Research Papers

Improving Road Safety and Public Health with Real-Time and Predictive Train Crossing Information

Version 1
Date added June 28, 2017
Downloaded 0 times/fois
Category 2017 CARSP XXVII Toronto
Tags Research and Evaluation, Session 5C
Author/Auteur Garreth Rempel
Stream/Volet Research and Evaluation

Slidedeck Presentation Only (no paper submitted)

5C_2_Rempel

Abstract

Real-time traffic information is becoming increasingly available to help with travel routing decisions. This information is convenient for commuters to reduce travel time and can be critical for emergency responders to arrive on scene faster. However, real-time and predictive train crossing information is currently unavailable and can significantly impact travel time and routing decisions. The need for this information is demonstrated by Transport Canada's ongoing investigation into the feasibility of low-cost warning systems that are less costly than flashing lights, bells, and gates but more active than cross-bucks. The need for this information is also demonstrated by the National Research Council of Canada's ongoing research into sharing real-time train crossing blockage information with connected and automated vehicles via dedicated short-range communication (DSRC) to help mitigate and potentially eliminate vehicle collisions with trains. This research addresses the need for real-time and predictive train crossing information and develops methods for sharing this information with various road users. The purpose of this research was to demonstrate the ability to deliver real-time and predictive train crossing information to a wide variety of users (e.g., government transportation departments, emergency service providers, mapping and navigation apps, variable message signs) in several formats. We conducted an extensive literature review to determine if there were existing technologies to provide real-time and predictive train crossing information, designed, developed, and tested a new train detection system and DSRC capabilities, and developed an information system to share this information using web-based tools and smartphone apps. This research resulted in the development of a real-time and predictive train crossing information system and a beta test in the City of Winnipeg. This included independent train detection sensors, data processing and wireless communication functionality, and methods to share this information in real-time using online data portals, web maps, application programming interfaces (APIs), and DSRC. The results of this research demonstrate the ability to deliver real-time and predictive train crossing information. This information can help road users avoid travel delays at railway crossings and support connected and automated vehicle operations. Further, the research demonstrates the potential for developing low-cost warning systems to provide active warnings to road users at remote crossings that currently use cross-bucks. Real-time and predictive train crossing information is convenient for commuters to reduce travel time and can be critical for emergency responders to arrive on scene faster. Currently this information is not available to road users. This research describes how to obtain this information and share it with users in real-time. Further, this research introduces low-cost technology that can help convert passive railway warning systems to active warning systems.

Garreth Rempel