Abstract
New technologies and traffic data sources provide great potential to extend advanced strategies in freeway safety research. The High Definition Monitoring System (HDMS) data contribute comprehensive and precise individual vehicle information. This paper proposes an innovative Variable Speed Limit (VSL) based approach to manage crash risks by intervening in traffic flow dynamics on freeways using HDMS data. We first conducted an empirical analysis on real-time crash risk estimation using a binary logistic regression model. Then, intensive microscopic simulations based on AIMSUN were carried out to explore the effects of various intervention strategies with respect to a 3-lane freeway stretch in China. Different speed limits with distinct compliance rates under specified traffic conditions have been simulated. By taking into account the trade-off between safety benefits and delay in travel time, the speed limit strategies were optimized under various traffic conditions and the model with gradient feedback produces more satisfactory performance in controlling real-time crash risks. Last, the results were integrated into lane management strategies. This research can provide new ideas and methods to reveal the freeway crash risk evolution and active traffic management.
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- http://downloads.hindawi.com/journals/jat/2018/3610541.pdf under the license https://creativecommons.org/licenses/by
- http://dx.doi.org/10.1155/2018/3610541 under the license cc-by
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- http://dx.doi.org/10.1155/2018/3610541 under the license http://creativecommons.org/licenses/by/4.0
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Published on 01/01/2018
Volume 2018, 2018
DOI: 10.1155/2018/3610541
Licence: Other
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