Evaluating safety at railway level crossings with microsimulation modeling

Safety at railway level crossings (RLXs) is a worldwide issue that increasingly attracts the attention of relevant transport authorities, the rail industry, and the general public. The differences in the operation characteristics of varying types of warning devices, together with differences in crossing geometry, traffic, or train characteristics, leads to different driver behaviors at crossings. The aim of this study was to use traffic microsimulation modeling based on field video recording data to compare the safety performance of varying conventional RLX warning systems. The widely used microsimulation model VISSIM was modified to produce safety-related performance measures, namely, collision likelihood, delay, and queue length. The results showed that RLXs with an active warning system were safer than those with a passive sign by at least 17%. Integration of surrogate measures in conjunction with traffic simulation models determined which safety approach was more efficient for specified traffic and train volumes

Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX

A vision-based method for on-road truck height measurement in proactive prevention of collision with overpasses and tunnels

This is the accepted manuscript. The final version is available from Elsevier at http://www.sciencedirect.com/science/article/pii/S0926580514002167.Over-height trucks are continuously striking low clearance overpasses and tunnels. This has led to significant damage, fatalities, and inconvenience to the public. Smart systems can automatically detect and warn oversize trucks, and have been introduced to provide the trucks with the opportunity to avoid a collision. However, high cost of implementing these systems remains a bottleneck for their wide adoption. This paper evaluates the feasibility of using computer vision to detect over-height trucks. In the proposed method, video streams are collected from a surveillance camera attached on the overpass/tunnel, and processed to measure truck heights. The height is measured using line detection and blob tracking which locate upper and lower points of a truck in pixel coordinates. The pixel coordinates are then translated into 3D world coordinates. Proof-of-concept experiment results signify the high performance of the proposed method and its potential in achieving cost-effective monitoring of over-height trucks in the transportation system. The limitations and considerations of the method for field implementation are also discussed.This material is based upon work supported by West Virginia University, Myongji University, and University of Cambridge

Robert L. Gleave v. The Denver and Rio Grande Western Railroad Company, a corporation, Utah Railway Company, a corporation : Brief of Appellant

(Case No. 20166) (Case No. 20300) Consolidated Case No. 20300 BRIEF OF APPELLANTS AND CROSS-RESPONDENTS THE DENVER AND RIO GRANDE WESTERN RAILROAD COMPANY AND UTAH RAILWAY COMPANY Appeal from the Judgment of the Fourth Judicial District Court, Utah County, State of Utah The Honorable Cullen Y. Christensen, Presiding

Feasibility of Evaluating Design Ideas for Reducing Vehicular Entrapment at Railroad Crossings Using a Laboratory Experiment

The number of accidents at railroad crossings is particularly high at places where streets run parallel to the railroad tracks. Existing grade crossings were investigated for potential problems and studied for design solutions. The present study reports progress of the first phase of a NJ DOT sponsored project. A laboratory experiment was designed for evaluating various design ideas before they are implemented in the second phase field study. The laboratory study used images taken from actual scenes of railroad crossings in New Jersey, instead of graphical drawings commonly used in driving simulations. Possible design ideas were edited using image processing software. Those design ideas were saved in different layers for generating design combinations which were superimposed on the background images to create virtual railroad crossing scenes. Nighttime images were also made possible by retouching the digital daytime images. Preliminary results of the in-lab experiment were presented. The experience learned from the current project indicates that use of actual images with superimposed design ideas is a cost-effective approach of evaluating and redesigning display layout

Analysis and Development of Emergency Management Information System for Railway Systems in Taiwan

Railway is one of the most efficient, convenient, and comfortable ways with maximum mobility to meet people. Railway accidents or disasters often cause delays and service interruptions, resulting in operational and other loss. Despite many railway systems in Taiwan having a variety of monitoring systems for natural disasters, they still need an efficient platform for the emergency management of disasters and accidents since time and efficiency are the keys to emergency management. This study aims to fill in this gap by developing an emergency management information system for Railway Systems in Taiwan, i.e. “Railway Emergency Management Information System”, to support railway emergency management center and its sub-divisions in resource management, communication, messaging, and information sharing among different groups. The system includes many features that will improve communications between emergency management center and the mobile emergency management center to facilitate the progress of the disaster control units and dispatching at the disaster site. The study’s information system has been designated by local railway administration as the core system and starts trial since February 2012. Information requirement analysis, framework and design of the aforementioned information system will be discussed in this paper. It is hoped that the present study's information system research will help improve the emergency response of railway administration and provide safer rail transport service for the passengers

EVALUATION OF DRIVER BEHAVIOR AT HIGHWAY-RAILROAD GRADE CROSSINGS BASED ON ENVIRONMENTAL CONDITIONS AND DRIVER DEMOGRAPHICS

Although the total number of highway-railroad grade crossing (HRGC) accidents has significantly decreased in recent decades, they remain as one of the highest causes of injuries and fatalities in rail transportation. It is known that driver behavior is the leading cause for accidents at HRGCs, but there is less understanding on the reason for these inappropriate behaviors. This research uses the Strategic Highway Research Program 2 Naturalistic Driving Study (SHRP 2 NDS) data and a behavior scoring methodology developed at Michigan Technological University (Michigan Tech), to evaluate driver behavior when traversing HRGCs. More specifically, it uses a two-sample t-test to determine whether there is a statistically significant difference in driver behavior based on weather condition, driver demographics (gender and age) and time of day. It also further divides the HRGCs to three subgroups based on the traffic control devices (TCD) and performs similar analysis for each subgroup. The research has identified that while statistically significant differences were absent in majority of the tested scenarios, they do exist between some of the compared categories. Especially, both male and female drivers received lower behavior scores during the night compared to the day and female drivers received lower behavior scores under rain and higher behavior scores in snow condition. In contrast to the researcher’s expectation, the data did not show any significant difference in average behavior scores of male versus female drivers. When considering the impact of TCD types on driver behavior, it was found that except for the “snow” condition, there was very little variability between behavior scores under various weather conditions