Evaluation of Driver Behavior at Railroad-Highway Grade Crossings Using Naturalistic Driving Study Data
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2021-02-03
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Alternative Title:Driver Behavior at Highway-Rail Grade Crossings Using NDS and Driving Simulators
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Subject/TRT Terms:
- Automatic data collection systems
- Behavior
- Data analysis
- Defensive drivers
- Drivers
- Driving simulators
- Evaluation and assessment
- Railroad grade crossings
- Traffic control devices
- Vehicle miles of travel
- Daylight saving time
- Annual average daily traffic
- freight train miles
- fatality analysis
- reporting system
- data normalization
- crossbuck
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Edition:Technical Report
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Abstract:Michigan Technological University (Michigan Tech) used the Second Strategic Highway Research Program (SHRP2) naturalistic driving study (NDS) data and driver simulator to perform a quantitative evaluation of driver behavior at highway rail grade crossings (HRGCs). We developed a three-point scale to generate driver behavior score for over 9,000 NDS traversals and used the mean scores to perform statistical comparisons of driver behavior at HRGCs with different traffic control devices (TCDs), with/without accident history, and with various environmental conditions. We also simulated two HRGCs in a driver simulator and compared the driver behavior scores between naturalistic and simulated environment. The investigation revealed that most drivers do not visually scan for trains and do not prepare to stop, regardless the type of warning device present at the crossing, or the environmental conditions that prevail at the time of traversal. The results were fairly consistent in both NDS and simulated approaches. The NDS data analysis showed very little statistical difference in driving behavior between any of the TCDs analyzed. The only exceptions were the significantly higher mean scores at passive HRGCs equipped with stop signs and the higher mean scores for traversals that took place during the day versus night time
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Main Document Checksum:urn:sha256:9cd4af13b2c7e20173eae22647970958611fbc92457d9a9d0132c03383c800f2