Advanced Warning System to Improve Safety at Train Grade Crossings

The severity of traffic accidents at train grade crossings has led to efforts in mitigating their potential damaging effects. Over the last 45 years, significant investment has been made at these crossings in the United States to reduce the number of accidents. Initially, these improvements reduced accidents, but in the last decade, the numbers have plateaued, even as additional safety investment has continued. Geospatial data from the Federal Railroad Administration was evaluated to ascertain the causes of the efficacy reduction of traditional safety measures. Temporal patterns were detected in diverse parameters that measure accident seriousness such as their frequency, financial damages, injuries, and deaths. An advanced warning system for motorist was proposed in this research to allow them enough time to change their schedules and driving routes, avoiding blockages caused by incoming trains. To avoid pitfalls from previous proposed systems the model will be initially implemented in locations with a high number of accidents and lower layout complexity for the railway, roads, and train grade crossings. Two railways in Texas were selected for the initial implementation of the system. The proposed pilot locations showed high potential for the development of the advanced warning system, in preparation for a broader effort to continue the improvement in safety at railway crossings.

Quantitative Multi-Criteria Decision Support Approach for Prioritizing Grade Crossings to Address the Problem of Blocked Crossings

How should an agency proactively identify and prioritize rail-highway grade crossings for intervention in relation to their likely performance benefits for the community and the system? Performance is mainly related to two factors: (i) the likelihood and duration of “blockage,” that is, the temporary obstruction of a road link when a train blocks the intersecting grade crossing, and (ii) the “hazard condition” of the crossing itself, with regard to its design and asset quality. Existing analytical grade crossing prioritization models focus almost solely on safety and crash prevention by addressing the “hazard condition” aspect of performance. The paper develops a quantitative multi-criteria approach that not only considers and builds on existing analytical safety-based approaches, but goes beyond and also includes considerations such as blocked crossings. The model calculates a multi-dimensional adaptive capacity score (ACS) for each crossing, which can then be used to rank a set of crossings, as well as test different policy scenarios and their effect on prioritization. The model is applied to approximately 5,700 grade crossings in the State of Ohio and detailed pilot validations with stakeholders in two counties conducted. Based on the validation process, the model provides comprehensive and cohesive results and is being deployed statewide. Next steps involve incorporating considerations for truck traffic and pedestrians/bicycles (non-motorized users) in calculating the ACS as well as developing mitigation measures for blocked crossings that can be considered from the model.