Deriving a surrogate safety measure for freeway incidents based on predicted end-of-queue properties
Deriving a surrogate safety measure for freeway incidents based on predicted end-of-queue properties
- New search for: Chou, Chih-Sheng
- New search for: Nichols, Andrew P.
- New search for: Chou, Chih-Sheng
- New search for: Nichols, Andrew P.
Incidents can significantly impact freeway operations and deteriorate mobility and safety. This study quantified their safety impacts through inspecting queue properties. Specifically, the end-of-queue (EOQ), where severe rear-end collisions commonly occur, is employed for safety assessment based on vehicles’ trajectories. Since detector data is typically available, this study applied such data for EOQ identification, as opposed to vehicle trajectories that are difficult to collect and process. Three measures related to queue duration, impact area and vehicle number exposed to the EOQ are presented as surrogates. To understand the applicability of these measures, a systematic set of incident scenarios is replicated with VISSIM. Quantitative results are used to estimate regression models, and significant variables are identified. The proposed methods can be used to evaluate safety impact of traffic incident management programs such as freeway service patrol, as well as to determine optimal plans for prearranged incidents such as pothole repair.
Document information
Deriving a surrogate safety measure for freeway incidents based on predicted end-of-queue properties
IET Intelligent Transport Systems ; 9 , 1 ; 22-29
2015-02-01
8 pages
Article (Journal)
Electronic Resource
English
surrogate safety measure , queueing theory , pothole repair , detector data , road safety , road vehicles , freeway service patrol , vehicle trajectories , queue duration , EOQ identification , freeway incidents , safety assessment , predicted end-of-queue properties , impact freeway operations , VISSIM , road traffic , rear-end collisions , traffic incident management programs , vehicle number
Metadata by IET is licensed under CC BY 3.0
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