Analysis of Factors Affecting Train Derailments at Highway-Rail Grade Crossings

Similar documents
Principal factors contributing to heavy haul freight train safety improvements in North America: a quantitative analysis

MEMORANDUM. Background

Understanding the risk of level crossing derailments

Hazards Associated with High-Speed Rail (HSR) Operation Adjacent to Conventional Tracks

QUANTITATIVE ANALYSIS OF FACTORS AFFECTING RAILROAD ACCIDENT PROBABILITY AND SEVERITY ROBERT THOMAS ANDERSON

THE RELATIONSHIP BETWEEN TRAIN LENGTH AND ACCIDENT CAUSES AND RATES

THE DEVELOPMENT OF MALAYSIAN HIGHWAY RAIL LEVEL CROSSING SAFETY SYSTEMS: A PROPOSED RESEARCH FRAMEWORK. Siti Zaharah Ishak

STATISTICAL SUMMARY RAILWAY OCCURRENCES 2015

DESIGN BULLETIN #66/2010

Major Factors Affecting Passenger Train Accident Occurrence and Severity in the United States: Paper Number:

Effectiveness of Red Light Cameras in Chicago: An Exploratory Analysis

Driver Behavior at Highway-Rail Grade Crossings With Passive Traffic Controls

Prevention Of Accidents Caused By Rotating Transit Bus Wheels By James M. Green, P.E., DEE

Complete Street Analysis of a Road Diet: Orange Grove Boulevard, Pasadena, CA

Geometric Categories as Intersection Safety Evaluation Tools

Truck Climbing Lane Traffic Justification Report

An Application of Signal Detection Theory for Understanding Driver Behavior at Highway-Rail Grade Crossings

Modal Shift in the Boulder Valley 1990 to 2009

HSIS. Association of Selected Intersection Factors With Red-Light-Running Crashes. State Databases Used SUMMARY REPORT

CHAPTER 9: SAFETY 9.1 TRAFFIC SAFETY INTERSECTION COLLISIONS

Analysis of Run-Off-Road Crashes in Relation to Roadway Features and Driver Behavior

Post impact trajectory of vehicles at rural intersections

Railroad-Highway Grade Crossing Analysis for Corridor Planning Projects

Study on fatal accidents in Toyota city aimed at zero traffic fatality

Title of the proposed project Development of a Toolbox for Evaluation and Identification of Urban Road Safety Improvement Measures

Briefing Paper #1. An Overview of Regional Demand and Mode Share

Relationship Between Child Pedestrian Accidents and City Planning in Zarqa, Jordan

Rogue Valley Metropolitan Planning Organization. Transportation Safety Planning Project. Final Report

Relative safety of alternative intersection designs

WE ALL REMEMBER FOX RIVER GROVE RIGHT?

EFFICIENCY OF TRIPLE LEFT-TURN LANES AT SIGNALIZED INTERSECTIONS

ITARDA INFORMATION. No.128. Special feature

An investigation of railroad-highway grade crossing consolidation rating in Iowa

Simulation Analysis of Intersection Treatments for Cycle Tracks

Crash Patterns in Western Australia. Kidd B., Main Roads Western Australia Willett P., Traffic Research Services

An Analysis of Reducing Pedestrian-Walking-Speed Impacts on Intersection Traffic MOEs

ESTIMATION OF THE EFFECT OF AUTONOMOUS EMERGENCY BRAKING SYSTEMS FOR PEDESTRIANS ON REDUCTION IN THE NUMBER OF PEDESTRIAN VICTIMS

For Information Only. Pedestrian Collisions (2011 to 2015) Resolution. Presented: Monday, Apr 18, Report Date Tuesday, Apr 05, 2016

Memorandum 1. INTRODUCTION. To: Cc: From: Denise Marshall Northumberland County

Turn Lane Warrants: Concepts, Standards, Application in Review

Glossary of Terms. ABANDONMENT The permanent cessation of rail activity on a given line of railroad.

CHAPTER 2 LITERATURE REVIEW

SCHOOL CROSSING PROTECTION CRITERIA

Defining Purpose and Need

Reduction of Speed Limit at Approaches to Railway Level Crossings in WA. Main Roads WA. Presenter - Brian Kidd

Average Runs per inning,

Analyses and statistics on the frequency and the incidence of traffic accidents within Dolj County

PEDESTRIAN/BICYCLIST CRASH ANALYSIS 2015

Highway & Transportation (I) ECIV 4333 Chapter (4): Traffic Engineering Studies. Spot Speed

SCHOOL CROSSING PROTECTION CRITERIA

HEADWAY AND SAFETY ANALYSIS OF SPEED LAW ENFORCEMENT TECHNIQUES IN HIGHWAY WORK ZONES

2009 URBAN MOBILITY REPORT: Six Congestion Reduction Strategies and Their. Effects on Mobility

Characteristics of Traffic Accidents in Highway Work Zones

EXAMINING THE EFFECT OF HEAVY VEHICLES DURING CONGESTION USING PASSENGER CAR EQUIVALENTS

An Analysis of the Travel Conditions on the U. S. 52 Bypass. Bypass in Lafayette, Indiana.

Local road mountable roundabouts are there safety benefits?

PEDESTRIAN COLLISIONS IN LOS ANGELES 1994 through 2000

MEMORANDUM. Charlotte Fleetwood, Transportation Planner

In the spring of 2006, national newspaper headlines screamed

Selected Intersection Crash Analysis for Prepared by: Rita Morocoima-Black Susan Chavarría Lucas Cruse

The Corporation of the City of Sarnia. School Crossing Guard Warrant Policy

SLOW DOWN A STUDY OF SPEEDING ON MCGUINNESS BLVD

INTERSECTION OPERATIONAL ANALYSIS AND NECESSARY RECOMMENDATIONS CIVL 440 Project

Washington St. Corridor Study

FORM A PASCO COUNTY ACCESS CONNECTION PERMIT APPLICATION

Effects of Traffic Condition (v/c) on Safety at Freeway Facility Sections

Traffic Signal Warrant Analysis Report

AUSTRIAN RISK ANALYSIS FOR ROAD TUNNELS Development of a new Method for the Risk Assessment of Road Tunnels

Analysis of Signalized Intersection Crashes Nasima Bhuiyan, EmelindaM. Parentela and Venkata S. Inapuri

CONCLUSIONS AND RECOMMENDATIONS

Evaluating Grade Crossing Safety. Christopher C. Pflaum, Ph.D. Spectrum Economics, Inc. Overland Park, KS (913)

TECHNICAL NOTE THROUGH KERBSIDE LANE UTILISATION AT SIGNALISED INTERSECTIONS

Effects of Traffic Signal Retiming on Safety. Peter J. Yauch, P.E., PTOE Program Manager, TSM&O Albeck Gerken, Inc.

Advance Yield Markings Reduce Motor Vehicle/Pedestrian. Conflicts at Multilane Crosswalks with an Uncontrolled Approach.

Demonstration of Possibilities to Introduce Semi-actuated Traffic Control System at Dhanmondi Satmasjid Road by Using CORSIM Simulation Software

A paper prepared for the 2012 TRB Annual meeting

Appendix A: Safety Assessment

Effects of Geometric Design Features on Truck Crashes on Limited-Access Highways

Mobility and Congestion

A Traffic Operations Method for Assessing Automobile and Bicycle Shared Roadways

D1.2 REPORT ON MOTORCYCLISTS IMPACTS WITH ROAD INFRASTRUCTURE BASED OF AN INDEPTH INVESTIGATION OF MOTORCYCLE ACCIDENTS

Guidelines for Integrating Safety and Cost-Effectiveness into Resurfacing, Restoration, and Rehabilitation Projects

Access Location, Spacing, Turn Lanes, and Medians

TRANSPORTATION ENGINEERING AND PLANNING Vol. I - Safety of Transportation - Benekohal R.F.

Chapter 5: Methods and Philosophy of Statistical Process Control

At-Grade Intersections versus Grade-Separated Interchanges (An Economic Analysis of Several Bypasses)

ANALYSIS OF ACCIDENT SURVEY ON PEDESTRIANS ON NATIONAL HIGHWAY 16 USING STATISTICAL METHODS

Evaluation of shared use of bicycles and pedestrians in Japan

Analysis of Car-Pedestrian Impact Scenarios for the Evaluation of a Pedestrian Sensor System Based on the Accident Data from Sweden

Notes to Benefit-Cost Analysis

2014 QUICK FACTS ILLINOIS CRASH INFORMATION. Illinois Emergency Medical Services for Children February 2016 Edition

EWC EARLY WARNING CONTROL OPERATIONAL PRESENTATION. Charles Dickens (757)

THE MAGICAL PROPERTY OF 60 KM/H AS A SPEED LIMIT? JOHN LAMBERT,

2012 QUICK FACTS ILLINOIS CRASH INFORMATION. Illinois Emergency Medical Services for Children September 2014 Edition

Roadway Conditions as Contributing Factors in Florida Traffic Crashes

VDOT Crash Analysis Procedures for Roadway Safety Assessments

Midtown Corridor Alternatives Analysis

Safety Assessment of Installing Traffic Signals at High-Speed Expressway Intersections

Cycle journeys on the Anderston-Argyle Street footbridge: a descriptive analysis. Karen McPherson. Glasgow Centre for Population Health

TRAFFIC IMPACT STUDY And A TRAFFIC SIGNAL WARRANT ANALYSIS FOR A SENIOR LIVING AND APARTMENT DEVELOPMENT

Transcription:

Chadwick et al TRB 12-4396 1 1 2 3 Analysis of Factors Affecting Train Derailments at Highway-Rail Grade Crossings 4 5 TRB 12-4396 6 7 8 9 Submitted for consideration for presentation and publication at the Transportation Research Board 91 st Annual Meeting 15 November 2011 10 11 12 13 14 15 16 Samantha G. Chadwick 1, M. Rapik Saat, Christopher P. L. Barkan Rail Transportation & Engineering Center Department of Civil and Environmental Engineering University of Illinois at Urbana-Champaign 205 N. Mathews Ave., Urbana, IL 61801 Fax: (217) 333-1924 17 Samantha G. Chadwick M. Rapik Saat Christopher P.L. Barkan (217) 244-6063 (217) 721-4448 (217) 244-6338 schadwi2@illinois.edu mohdsaat@illinois.edu cbarkan@illinois.edu 18 19 20 3337 words + 10 Figures + 1 Table = 6,087 Total Words 21 1 Corresponding author

Chadwick et al TRB 12-4396 2 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 ABSTRACT Implementation of highway-rail grade crossing warning systems, educational programs and research on crossings have all contributed to a steady reduction in the risk to highway users of grade crossings over the past several decades. Much less attention has been given to understanding the effect of grade crossings on train safety and risk. Collisions at highway-rail grade crossings can have serious consequences for the public and the railroads alike, especially in the form of train derailments. The goal of this research is to identify and understand the factors leading to these derailments. This paper focuses on three factors affecting train derailments at highway-rail grade crossings. An examination of the effect of highway vehicle type on derailment occurrence showed that large highway vehicles, such as tractor-semitrailers, cause a disproportionate number of derailments but that vehicle size does not affect derailment severity. Examinations of highway vehicle collision speed and train collision speed showed that derailments are more likely to occur at higher vehicle speeds and lower train speeds. 37 38

Chadwick et al TRB 12-4396 3 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 INTRODUCTION Considerable research has been conducted to understand the impact of highway-rail grade crossings on highway users. This has led to improved grade crossing warning systems, integration of grade crossing operations with highway traffic signaling, public education programs such as Operation Lifesaver, and numerous other improvements. These technologies and programs aim to reduce the number of casualties due to train-highway vehicle collisions, and the result has been a steady decline in the number of incidents and casualties over the past several decades (1). However, much less research has focused on understanding the risk that highway users pose to trains at highway-rail grade crossings. We used two databases maintained by the Federal Railroad Administration (FRA) in order to better understand the effect that highway users have on trains, especially on train derailment rates. Some highway-rail grade crossing collisions result in derailment of the train, whereas others do not; the challenge is to identify the critical factors affecting the former. This paper focuses on 1) type of highway vehicle involved in the collision, 2) speed at collision of highway user, and 3) speed at collision of train. This paper seeks to answer the following questions: Are trucks more likely than cars to cause a derailment and if so how much? Does vehicle size affect derailment severity? Does impact velocity (of the highway vehicle and/or the train) affect derailment rate and severity? How does vehicle size affect the speed distribution of a vehicle striking a train? In this paper, a grade crossing incident is defined as any collision between a rail consist and a highway user at a grade crossing 2. A grade crossing derailment is defined as any grade crossing incident where one or more cars or locomotives were derailed as a result of the incident. DATA SOURCES The FRA maintains two databases that are of great interest to this study. The Rail Equipment Accident (REA) database collects data on any damage sustained by a train consist that exceeds a reporting threshold set by the FRA. This threshold periodically changes to account for inflation and other adjustments; as of 2011 it was set at $9,400. This data is reported to the FRA through the use of form FRA F 6180.54, which is filed by railroads that experienced an incident meeting this criterion. It provides useful information about incidents, such as the number of cars or locomotives derailed, the length of consist, the type of track involved, and a number of other variables of interest. The Highway Rail Accident (HRA) database collects data concerning any impact, regardless of severity, between a railroad on-track equipment consist and any user of a public or private crossing site (FRA 2011). All grade crossing collisions are reported to the FRA regardless of the monetary value of damage caused. The data is reported using form FRA F 6180.57. The database contains a variety of information including data about the highway user 2 The FRA defines a grade crossing accident as any collision, derailment, fire, explosion, act of God, or other event involving operation of railroad on-track equipment (standing or moving) that results in damages greater than the current reporting threshold to railroad on-track equipment, signals, track, track structures, and roadbed. A grade crossing incident is defined as any event involving the movement of on-track equipment that results in a reportable casualty but does not cause reportable damage above the current threshold established for train accidents (2).

Chadwick et al TRB 12-4396 4 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 involved, the speed of the train at collision, and environmental factors such as time of day and weather conditions. METHODOLOGY Data for all U.S. railroads during the period 1991 through 2010 were used. Each of the two databases described above provides useful data for this study. The HRA database contains the largest amount of pertinent information; however, further analysis required identification of incidents that resulted in derailment, and the HRA database does not provide any information about the number of cars or locomotives derailed in the incident. On the other hand, the REA database does provide the derailment information but not the detailed data needed regarding grade crossing incidents. The solution was to merge the two databases in order to create a dataset consisting of incidents that had been reported using both forms. A unique identification code was created for each incident in the HRA and REA databases. The code concatenated the date, time, and crossing identification number to provide a field that could be cross-referenced between the two databases. This methodology resulted in a consolidated dataset consisting only of incidents that occurred at grade crossings and were also REA-reportable (i.e. exceeded the REA damage value threshold). This consolidated dataset contained what were likely the most severe grade crossing incidents. Mainline grade crossing incidents were the focus of this study because they accounted for approximately 88% of all incidents. A Venn diagram was prepared showing the relationship among the datasets used (Figure 1). 103 104 105 Figure 1 Venn diagram representing data set. 106

Frequency (Accidents) Chadwick et al TRB 12-4396 5 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 RESULTS The frequency distribution of incident severity as measured by the number of cars or locomotives derailed in individual grade crossing incidents was plotted (Figure 2). The modal value was for incidents in which one car or locomotive derailed with declining frequency up to a maximum of 35 derailed cars and locomotives in one incident. 180 160 140 120 100 80 60 40 20 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Derailment Severity (Cars and Locos Derailed) Figure 2 Number of rail cars derailed per incident at grade crossings given that a derailment occurred. Large Highway Vehicle Involvement The larger mass of trucks suggests that train collisions with them may be more likely to result in a derailment. An analysis was conducted to test this hypothesis and quantify the relative difference between larger and smaller motor vehicles. The percentage of large highway vehicle traffic at a given highway-rail grade crossing may have a corresponding risk of causing a derailment. The HRA database contains a field that identifies the type of highway vehicle involved in the incident. Types B (straight truck) and C (tractor-semitrailer) were believed to generally be the heaviest vehicles and these were compared to all other types 3. For the study period, the total number of REA-reportable, mainline grade crossing derailments involving large vehicles were compared with those involving other vehicles (Figure 3). 3 It is possible that buses (type F ) should also be included in the large vehicle category; however, analysis showed that their exclusion did not affect the results for the twenty-year period being studied because no derailments exceeding the REA reporting threshold involving buses occurred.

Percent of Incidents Chadwick et al TRB 12-4396 6 90% 80% Large Vehicle No Large Vehicle 70% 60% 50% 40% 30% 20% 10% 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 0% All Incidents Incidents Resulting in Derailment Figure 3 Incidents occurring at grade crossings on mainline track from 1991 to 2010 involving large highway vehicles versus all other vehicles. The data shows that large highway vehicles were involved in 29% of all mainline grade crossing incidents and 85% of mainline REA-reportable grade crossing derailments and thus were four times more likely to cause a derailment. The other 15% of grade crossing derailments involved automobiles, pick-up trucks, other motor vehicles, and vans. The greater tendency for large vehicles to cause derailments led to the question about whether they might also tend to cause more severe derailments than smaller vehicles. To investigate this hypothesis, the distribution of total cars and locomotives derailed in incidents was compared for incidents that did and did not involve large vehicles (Figure 4). Statistical testing of the data using the Wilcoxon Rank Sum test with α = 0.05 showed that there was no significant difference between the severity of derailment incidents involving large vehicles, and the severity of derailment incidents not involving large vehicles. In other words, once a motor vehicle has caused a derailment, the severity of that derailment is little affected by the size of the vehicle that caused it.

Percent of Derailments Chadwick et al TRB 12-4396 7 50% 40% Large Vehicle Involvement No Large Vehicle Involvement 30% 20% 10% 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 0% 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Derailment Severity (Cars and Locos Derailed) Figure 4 Number of cars and locomotives derailed in grade crossing incidents by vehicle type. Frequencies are given as a percentage of all incidents of each type. Speed of Highway Vehicle at Collision Another factor of interest in terms of assessing the hazard that grade crossings pose to train safety is velocity and whether the motor vehicle struck the train or the train struck the motor vehicle. The speeds of both the highway vehicle and train might affect this so both were investigated. The FRA records data about the speed at collision of the highway vehicle involved in grade crossing incidents. It should be noted that these data are estimated by observers at the incident scene. The data were divided into two categories according to whether the train struck the highway vehicle or the highway vehicle struck the train. This was done because the physical mechanism involved in these two types of collisions is likely very different and may have to be accounted for differently in the final statistical model. For each category, we further divided the data according to derailments and nonderailments. We then performed pair-wise comparisons within the categories. This is shown in Figures 5a and 5b.

Percent of Category Percent of Category Chadwick et al TRB 12-4396 8 163 40% 30% Derailment: Train struck vehicle Non-Derailment: Train struck vehicle 20% 10% 0% 164 165 (a) 40% 30% Speed of Highway Vehicle At Collision (mph) Derailment: Vehicle struck train Non-Derailment: Vehicle struck train 20% 10% 0% 166 Speed of Highway Vehicle At Collision (mph)

Frequency (Accidents) Chadwick et al TRB 12-4396 9 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 (b) Figure 5 Speed at collision of vehicles involved in grade crossing incidents, 1991-2010 for (a) train striking highway vehicle scenario and (b) highway vehicle striking train scenario. The majority of train striking vehicle incidents occurred at highway vehicle speeds less than 5 mph. A large number of incidents occurred in which the highway vehicle stopped or became stranded on the tracks. A survey of the narrative fields provided with each incident record indicates that this is a common problem, with about 40% of all train striking vehicle incidents involving a highway user stopped on the tracks. Speeds for the vehicle striking train incidents were generally higher, mostly concentrated in the 40 to 60 mph speed range. Statistical testing was performed on the data to determine if there was a difference in speed between derailment and non-derailment incidents. Testing using the Wilcoxon Rank Sum test with α = 0.05 showed that in both the train striking vehicle and vehicle striking train scenarios derailments are more likely to occur at higher vehicle speeds. The effect of vehicle speed on derailment severity was also studied (Figures 6a and 6b). The distributions of the total number of cars and locomotives derailed do not suggest any strong relationship between highway vehicle speed at collision and derailment severity. 60 50 0 mph 1-20 mph 21-40 mph 41-60 mph 40 30 20 10 185 186 187 (a) 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Derailment Severity (Cars and Locos Derailed)

Frequency (Accidents) Chadwick et al TRB 12-4396 10 18 16 1-20 mph 21-40 mph 41-60 mph 61-80 mph 14 12 10 8 6 4 2 188 189 190 (b) 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 Derailment Severity (Cars and Locos Derailed) 191 192 193 194 195 196 197 198 199 200 Figure 6 Distribution of total cars and locomotives derailed in incidents, by vehicle speed category, where (a) train struck motor vehicle and (b) motor vehicle struck train. As discussed above, large highway vehicles were involved in a disproportionately large percentage of grade crossing derailments, so the motor-vehicle-speed analysis was repeated using only large highway vehicles (Figure 7). The results followed the same trends exhibited by the all-vehicle analysis.

Percent of Incidents Chadwick et al TRB 12-4396 11 40% 30% Derailment: Train struck large vehicle Non-Derailment: Train struck large vehicle Derailment: Large vehiclestruck train Non-Derailment: Large vehicle struck train 20% 10% 0% 201 202 203 204 205 206 207 208 209 210 Speed of Highway Vehicle At Collision (mph) Figure 7 Speed at collision of large vehicles involved in grade crossing incidents. Speed of Train at Collision A complementary analysis was conducted to investigate the effect of train speed on derailment occurrence and severity. The FRA also records information about the speed of trains involved in grade crossing incidents, and these data may be either exact or estimated. The data were grouped into the same four categories described above. The percentage of each type of incident that occurred at a given train speed was plotted (Figure 8).

Percent of Incidents Chadwick et al TRB 12-4396 12 211 212 20% Derailment: Train struck vehicle Non-Derailment: Train struck vehicle 15% 10% 5% 0% 213 214 (a) Speed of Train At Collision (mph)

Percent of Incidents Chadwick et al TRB 12-4396 13 20% Derailment: Vehicle struck train Non-Derailment: Vehicle struck train 15% 10% 5% 0% 215 216 (b) Speed of Train At Collision (mph) 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 Figure 8 Speed at collision of trains involved in grade crossing incidents for (a) train striking vehicle and (b) vehicle striking train scenarios. The distributions for all four scenarios were roughly the same, with the majority of collisions occurring in the 35 to 55 mph range most likely because this represents the typical range of mainline speeds. Statistical testing of the data using the Wilcoxon Rank Sum test with α = 0.05 showed that derailments were more likely to occur at lower train speeds for both scenarios. The effect of train speed on derailment severity was also studied for all vehicles and for large motor vehicles alone, but no obvious relationship was evident for any of these scenarios. DISCUSSION Throughout this paper, each of the questions posed in the introduction have been considered. First, large vehicles such as trucks appear to be about four times more likely to cause a grade crossing derailment than small vehicles. Figure 3 shows that large vehicles are involved in a disproportionately greater number of derailments than the number of incidents in which they are involved, and by a considerable margin. This result is not surprising; in cases where a train hits a large, heavy vehicle its mass may make it more likely to dislodge the train from the tracks, and it is also capable of absorbing more of the train's momentum causing a

Chadwick et al TRB 12-4396 14 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 sudden stop and possible jack-knifing of the train. A smaller, lighter vehicle is more likely to be pushed down the tracks allowing the train to lose speed more gradually. Somewhat surprisingly, vehicle size did not seem to have much effect on derailment severity. While the most severe incidents those resulting in the derailment of more than 25 cars and locomotives were generally caused by trucks, this accounted for only 3% of all incidents. Setting aside this 3%, the distribution of severity for the large vehicle and no large vehicle cases was very similar (Figure 4). Impact velocity of both the highway vehicle and the train were found to have an effect on derailment rate. It was shown that derailments tended to occur at higher vehicle speeds and lower train speeds. That higher vehicle speeds result in more derailments is not surprising given that the energy involved in high vehicle speed collisions is greater than other collisions, making the vehicle more likely to dislodge the train from the traicks. It was more surprising to find that derailments were more likely to occur at lower train speeds. One proposed reason for this is that a train traveling at higher speeds is more likely to knock the vehicle out of the way in a collision, whereas a slower train will not impart enough force to do so. Additionally, some interesting patterns were evident in the velocity study. For the train striking vehicle category, about 40% of these incidents occurred between a train and a vehicle that was stationary on the tracks (with a speed of 0 mph). 30% of all derailments for this category occurred with a stationary vehicle. Examination of these incidents found that at least 40% were caused by a truck being stuck on a crossing and unable to move in time. This suggests that further efforts to modify crossing geometry so that trucks are less likely to get stuck would yield benefits. Alternatively, frequent crossing inspection combined with careful route planning could prevent trucks from becoming stuck by sending them on routes that are more appropriate given their under-truck clearance. It is difficult to tell if impact velocity has an effect on derailment severity, because the small data set available did not provide a very clear distribution. However, it seems that speed alone may not have sufficient explanatory power. Momentum, as opposed to speed, seems to be a more important factor affecting train derailment severity. Speed may be more important if it is correlated with vehicle size and train length. Vehicle size appeared to have little relationship with the speed distribution of vehicles striking the train. Although the data were not all presented due to space constraints, the distributions for all motor vehicles and for large vehicles were similar. FUTURE WORK Future research will be expanded to include detailed data about the intersecting highways, perhaps using data from the Federal Highway Administration, which maintains travel monitoring throughout the U.S. Additionally, the latitude and longitude information given for each grade crossing in the Highway-Rail Crossing Inventory could allow for integration with current GIS data, which could expand the scope and power of the analysis. Other factors pertaining to grade crossing incidents and derailments are also being explored, with the ultimate goal of developing a model to predict derailment rate at an individual grade crossing or along a rail line with a combination of different grade crossing vehicular traffic and warning systems. Additional analysis will also consider passenger and freight trains separately, to better understand the different effect that grade crossing collisions have on these two train types.

Chadwick et al TRB 12-4396 15 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 CONCLUSIONS This paper analyzed three factors in grade crossing incidents and their effect on derailment rate and severity. The purpose was to identify which factors have an effect on these metrics, with the longer range goal of developing a model to predict derailment risk at a given grade crossing. The results show that vehicle size has a strong effect on derailment rate, but little effect on derailment severity. Vehicle and train speed at collision also have an effect on derailment rate but little effect on severity. Current research considered only mainline, REAreportable incidents from the years 1991 to 2010, which represents an expanded data set which was developed to obtain a more robust sample size and greater statistical power. ACKNOWLEDGEMENTS The authors wish to thank Xiang Liu, Laura Ghosh and Nanyan Zhou for their assistance on this project. The first and second authors were supported in part by a grant from ABSG. 298 299 300 301 302 303 304 305 REFERENCES 1. Mok, S. C., and I. Savage. Why Has Safety Improved at Rail-Highway Grade Crossings? In Risk Analysis, Vol. 25, No. 4, Society for Risk Analysis, 2005. 2. Federal Railroad Administration (FRA). FRA Guide for Preparing Accident/Incident Reports, FRA, U.S. Department of Transportation, 2011. 3. Federal Highway Administration (FHWA). FHWA Railroad-Highway Grade Crossing Handbook, FHWA, U.S. Department of Transportation, 2007.