Quantitative Multi-Criteria Decision Support Approach for Prioritizing Grade Crossings to Address the Problem of Blocked Crossings
Aleksandr Prodan, Vivek Sakhrani, Marc‐André Roy, Matthew Dietrich, Scott N. Phinney, Megan McClory
Abstract
Aleksandr Prodan, Vivek Sakhrani, Marc‐André Roy, Matthew Dietrich, Scott N. Phinney, Megan McClory
Abstract
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.
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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.
Key concepts: Transport engineering, Hazard, Duration (music), Computer science, Set (abstract data type), Level crossing, Crash, Prioritization