A Highway On-Ramp Control Approach Integrating Percolation Bottleneck Analysis and Vehicle Source Identification

Shengnan Li, Hu Yang, Minglun Li, Jianjun Dai and Pu Wang ()
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Shengnan Li: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Hu Yang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Minglun Li: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Jianjun Dai: Hunan Communications Research Institute Co., Ltd., Changsha 410015, China
Pu Wang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

Sustainability, 2023, vol. 15, issue 16, 1-15

Abstract: Identifying the bottleneck segments and developing targeted traffic control strategies can facilitate the mitigation of highway traffic congestion. In this study, we proposed a new method for identifying the bottleneck segment in a large highway network based on the percolation theory. A targeted on-ramp control approach was further developed by identifying the major vehicle sources of the bottleneck segment. We found that the identified bottleneck segment played a crucial role in maintaining the functional connectivity of the highway network in terms of meeting the required level of service. The targeted on-ramp control approach can more effectively enhance the service level of the highway network.

Keywords: highway bottleneck; percolation theory; traffic control; major vehicle sources (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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