obstacle Detection (LaserOptronix) [12]................ 12 

Figure 11. FenceGrabber System (LaserOptronix) [13].................................................. 12 

Figure 12. AWARE Project–Rail CrossingGuard Camera and Train 

Warning System [14] ...................................................................................... 13 

Figure 13. AWARE Project–Web-Based User Interface [14]......................................... 13 

Figure 14. Guideway and Platform Intrusion Detection System [15] ............................. 14 

Figure 15. JR-East Stereo Camera System at Crossing [16] ........................................... 14 

Figure 16. JR-East Stereo Camera System at Train Station Platform [17]...................... 15 

Figure 17. Capsys Product Line Applications [18].......................................................... 15 

Figure 18. Laser Intrusion Detection System Applications [19] ..................................... 16 

Figure 19. PIES System [20] ........................................................................................... 16 

Figure 20. Intelligent Video in MBTA Silver Line Tunnel............................................. 17 

Figure 21. Trespasser Detection (Object Video) [21]...................................................... 17 

Figure 22. San Antonio AWARD System [10] ............................................................... 18 

Figure 23. Active Warning for Low-Volume Highway-Rail Intersections 

(C3 Trans System LLC) [23] .......................................................................... 19 

Figure 24. Minnesota Guidestar In-Vehicle Warning System [10] ................................. 19 

Figure 25. Minnesota Guidestar-Bicycle and Pedestrian Detection [26] ........................ 20 

Figure 26. SAVME Concept [27] .................................................................................... 21 

Figure 27. Guardian Solutions ThreatSTALKER System [28] ....................................... 21 

Figure 28. 4-D Security Solution ELM2107 System [29] ............................................... 22 

Figure 29. Wireless Sensor Network (SAIC) [30]........................................................... 23 

Figure 30. Optical Detection of Obstacles System [32] .................................................. 23 

Figure 31. Railway Electro Optical System [33]............................................................. 24 

Figure 32. Ultrasonic Rail Flaw Sensing Cart [35].......................................................... 25 

Figure 33. URV Concept ................................................................................................. 25 

Figure 34. SAIC Vigilante VTOL UAV [40] .................................................................. 26 

Figure 35. Whirly Bird WB 80 VTOL UAV [41] ........................................................... 27 

Figure 36. MLB Company BAT Mini-UAV [42] ........................................................... 28 

Figure 37. BAI Aerosystems BQM-147 Exdrone UAV [43] .......................................... 28 

vi
Executive Summary 

This report provides an update on state-of-the-art technologies available worldwide with 

intrusion and obstacle detection capabilities for rail rights of way (ROW) and crossings. 

It also attempts to synthesize state-of-the-art research on intrusion and obstacle detection,

as well as catalogue commercial-off-the-shelf (COTS) systems with such detection 

capabilities for railroad operations. 

Several types of non-track circuit-based intrusion and obstacle detection system 

prototypes have been field tested in recent years. These systems incorporate technologies 

such as magnetic, infrared, ultrasonic, and acoustic sensors, as well as radar and video 

detection. Other approaches to detection are also discussed. Some were developed 

specifically for the railroad environment, mainly infrastructure-based and for activecooperation use. Others were developed for other applications, such as perimeter 

security, military reconnaissance, and vehicle detection on roadways. While some 

technologies and systems have been commercially offered and are in operational use, 

many are still either being prototyped or field tested. Most of the systems described in 

this report show promise, but their effectiveness has not yet been properly tested and 

evaluated over the range of operational conditions, especially within the railroad 

environment. 

The ultimate objective is to develop a comprehensive list of existing and potential 

technology solutions that could be considered for use as Intruder and Obstacle Detection 

Systems (IODS) or are capable of performing integral functions within such systems. 

The results are intended to provide a technology update, as well as to recommend 

potential technology concepts for future field testing. Next steps include an evaluation of 

the promising technologies that are currently ready for use in obstacle detection 

applications and identification of the technologies that require further refinement before 

they can be relied upon to ensure public safety. 

1 

1. Introduction

Railroads have continuously struggled with the issue of trespassing on the ROW and 

blocked railroad crossings, which can lead to very serious incidents. These can be 

intentional, such as destruction of track infrastructure and/or signaling equipment or 

attempted suicide. They can also inadvertently occur, such as a vehicle stalled at a 

crossing, failure of the motor vehicle operator to observe warning signals, cargo dropped 

from a truck, or signal equipment malfunction. Most incidents have been highly 

publicized due to the nature of the results (derailment, hazardous material spillage, nonfatal or fatal injuries). Although some types of incidents have been on a decrease, a need 

still exists for better monitoring of crossings, as well as of other high-risk rail assets, such 

as bridges and tunnels. The risk of terrorist activity on U.S. soil also presents a danger to 

rail assets, especially to passenger service and rail equipment carrying hazmat. 

The use of high-speed trains has also been increasing, especially along certain corridors 

recently given infrastructure upgrades. This, along with an increase of railroad freight 

shipments, makes the rail network operate at continuously higher loads and increases the 

exposure factor of the system (more trains and higher speeds but same amount of track). 

These developments emphasize the need for automatic continuous monitoring of the rail 

network with the capability of notifying the train operator and/or railroad dispatcher of 

any impending danger or of automatically controlling the locomotive. The concept of 

positive train control (PTC) is an integral component of safety enhancements for the 

railroad. PTC systems are “integrated command, control, communications, and 

information systems for controlling train movements with safety, security, precision, and 

efficiency” [3]. PTC has the potential to be deployed across the rail industry, which uses 

about 21,000 locomotives across the country. 

1.1 Previous Work 

A national workshop entitled, “Intruder and Obstacle Detection Systems (IODS) for 

Railroads Requirements,” held at the John A. Volpe National Transportation Systems 

Center (Volpe Center) in 1998 under the sponsorship of the Federal Railroad 

Administration (FRA) [1] assembled a representative set of researchers and rail industry 

representatives to brainstorm possible IODS requirements and constraints. One of the 

central findings was that efforts should be concentrated on highway-rail grade crossing 

safety over ROW safety, since most high severity incidents occur at crossings. 

Requirements ranged from accurate detection and timely communication to reliability 

and redundancy. Another result from the workshop was the creation of the IODS 

operation process flow, as shown in Figure 1 [1, p. 15]. The present effort detailed in this 

report focuses on the “sensing” component of Figure 1, namely providing an update on 

the evolution of relevant monitoring platforms and technologies. 

3 
Figure 1. IODS Data Flow [1, p.15] 

Following the guidelines set forth in the IODS Workshop, FRA tasked the Volpe Center 

and the Transportation Technology Center, Inc. to evaluate available technologies for 

their “ability to detect trains and/or highway vehicles approaching and occupying 

highway rail intersections” [2, p. V]. A report entitled, Evaluation of Alternative 

Detection Technologies for Trains and Highway Vehicles at Highway Rail Intersections, 

Federal Railroad Administration Office of Research and Development, outlines the 

findings of this effort [2]. Five systems were selected for testing of their performance on 

successful/missed detection, critical failures, and nuisance/false alarms. The technologies 

used included magnetic, ultrasonic, laser, infrared, vibration, wheel axle counters, and 

video imaging. The results from some systems were encouraging while others did not 

fare well in detecting trains and/or vehicles. The mixed results were attributed not only 

to the sensing packages but also to sensor placement. 

1.2 Current Effort 

As in the above study, several types of non-track circuit-based intrusion and obstacle 

detection prototypes have been field tested in recent years. These systems incorporate 

technologies, such as magnetic, infrared, ultrasonic, and acoustic sensors, as well as radar 

and video detection. This report attempts to synthesize state-of-the-art research on 

obstacle and intrusion detection, as well as catalogue COTS systems available for these 

applications. The report also discusses other approaches to detection. The ultimate 

objective is to develop a comprehensive list of existing and potential technology solutions 

that could be considered for use as IODS or capable of performing integral functions 

within such systems. 

4
2. Problem Definition

Highway-rail and trespass incidents have experienced a downward trend over the past 

decade, as shown in Figure 2. About 1 vehicle/train collision occurs every 90 minutes, 

amounting to approximately 3,000 per year [4]. Over 250,000 crossings currently exist 

across the United States, including almost 100,000 private crossings [5]. Two basic types 

of warning devices are at crossings: passive and active. Most of these crossings make 

use of passive warning devices, such as crossbucks and pavement markings, meaning no 

active gates and/or flashing lights warn motorists of an oncoming train. Overall, only 26 

percent of all grade crossings have active warning devices with either flashing lights or 

lights and gates, which are inherently dependent on train activity [7]. These systems do 

sometimes malfunction, however, and are a contributing factor to a small but increasing 

number of highway-rail incidents, as detailed in a report entitled Railroad Safety 

Statistics–Interim Report 2003 [6] and shown in Figure 3. 

0

1,000

2,000

3,000

4,000

5,000

6,000

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Year

Number

Incidents

Injuries

Fatalities

Figure 2. Highway-Rail and Trespass Incidents, Injuries, and Fatalities 1994-2004 

[5] [6] 

0

10

20

30

40

50

60

70

80

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003

Year

Number

Figure 3. Signal-Malfunction Highway-Rail Incidents 1994-2004 [6] 

5
Obstacle and intrusion detection would provide great benefits at passive and active 

crossings, as well as for the overall railroad ROW. 

 

2.1 Problem 

This report focuses on two general railroad problem areas: crossings and the ROW. The 

application of obstacle and intrusion detection or remote sensing technologies would 

serve to improve the safety of the rail passengers and road users, as well as protect the 

general population and environment from the risks associated with hazmat shipments, 

and aid in the relief of congestion by reducing the number of incidents and delays due to 

those incidents. Of particular concern in the post-9/11 environment, although no clear 

indication exists that terrorists plan to attack U.S. railroads or shipments, the expansive 

nature of the railroad infrastructure makes it extremely vulnerable to such actions. 

2.2 Functional Concepts of Intrusion and Obstacle Detection Systems 

Figure 4 provides a three-dimensional graphical layout that displays problem areas, 

situational applications, and device-type solutions. Three types of technology platforms 

are applicable to the problem area and application pairs, as depicted in Figure 4, 

infrastructure-based with communication to the locomotive, infrastructure/locomotive 

cooperation, and locomotive-based. 

Application

Device

Hazmat

People

Problem Areas

Crossings

ROW

Locomotive-based

Infrastructure-based

Infrastructure/Locomotive Cooperation

Application

Device

Hazmat

People

Locomotive-based

Infrastructure-based

Infrastructure/Locomotive Cooperation

Crossings

ROW

Figure 4. Potential Solutions 

Infrastructure-based systems depend on active cooperation between wayside-mounted 

sensory equipment and warning devices on the train. This approach has been the focus of 

most research into the subject, especially since the introduction of the Intelligent 

Transportation Systems (ITS) framework. It maximizes the use of PTC by providing 

wireless communication from the wayside sensory package to the train cab, warning the 

locomotive engineer of obstacles or trapped vehicles at grade crossings and of trespassers 

6
along the ROW [8]. This architecture provides for the integration of railroad and traffic 

management systems, as shown in Figure 5. 

Figure 5. ITS Architecture: Integration of Railroad and Traffic Management 

Systems [8] 

Other types of systems use passive cooperation between train-mounted sensors and 

markers, or reflectors, along the rail route, as displayed in Figure 6. Such systems rely on 

train-mounted sensors, such as radar or laser, and reflectors along the route. Detecting 

the reflectors indicates a clear path, while a loss of line-of-sight to the reflectors indicates 

the presence of an obstacle on the ROW. This concept relies on real-time global 

positioning system (GPS) train position data, as well as the location of each reflector 

overlaid on a geographic information system (GIS) map. Reflectors would have to be 

placed in such a manner as to give the train the maximum distance possible to slow down 

and possibly stop. A clear problem with this concept is how to compensate for curves 

and grade changes along the rail infrastructure. As described in a subsequent section, 

however, a prototype system using this approach shows potential in overcoming these 

challenges. 

Train

Figure 6. Locomotive/Infrastructure Cooperation 

Locomotive-based systems are those mounted on rail vehicles only. The main advantage 

to these systems is that installation is confined to the number of locomotives in service 

and not the number of crossings, thus considerably reducing the number of these systems 

7
while providing 100 percent route coverage. Another advantage of train-borne sensor 

technology is that system failures are more easily detected since the equipment resides 

entirely in the locomotive’s cab. In addition, repairs can be done quickly since 

locomotives undergo regular maintenance at rail yards. 

8
3. Sensor and Platform Technologies 

A wide array of sensor systems are used throughout the transportation industry and other 

arenas both within the United States and in other parts of the world. Some were 

developed specifically for the railroad environment, mainly infrastructure-based and for 

active-cooperation with the locomotive. Others were developed for other applications, 

primarily for vehicle detection on highways and at intersections, perimeter security, and 

other military applications. This chapter discusses not only the technologies in use but 

also integrated sensor systems that have been developed and tested in real-world 

situations. Specific strengths and weaknesses of each system will not be addressed, 

although many other research efforts have documented such findings [9]. 

3.1 Sensor Technologies 

Two general types of sensors exist, intrusive and non-intrusive. Intrusive sensors refer to 

the types that are installed on or under the road/rail surface, usually impacting the flow of 

traffic during installation and maintenance. These include inductive loops, pneumatic 

road tubes, magnetometers, piezoelectric cables, and others. Most of these sensors are 

used in vehicle detection applications, such as acquiring traffic count data, controlling 

traffic signals, or opening parking lot gates. Inductive loops are used in four-quadrant 

gate systems at railroad crossings to identify vehicles trapped between the gates and 

signal the exit gate to open so the vehicle can clear the crossing. Intrusive sensors tend to 

be comprised of low-tech hardware and therefore usually cost less to purchase but cost 

more to install. Non-intrusive sensors refer to the types that are installed above ground 

and with minimal traffic disruption during installation and maintenance. Converse to 

intrusive sensors, these are typically more expensive to acquire and maintain but cheaper 

to install. Non-intrusive sensors include radar, infrared, acoustic, ultrasonic, video, and 

combinations of these technologies. 

The following lists technology concepts currently used throughout the transportation and 

security industries in obstacle and intrusion detection. Appendix F of the Intruder and 

Obstacle Detection Systems (IODS) for Railroads–1998 Requirements Workshop 

explains these technologies in more detail [1]. 

• Radar 

• Laser 

• Infrared 

• Ultrasonic 

• Microwave 

• Magnetic 

• Ported Coaxial 

• Video Motion 

• Seismic 

• Fiber Optic 

• Photoelectric Beam 

• Perimeter Fence with Intrusion Sensors 

9
• Inductive Loops 

• Piezoelectric Cables 

• Pneumatic Tubes 

3.2 Studies, Concepts, Prototypes, and Systems 

Numerous prototypes, as well as fully operational intrusion and obstacle detection 

systems, have been deployed in recent years. Various technologies have been used 

ranging from laser radar to infrared, Doppler radar, and intelligent video. The following 

describes each of these systems. 

3.2.1 Infrastructure-Based

Infrastructure-based systems depend on active cooperation between sensory equipment 

mounted along the ROW and train-borne warning devices. 

Four-Quadrant Gate with Obstacle Detection and Train Control, Groton, CT (1999-

2000) [10]. A four-quadrant gate tested on an Amtrak line in Connecticut, as shown in 

Figure 7, incorporated inductive loops within the crossing to detect any vehicle that 

became stranded within this zone when the gates came down. This system also 

interfaced with the in-cab signaling system of the locomotive on approach and notified 

the train engineer to stop the train if the crossing was obstructed. The PTC function of 

this system also had the ability to automatically stop the train, if necessary.

Figure 7. Four-Quadrant Gate in Groton, CT [10]

Long Island Railroad Intelligent Grade Crossing, New Hyde Park, NY (2001) [10]. This 

demonstration project focused on providing train information to drivers by way of 

variable message signs on the roadway (Figure 8). The system also provided for stalled 

vehicle detection by use of in-ground loop detectors and video imagery. A signal sent to 

the train engineer if the crossing was blocked enabled the engineer to slow the train as 

much as possible before reaching the crossing. 

10
Figure 8. Long Island Railroad Intelligent Grade Crossing Variable Message Sign 

on Roadway in New Hyde Park, NY [10] 

Intrusion Detection System, Pittsford, NY (2001-2004) [11]. An automated prototype 

railroad infrastructure security system was demonstrated on a railroad bridge in Pittsford, 

NY, where trespassing had become a safety issue. This COTS technology system 

consists of video cameras, motion detectors (stereo Doppler microwave and passive 

infrared), infrared illuminators, speakers, and central processing units (Figure 9). It has 

the capability of detecting trespass events when an intrusion occurs on the railroad ROW. 

Once triggered, the system sends audible and visual signals to a monitoring workstation 

at the local security company. An attendant at the security company then validates the 

alarm by viewing the live images from the scene, issues a real-time warning to the 

trespasser(s) via pole-mounted speakers near the bridge, and calls the local police and the 

railroad police, if necessary. This system has been in operation for over 3 years and has 

been credited with potentially saving the lives of four people who were warned off the 

bridge within moments of a train arrival. (This system detected the trespassing event 

shown in the picture on the cover of this report.) 

 

Data

Legend

Camera Speaker Motion

Detector

Pole-Mounted

Computer

Phone Line

for Voice, Video,

or Data

Schematic not to scale.

110 VAC

Video Data Voice

110 VAC

Bridge Deck

Magnetometer Power

Supply

Power

Meter and

Breakers

Data

Figure 9. Pittsford Trespassing Detection System Schematic [11] 

11
Laser Radar System for Obstacle Detection, Åkersberga, Sweden (2001-2003) [12]. A 

laser radar system, more commonly referred to as LADAR (LAser Detection and Range), 

has been developed by a Swedish company called LaserOptronix and installed on a single 

line crossing in the town of Åkersberga, Sweden. This system, named LaserGrab, can 

detect obstacles at distances greater than 100 meters and can accommodate a picture or 

video camera with outputs for wireless image transmission to an oncoming locomotive. 

It also has the capability of distinguishing between vehicles and smaller targets, such as 

pedestrians. Figure 10 shows a picture of the LADAR scanner mounted on a pole, as 

well as a diagram of the installation layout at the crossing. 

Figure 10. Laser Radar System for Obstacle Detection (LaserOptronix) [12] 

LaserOptronix also markets another system aimed at creating virtual fences using lasers 

called FenceGrabber (see Figure 11) [13] which is used for protecting fences from 

intruders or where no mechanical protection can be provided, such as over water or 

swamps. This system generates an alarm when any of the sensor’s laser beams are 

tripped. A video camera system can be connected to the FenceGrabber system and relay 

digital imagery along with the alarm signal to a monitoring station. The maximum range 

of an individual system is 200 meters. 

Figure 11. FenceGrabber System (LaserOptronix) [13] 

12
Florida Department of Transportation (DOT) Advanced Warning Alerts for Railroad 

Engineers (AWARE) Pilot Project, USA (2001-2002) [14]. Nestor Traffic Systems 

conducted the AWARE Project for the Florida DOT. This project combined Nestor’s 

Rail CrossingGuard automated video monitoring system with a GPS-based train location 

and communication system called TrainTrac from GeoFocus, LLC. This combination 

allowed for real-time communication between monitoring equipment at the crossing and 

an informational system on board specially equipped trains. This proof-of-concept 

demonstration consisted of testing the AWARE system at two crossings equipped with 

Nestor’s Rail CrossingGuard system and two trains equipped with mobile information 

terminals (Figure 12). A Web-based user interface was developed, and a central 

monitoring station was set up to receive all information relayed to and from the trains. 

Figure 13 shows a screenshot of the user interface. This project focused on vehicle 

signal/gate violation detection. Although it may be possible to configure the Rail 

CrossingGuard system for pedestrian intrusion and obstacle (other than vehicles) 

detection capability, the AWARE Pilot Project did not address these issues. 

Figure 12. AWARE Project–Rail CrossingGuard Camera and Train Warning 

System [14] 

Figure 13. AWARE Project–Web-Based User Interface [14] 

13
Guideway and Platform Intrusion Detection System (GPIDS), Singapore (2001-Present) 

[15]. The Nanyang Technological University (NTU) and the Singapore Light Rail 

Transit (SLRT) Agency have jointly developed GPIDS using LaserGrab technology [12]. 

The system was developed for guideway intrusion detection along light rail platforms, 

namely people jumping down or throwing objects from the platforms and onto the tracks. 

Demonstrated at SLRT Bukit Panjang underground station in Singapore (Figure 14), it 

has proved successful in detecting people, animals, and objects on the guideway. Upon 

alarm activation, the system sounds an audible warning at the platform and sends a signal 

along with video imagery to the light rail operations control center. 

Figure 14. Guideway and Platform Intrusion Detection System [15] 

East Japan Railway Company (JR-East) [16, 17]. JR-East is currently developing and 

testing obstacle detectors at crossings and tracks adjacent to station platforms. The 

detectors, intended to be low cost, use stereo image processing to detect intrusion onto 

the ROW. Stereo cameras are used to minimize the effect of shadows and train lights on 

the system [17]. The platform intrusion detection system became operational in July 

2004. Although the crossing system has not yet been directly tied to train operations, JREast is presently conducting research into relaying real-time intrusion information from 

vehicles violating the crossing to the train. Figure 15 shows the stereo camera system 

installed at a railroad crossing. Figure 16 illustrates the same concept for ROW 

monitoring at train station platforms. 

Figure 15. JR-East Stereo Camera System at Crossing [16] 

14
Figure 16. JR-East Stereo Camera System at Train Station Platform [17] 

Capsys, France [18]. Capsys is a French company specializing in vehicle and pedestrian 

detection systems for a wide range of transportation applications. This company has 

developed a wide range of sensors using video sensing, microwave and Doppler radar, 

infrared, and magnetic induction. Capsys also developed a high-frequency wireless link 

using an active radio antenna at the monitored location and a user interface box up to 400 

meters away. Figure 17 shows an example of the application of their product line. 

Although shown at a vehicular intersection, these sensors could be deployed at highwayrail crossing locations to monitor vehicles and pedestrians intruding on the ROW and 

send an alarm wirelessly to an in-cab warning system on board the train. 

Figure 17. Capsys Product Line Applications [18] 

Molinari & Associates, Canada [19]. This Canadian company has developed a Laser 

Intrusion Detection System (LIDS) to use mainly at tunnel entrances and station 

platforms. This laser-based system can recognize train profiles and therefore mask them 

out when they cross the detection zone. The main advantage of this technology, as 

determined by the use of major rail transit operators, is the elimination of false and 

15
nuisance alarms while maintaining 100 percent intrusion detection capability. Figure 18 

shows the laser assembly mounted at a tunnel entrance and by a railroad crossing. 

Figure 18. Laser Intrusion Detection System Applications [19] 

Alpha Zaicon Technology Inc.’s Platform Intrusion Emergency Stop System (PIES),

Canada [20]. This rail level system is composed of sensor panels installed in a series of 

continuous rows in between and along the side of the rails, as indicated by the yellow 

arrows in Figure 19. The system uses these sensor panels to detect intrusions onto the 

rail space and automatically sends a stop signal to the approaching train. The Kuala 

Lumpur Putra Light Rail Transit system uses this technology as part of its GPIDS system. 

Figure 19. PIES System [20] 

Intelligent Video Systems [21]. One of the most promising emerging technologies is 

commonly referred to as intelligent video. Several manufacturers of this equipment offer 

commercial products that purport to be effective in obstacle detection applications. 

These vendors include Object Video, Northrup-Grumman, VistaScape, and Sarnoff. The 

Massachusetts Bay Transportation Authority (MBTA) installed a system using Object 

16
Video equipment to detect trespassers entering the ROW in their new Silver Line Bus 

Rapid Transit (BRT) dedicated tunnel, as shown in Figure 20. This system is designed 

not to alarm when MBTA vehicles are detected, but the alarm will activate for most other 

objects in the predefined detection zones. 

Detection Zones 

Figure 20. Intelligent Video in MBTA Silver Line Tunnel 

One of the reasons intelligent video (sometimes referred to as behavioral video) shows so 

much promise is that it can be configured to detect a variety of real-world anomalies, 

such as traffic delays, stalled vehicles, U-turns, and changes in direction. Unlike 

traditional video detection systems, these systems can be programmed so that alarms are 

not generated unless specific behavioral patterns are exhibited. This technology can also 

have applications for the security of stations, platforms, and infrastructure. Figure 21 

shows an example of a railroad ROW installation. 

Figure 21. Trespasser Detection (Object Video) [21] 

17
The following integrated systems were not developed exclusively for intrusion or 

obstacle detection. These systems are listed herein because they either contain relevant 

components or are expandable and could be reconfigured for intrusion and obstacle 

applications. 

San Antonio Advanced Warning to Avoid Railroad Delay (AWARD) System (1998-

Present ) [10]. The Texas DOT tested a train detection system using radar speed guns 

and acoustic sensors, as shown in Figure 22. This system provided information on the 

presence, speed, and length of trains that was then used to calculate delays to motorists at 

crossings. This information was relayed to variable message signs along the roadway so 

that motorists could choose alternative routes to avoid a blocked crossing. 

Figure 22. San Antonio AWARD System [10] 

Minnesota Guidestar [22]: The Minnesota DOT ITS program, called Minnesota 

Guidestar, has conducted various research projects and system field tests for rural lowvolume grade crossings, as well as for vehicle and pedestrian detection. The following 

lists the projects most relevant to intrusion and obstacle detection: 

• Low-Cost Active Warning for Low-Volume Highway-Rail Intersections, MN and 

SD (2002-Present) [23]. C3 Trans System LLC has developed a low-cost grade 

crossing active warning system for low-volume crossings (Figure 23). This 

system converts passive crossings to active ones by using radio communications 

between the locomotive and the solar-powered warning system at the crossing. It 

has the ability to relay diagnostic information from the crossing back to the train 

and provide the train engineer with defective crossing information up to 1 mile 

upstream of the crossing. Although this system does not provide for intrusion or 

obstacle detection, the configuration allows for the addition of sensors at the 

crossing and communication of events to the train. 

18
Figure 23. Active Warning for Low-Volume Highway-Rail Intersections (C3 Trans 

System LLC) [23] 

• In-Vehicle Warning with Passive Train Detection System (1998) [10]. This test 

included equipping school buses with a warning display unit that would be 

activated if the bus was in the vicinity of the crossing and a train was approaching 

(Figure 24). The system would activate when the Head-of-Train (HOT) internal 

radio frequency communication on board the train was detected [24]. Most 

freight railroads use HOT to coordinate the train’s front and rear braking. This 

existing technology could be exploited further as a component of a wayside-based 

obstacle detection system.

Figure 24. Minnesota Guidestar In-Vehicle Warning System [10]

• Field Test of Monitoring of Urban Vehicle Operations Using Non-Intrusive 

Technologies (1995-1997) [25]. This involved a 2-year test of available non19
intrusive traffic detection technologies for motor vehicle detection. The systems 

tested utilized magnetic, sonic, ultrasonic, microwave, radar, infrared, and video 

technologies. They were evaluated in a variety of traffic and environmental 

conditions. The final report [25] details the observed strengths and weaknesses of 

each technology at highway and intersection test locations. This study also 

included research into bicycle and pedestrian detection using non-intrusive 

technologies [26]. Various technologies were tested, and the results provided 

good insight into the performance of the sensors. Figure 25 shows one type of 

sensor mounting configuration. 

Figure 25. Minnesota Guidestar-Bicycle and Pedestrian Detection [26] 

System for Assessing the Vehicle Motion Environment (SAVME) (1989-Present) [27]. 

SAVME is an infrastructure-based system that gathers information about vehicle 

kinematic interaction and traffic flow at specific roadway locations using overhead 

imaging sensors (video cameras). This system, developed in cooperation with the 

University of Michigan Transportation Research Institute and the U.S. DOT National 

Highway Traffic Safety Administration, gathers data on how people drive in varying 

traffic conditions and roadway geometries. It is a type of portable surveillance system 

using digital video cameras mounted on multiple portable towers to detect and track 

vehicles on the roadway, as shown in Figure 26. It is envisioned that a similar system 

will be an integral component to an in-vehicle intersection collision warning system. 

Although not specifically designed for railroad applications, this system could be 

modified for train and vehicle detection. It could potentially be used to detect oncoming 

trains and/or vehicles approaching or occupying the crossing. 

20
SAVME 

Camera 1

H

SAVME 

Camera 2

DSRC -

Controller SAVME 

Camera 1

H

DSRC -

Controller SAVME 

Camera 2

Figure 26. SAVME Concept [27] 

Guardian Solutions [28]. Guardian Solutions has created a product line of automated 

video surveillance systems primarily for perimeter security applications. One such 

portable system is called the ThreatSTALKER and consists of a tripod-mounted video 

camera with infrared illumination and associated video processor, power supply, and 

wireless communication equipment, as shown in Figure 27. Such a system could be 

adapted for monitoring rail crossings and sending wireless signals to a receiver on board 

the train. 

Figure 27. Guardian Solutions ThreatSTALKER System [28] 

4-D Security Solutions, Inc. [29]. This Division of Sentry Technology Group is an 

integrator of security systems focusing primarily on government customers. One of their 

sensor systems, named ELM2107, uses a high-resolution Doppler radar to automatically 

21
detect moving objects and persons within a pre-defined zone. As shown in Figure 28, 

multiple systems can be daisy-chained to provide continuous coverage over a large area. 

This company is also working on a system called Linear Sentry. Although little 

information is readily available, this is supposed to be a locomotive-based optical system, 

making it very similar to the Railway Electro Optical System for Safe Transportation 

(REOST) system discussed in a subsequent section of this report. 

Figure 28. 4-D Security Solution ELM2107 System [29] 

3.2.2 Infrastructure/Locomotive Cooperation 

These systems use passive cooperation between train-mounted sensors, such as radar or 

laser and markers or reflectors along the route. 

Wireless Sensor Networks [30]. As a new approach initially developed for border and 

perimeter security, this system uses low-power wireless sensor networks to detect, locate,

and characterize vehicles and people on the railroad ROW. Science Applications 

International Corporation (SAIC), along with Dust Networks, has created such a network 

system with many sensor options (seismic, acoustic, magnetic, passive infrared, and 

video). This approach utilizes a mesh of wireless sensors deployed along the area to be 

monitored, as seen in Figure 29. A system gateway collects all signals from the network 

and relays them to a base station, which could be a control center or a computer on board 

a locomotive. 

22
Figure 29. Wireless Sensor Network (SAIC) [30] 

Optical Detection of Obstacles (ODO) System [31]. Aspen Systems, Inc. has developed a 

system using fiber optic-relayed laser radar that is capable of detecting obstacles off the 

line of sight (around curves or hills). As shown in Figure 30, the locomotive-born 

transceiver emits a laser pulse that is relayed by a wayside input coupler to an output 

coupler a few miles downstream to the area being monitored. The signal is then bounced 

off a retroreflector across the track to detect any obstacles and returned to the transceiver 

via the couplers. A break in the signal indicates the presence of an obstacle. The 

company claims zero false alarm rate and total obstacle detection [32]. 

Figure 30. Optical Detection of Obstacles System [32] 

3.2.3 Locomotive-Based 

Locomotive-based systems are those mounted on rail vehicles only and those that do not 

interact with any wayside equipment. 

Railway Electro Optical System for Safe Transportation, Israel (REOST) (1998-Present) 

[33]. This ongoing project, funded by the European Union under the Information Society 

Technologies Program, focuses on the use of locomotive-based sensors to detect 

obstacles on the railroad track. Numerous difficulties have affected the project, from 

bankruptcy of project partners to contract negotiations and scope changes [34]. Various 

prototypes have been constructed and field-tested on Israeli Railways locomotives, as 

23
shown in Figure 31. The major sensing components are optical cameras mounted in a 

specially built housing on top of the locomotive. 

Figure 31. Railway Electro Optical System [33] 

Unmanned Vehicles. Recent advances in miniaturization of components and autonomous 

guidance system have made unmanned vehicles a very attractive alternative for 

dangerous applications, such as bomb disposal, military reconnaissance, and aerial 

surveying. The U.S. military, as well as many other entities, has invested billions of 

dollars in this field, resulting in a variety of vehicle platforms that are either being 

developed or are already in production. Two types of these autonomous vehicles could 

be used as platforms for intrusion and obstacle detection along the ROW: Unmanned 

Rail Vehicles (URVs) and Unmanned Aerial Vehicles (UAVs). 

URVs. These autonomous or remote-controlled rail-based platforms have yet to 

be developed but could be composed of video-based sensing and wireless 

communication equipment mounted on a small rail vehicle. This platform would 

be self-powered and provide a base for various sensors, including video imaging 

and GPS, and would provide a wireless data link to a display system on the 

locomotive. Similar systems already exist for the purpose of track inspection, 

such as the ultrasonic rail flaw-sensing cart shown in Figure 32. A URV would 

travel slightly ahead of a train, allowing for a velocity-based temporal safety gap 

between them. It would provide real-time intrusion and obstacle detection along 

the ROW and at crossings, and the URV would relay that information via a 

wireless connection to the train trailing it, as shown in Figure 33. The URV 

would also have the capability to come to a full stop in a short distance, in case an 

obstacle was detected. This concept would provide all-around detection 

capability along the entire rail network. In addition, it could be used along higher 

risk routes only, for higher risk shipments, such as Hazmat or nuclear material, or 

for situations where a specific threat was received by the authorities. There are, 

however, major concerns with the URV concept. These concerns include the 

possible reduction of the rail lines’ capacity and greater driver delay at crossings. 

24
Figure 32. Ultrasonic Rail Flaw Sensing Cart [35] 

Train

Obstacle

URV

Figure 33. URV Concept 

UAVs. These remote-controlled aerial platforms were first developed for military 

applications, such as surveying dangerous locations without putting pilots at risk. 

These systems have come a long way and are being adapted for commercial 

applications, such as aerial photography, traffic surveillance, and land surveying. 

Currently, over 50 entities work on UAVs, and dozens of models are already in 

use by both military and civilian customers. Although some of these remotesensing platforms can be quite costly, the price is constantly decreasing, and 

miniaturization of components means ever increasing functionality. 

The Department of Homeland Security (DHS) has identified four missions that it wants 

addressed by UAVs: border protection, critical infrastructure monitoring support (such 

as pipeline monitoring), transportation security (such as Hazmat shipment monitoring 

over railways, bridges, and tunnels), and maritime support [36]. DHS has specifically 

pointed to the use of these systems for Hazmat shipment protection along the Nation’s 

railways and is currently using a fleet of UAVs to patrol the Mexican border. Although 

no known project is currently testing the use of these systems to protect the railroad 

ROW, the U.S. DOT has sponsored a demonstration of this technology for traffic 

monitoring and DHS [37]. Specifically, Bridgewater State College tested a small camera 

and GPS-equipped UAV that demonstrated its aerial surveying capacity, as well as roadfollowing and vehicle-following capabilities [38]. Railway-protecting UAVs could 

operate autonomously using GPS/GIS information to navigate along a segment of 

25
railroad track ahead of the train and relay sensory information back to a locomotivemounted display system and/or a ground station. Like the URV concept mentioned 

earlier, this approach would provide all-around detection capability along the entire rail 

network, except for the inside of tunnels. Since the track would not be used, however, 

this system would not increase delay to motorists at crossing locations. In addition, it 

could be reserved for selected higher risk routes or for higher risk shipments, such as 

Hazmat or nuclear material. 

A substantial number of companies are developing a variety of UAV systems for tactical 

applications, mostly for the U.S. military. SPAWAR Systems Center of San Diego, CA, 

maintains a database of previous research and current products in this field [39]. Two 

basic types of UAVs exist, ones that take off and land like conventional airplanes and 

ones that fly similarly to helicopters and described as Vertical Take-Off and Landing 

(VTOL) UAVs. Two approaches for use of these drone systems exist, having them be 

locomotive-based or operating from bases throughout the rail network. Many systems 

have a range of hundreds of miles and are configured to carry wireless equipment, such 

as video cameras and other sensors. Although a VTOL-type system could present an 

easier challenge, both VOTL and airplane-type UAVs could potentially be configured to 

use the locomotive or a specially modified railcar as a base, thus making it a locomotivebased system. Such a platform would thus be envisioned to be battery-operated, so that 

no danger would be present by the use of flammable fuel near the train. Since some 

systems have a range of hundreds of miles, they would only need to return to the moving 

base periodically, if at all, during the period of train movement. A UAV for this 

application could also be designed to use solar power to recharge its batteries. Below is a 

sample of existing VTOL, or rotor-winged, UAV systems: 

• SAIC Vigilante [40]. This in-production unmanned aerial system looks just like a 

helicopter (Figure 34). It costs approximately $350,000 and is currently in service 

with the U.S. military. 

Figure 34. SAIC Vigilante VTOL UAV [40] 

• Whirly Bird LLC Whirly Bird WB80 [41]. Whirly Bird LLC focuses on providing 

close range light aerial filming systems. The WB80 has a range of almost 500 

26
miles and cruises at 62 mph, with maximum speed of 75 mph. The autonomous 

flight system consists of a flight control processor with a built-in embedded 

computer system, a GPS receiver, and a general-purpose input/output interface 

that allows control of custom payload equipment, such as video cameras. Figure 

35 shows the WB80 model. The picture on the right shows the WB80 outfitted 

with an aerial video camera enclosure. 

Figure 35. Whirly Bird WB 80 VTOL UAV [41] 

Non-VTOL UAVs are much more common and usually cheaper since they do not require 

the extra engineering associated with VTOL. The U.S. military’s Predator drone aircraft 

is perhaps the most famous of all. This multimillion dollar UAV can be configured in a 

multitude of ways, including the addition of missiles to actively engage targets. On a 

much smaller scale, other UAVs have been developed for civilian applications. Most 

non-VTOL UAVs are either catapulted into the air or use a flat surface to take off and 

land. These systems tend to be relatively inexpensive but are usually land-based. So, a 

network of bases would have to be constructed to accommodate this type of detection 

platform, or they would have to be reconfigured to be able to be launched and retrieved 

from a moving vehicle (train). The following describes two examples of this type of 

UAV: 

• MLB Company BAT Mini-UAV [42]. This small production UAV comes 

equipped with a portable ground station, as seen in Figure 36. It is launched via a 

rail system and lands on a small strip of land. A flight path is programmed into 

the flight control system, and the portable control station receives the live video 

imagery. It has road- or convoy-following capability and has an endurance of up 

to 6 hours or 200 miles. The complete system costs approximately $42,000. 

27
Figure 36. MLB Company BAT Mini-UAV [42] 

• BAI Aerosystems BQM-147 Exdrone [43]. The BAI Aerosystems BQM-147 

Exdrone is a very small and inexpensive UAV, at about $5,000 each. Initially 

developed about 20 years ago and used by the U.S. military, this vehicle is usually 

launched by a rail system and can be caught by a recovery net. It has a range of 

over 200 miles with an optional auxiliary fuel tank. Multiple Exdrones could be 

carried on board a train, and each could be launched after the previous one landed 

on a recovery net on the train, thus providing continuous coverage over the entire 

trip. Figure 37 shows an Exdrone taking flight. 

Figure 37. BAI Aerosystems BQM-147 Exdrone UAV [43]

28
4. Reliability and Redundancy Issues 

Since any type of railway incident has the capability of being catastrophic in terms of 

safety and security, every type of IODS must have a high degree of reliability, meaning a 

very low probability of failure. Detection platforms could include backup or redundant 

components, such as an extra camera or sensor, which could be temporarily used in case 

the primary sensing component fails. This, along with the use of high quality devices 

already proven in operational situations, will increase the system’s reliability. 

Taking into account the typical severity of rail incidents and the high risk of terrorist 

attacks on the Nation’s infrastructure, each system would have to be designed to be 

failsafe. This means that if any component of the system experiences a possible failure, 

the appropriate warnings are transmitted to the oncoming train. Self-diagnostic routines 

have to be incorporated into these systems, periodically checking all sensory and 

communication components for failures and relaying any failure information to the 

appropriate channels (train, wayside warning system, and/or control center). 

Operation and maintenance plans would also have to be developed for each IODS. 

Protocols must be developed to address the range of operational situations, ranging from 

the positive detection of intruders or obstacles on the ROW to false detection or failure of 

the warning system. A playbook of protocols covering all possible situations must be in 

place so that the train engineer and any other designated authority initiate the correct 

emergency action. 

29
30
5. Conclusions and Recommendations 

This report provides an update on the state-of-the-art technologies with intrusion and 

obstacle detection capabilities for rail crossings and ROW. The application of intrusion 

and obstacle detection or remote sensing technologies would serve to improve the safety 

of the rail passengers and road users, as well as protect the general population and 

environment from the risks associated with hazmat shipments, and aid in the relief of 

congestion by reducing the number of incidents and delays due to those incidents. The 

report lists non-track circuit-based approaches and methods of identifying obstacles and 

intruders. This research builds upon the IODS Workshop effort [1]. The purpose was to 

develop a comprehensive list of existing and potential technology solutions that could be 

considered IODS or capable of performing integral function within such systems. 

The main objective of rail intrusion and obstacle detection systems is to provide train 

engineers and/or railroad dispatchers timely information on the status of upcoming 

sections of railroad track and crossings. The goal is to give them enough time to take the 

appropriate emergency actions to stop or slow down the train to avoid or mitigate the 

devastating effects of a collision. The basic technologies used by such systems 

(magnetic, infrared, ultrasonic, acoustic, radar, and video) have not changed much in the 

past few years. The application methods, or platforms, have been expanded, however, 

mainly due to other applications and DHS concerns. New applications of existing 

technologies, as well as delivery platforms, have emerged in the past few years.

Two areas of concern exist along the railway: crossings and the entire ROW. Obviously 

the best case scenario would include total intrusion and obstacle detection along the 

entire railroad ROW. Cost concerns, however, could force the selection of higher risk 

targets along the ROW, such as crossings, bridges, tunnels, and highly populated areas. 

This report provides a synthesis of state-of-the-art research into entire ROW detection 

and crossing-only detection. Some systems, such as the AWARE system, were 

developed for crossing applications only. Other systems, such as the ODO and Wireless 

Sensor Network systems, were developed for application to entire rail corridors. 

Three application methods were identified: infrastructure-based, cooperation between 

infrastructure and locomotive, and locomotive-based. Infrastructure-based systems 

consist mainly of sensors positioned at locations such as crossings and bridges. The main 

disadvantage of such systems is that they tend to be expensive and only cover a specific 

location. Maintenance is also a concern since crews have to travel to each site to inspect 

and maintain each independent detection system. The AWARE system demonstrated in 

Florida incorporated an intrusion detection system with wireless communication and 

warning display on board the locomotive. Crossing violation systems, such as Nestor’s 

Rail CrossingGuard, are capable of cost recovery (revenue-generation) since they can 

detect vehicle gate/signal violations and provide the local law enforcement agency with 

tamperproof evidence. Some communities already use such systems to issue citations for 

red light violations. 

31
Other systems rely on sharing of detection between the locomotive and infrastructure. 

This approach provides for a greater coverage area than most infrastructure-based 

systems. The ODO and Wireless Sensor Network systems depend on a locomotivemounted or base-station (for the Wireless Sensor Network only) component to actively 

interact with the infrastructure sensing components. The Wireless Sensor Network 

approach is capable of providing continuous monitoring independent of train location, 

while the ODO system provides monitoring ahead of the train. These types of systems, 

however, require a substantial capital investment for the infrastructure-based and trainmounted components. 

Although no formal benefit/cost studies have been conducted to date, the least expensive 

options are locomotive-based equipment since these have the capability to monitor the 

whole rail network and need only to be mounted on railroad locomotives, which number 

about 21,000 and are far fewer than the number of crossings or number of railway miles. 

In addition, locomotive-based systems could be selectively used along higher risk routes 

or with higher risk shipments. Railway monitoring is constantly mentioned as an 

application of UAV technology, and DHS already uses these systems to detect intrusion 

along the Mexican border. Small UAV platforms, such as the MLB’s Bat, have proven 

roadway-following capability and high endurance, as well as wireless transmission of 

video imagery back to a portable control unit. The URV concept could potentially offer 

even better protection capabilities since it could also detect track and switch tampering, 

as well as track monitoring in tunnels and bridges, unlike UAVs. In addition, it could 

prove much cheaper to operate and maintain. Its main disadvantage would be that it 

would most likely add to motorist waiting time at crossings, although this could be 

minimized by headway adjustments. The REOST system could probably be the most 

ideal, but many technical issues still need to be addressed in its still ongoing testing 

phase, such as detection around curves. 

As noted throughout this report, a vast selection of technologies from around the world is 

currently available for intrusion and obstacle detection. Some were developed 

specifically for the railroad environment, mainly infrastructure-based and for activecooperation use. Others were developed for other applications, such as perimeter 

security, military reconnaissance, and vehicle detection on roadways. While some 

technologies and COTS systems have been commercially offered and are in operational 

use, many are still either being prototyped or field-tested. Most of the systems described 

in this report show promise, but the effectiveness of many of them in various operational 

conditions has not been properly tested and evaluated. Next steps include an evaluation 

of the promising technologies that are currently ready for use in obstacle detection 

applications and identification of the technologies that require further refinement before 

they can be relied upon to ensure public safety. 

 

In the future, variations of these technologies will likely be drawn from existing 

configurations. The existing technologies, systems, and concepts could be considered as 

elements of a tool box at the disposal of the rail industry and government. These entities 

would draw upon these various tools in their quest to achieve the ultimate goal of 

improved safety, security, and mobility.

32
References 

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(IODS) for Railroad–1998 Requirements Workshop, Federal Railroad 

Administration, Office of Research and Development, Washington, DC, 

DOT/FRA/ORD-01/13, December 2001. 

[2] Reiff, R., Gage, S., Carroll, A., Gordon, J., Evaluation of Alternative Detection 

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[13] http://www.laseroptronix.se/rail/perimeter.html, viewed April 28, 2005. 

[14] AWARE Pilot Project Along South Florida Rail Corridor–Final Project Report, 

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[15] http://www.ntu.edu.sg/home/hw/gids/, viewed April 26, 2005. 

[16] http://www.jreast.co.jp/e/development/theme/safety/safety01.html, viewed April 

28, 2005. 

[17] http://www.jreast.co.jp/e/development/theme/safety/safety02.html, viewed April 

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[18] http://www.capsys-fr.com, viewed April 29, 2005. 

[19] Email exchange on March 24, 2005, with Adrian Molinari, Molinari & 

Associates, Toronto, Canada. 

33 
[20] Information received by mail on May 13, 2005, from Allan Friedman, Alpha 

Zaicon Technology Inc., Hearthstone Crescent,Willowdale, Ontario, Canada M2R 

1G3. Email: alpha@istar.ca, Office Telephone: (416) 633-4710. 

[21] http://objectvideo.com, viewed April 27, 2005. 

[22] http://www.dot.state.mn.us/guidestar/, viewed April 27, 2005. 

[23] http://64.65.174.244/BrochureC3.pdf, viewed April 27, 2005. 

[24] http://www.itsdocs.fhwa.dot.gov/JPODOCS/REPTS_TE/13609_files/6_1_2.htm, 

viewed April 27, 2005. 

[25] Field Test of Monitoring of Urban Vehicle Operations Using Non-Intrusive 

Technologies Final Report. U.S. Department of Transportation, Federal Highway 

Administration, Publication Number FHWA-PL-97-018. May 1997. 

http://www.itsdocs.fhwa.dot.gov/JPODOCS/REPTS_TE/55501!.PDF, viewed 

April 27, 2005. 

[26] Bicycle and Pedestrian Detection. U.S. Department of Transportation, Federal 

Highway Administration and Minnesota Department of Transportation Office of 

Traffic Engineering/ITS. February 2003. 

http://projects.dot.state.mn.us/nit/bikepedfinalreport.html, viewed April 27, 2005. 

[27] Ervin, R.D., MacAdam, C.C., and Gilbert, R.K., A Measurement and Processing 

System for the Vehicle Motion Environment (VME). IVSA 1993 Meeting’s 

“Surface Transportation: Mobility, Technology, and Society,” Washington, DC, 

April 1993. 

Email: adrian.molinari@sympatico.ca, Office Telephone: 416-614-3415. 

[28] http://www.guardiansolutions.com, viewed April 29, 2005. 

[29] http://www.4-dsecurity.com/business_perimetersecurity.htm, viewed May 4, 

2005. 

[30] http://www.saic.com/news/saicmag/2005-winter/wireless.html, viewed April 25, 

2005. 

[31] http://spt.dibe.unige.it/ISIP/reost/Documentation/D4.pdf, viewed April 26, 2005. 

[32] http://www.railwayage.com/may01/highspeed.html, viewed May 11, 2005. 

[33] http://www.reost.com, viewed April 26, 2005. 

[34] Email exchange on April 27, 2005, with Paolo Pozzobon, Professor of Electric 

Energy Static Conversion at University of Genova Electrical Engineering 

Department, Genova, Italy. 

Email: pappo@die.unige.it, Office Telephone: +390103532181. 

[35] http://www.railinks.com/images/rail%20flow%20cart.gif, viewed May 11, 2005. 

[36] Myhra, D., UVAs: No Place to Hide, Homeland Defense Journal, April 2005, p. 

28-30. 

[37] Mini-Unmanned Aerial Vehicles Take to the Airways, TR News 227, July-August 

2003. http://trb.org/publications/trnews/trnews227.pdf, viewed May 9, 2005. 

[38] Harman, L.J., and Shama, U., Unmanned Aerial Vehicles: A New Pilot, 

GeoGraphics Laboratory, Moakley Center for Technological Applications, 

Bridgewater State College, Bridgewater, MA. Email: lharman@bridgew.edu, 

Office Telephone: (508) 531-6144 [received paper via email January 21, 2005]. 

[39] http://robot.spawar.navy.mil/, viewed May 4, 2005. 

[40] http://www.saic.com/products/aviation/vigilante/vig.html, viewed May 4, 2005. 

[41] http://rcwhirlybird.com/tatical/default.htm, viewed May 4, 2005. 

34
[42] http://www.spyplanes.com/bat3.html, viewed May 9, 2005.[43] 

[43] http://www.astronautix.com/lvs/exdrone.htm, viewed May 4, 2005.

35

Acronyms 

AWARD Advanced Warning to Avoid Railroad Delay 

AWARE Advanced Warning Alerts for Railroad Engineers 

BRT Bus Rapid Transit 

COTS commercial off the shelf

DHS Department of Homeland Security 

DOT Department of Transportation 

DSRC Dedicated Short Range Communication 

FRA Federal Railroad Administration 

GIS geographic information system 

GPIDS Guideway and Platform Intrusion Detection System 

GPS global positioning system 

HOT Head-of-Train 

IODS Intruder and Obstacle Detection Systems 

ITS Intelligent Transportation Systems 

JR-East East Japan Railway Company 

LADAR LAser Detection And Range 

LIDS Laser Intrusion Detection System 

MBTA Massachusetts Bay Transportation Authority 

NTU Nanyang Technological University 

ODO Optical Detection of Obstacles 

PIES Platform Intrusion Emergency Stop System 

PTC positive train control 

REOST Railway Electro Optical System for Safe Transportation 

ROW right of way 

SAIC Science Applications International Corporation

SAVME System for Assessing the Vehicle Motion Environment 

SLRT Singapore Light Rail Transit 

UAV Unmanned Aerial Vehicle 

URV Unmanned Rail Vehicle 

VTOL Vertical Take-Off and Landing 

37