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Railroad-Highway Crossing Safety Improvement Evaluation and Prioritization Tool
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The expected crash frequency model of Illinois Department of Transportation’s Bureau of Design and Environment needed improvement to incorporate track circuitry as well as pedestrian exposure at railroad-highway grade crossings to make the model more comprehensive. The researchers developed, calibrated, and validated three models to predict collision rates at public, at-grade railroad-highway crossings in Illinois’ six-county northeast region for prioritizing railroad-highway crossings for safety improvements. The first model updated B-factors in the existing Illinois model, which was last validated with data from 1968. The second model modified B-factors to include circuitry types given the active maximum traffic control device at the crossing and added another factor (i.e., P-factor) to account for pedestrian daily traffic using the crossing. The third model added a P-factor to the existing US Department of Transportation’s web accident prediction system model to account for daily pedestrian traffic. Using year 2018 validation data, the first model had an r2 of 0.20 with reported collision rates. The second model had an r2 of 0.58 with reported collision rates, while the existing BDE model had an r2 of 0.17 with year 2018 reported collision rates. The third model had an r2 of 0.70 with reported collision rates using 2018 validation data whereas the existing US Department of Transportation’s web-based accident prediction system model had an r2 of 0.50 using year 2018 validation data. The three models are presented in this report along with a digital tool using the second model for illustrative purposes.
Illinois Center for Transportation
Title: Railroad-Highway Crossing Safety Improvement Evaluation and Prioritization Tool
Description:
The expected crash frequency model of Illinois Department of Transportation’s Bureau of Design and Environment needed improvement to incorporate track circuitry as well as pedestrian exposure at railroad-highway grade crossings to make the model more comprehensive.
The researchers developed, calibrated, and validated three models to predict collision rates at public, at-grade railroad-highway crossings in Illinois’ six-county northeast region for prioritizing railroad-highway crossings for safety improvements.
The first model updated B-factors in the existing Illinois model, which was last validated with data from 1968.
The second model modified B-factors to include circuitry types given the active maximum traffic control device at the crossing and added another factor (i.
e.
, P-factor) to account for pedestrian daily traffic using the crossing.
The third model added a P-factor to the existing US Department of Transportation’s web accident prediction system model to account for daily pedestrian traffic.
Using year 2018 validation data, the first model had an r2 of 0.
20 with reported collision rates.
The second model had an r2 of 0.
58 with reported collision rates, while the existing BDE model had an r2 of 0.
17 with year 2018 reported collision rates.
The third model had an r2 of 0.
70 with reported collision rates using 2018 validation data whereas the existing US Department of Transportation’s web-based accident prediction system model had an r2 of 0.
50 using year 2018 validation data.
The three models are presented in this report along with a digital tool using the second model for illustrative purposes.
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