Multi-Objective Optimisation of a Variable Speed Limit Control Strategy in a Tunnel Maintenance Work Zone of the Mountain Highway

Zhipeng Fu; Ruizhen Kang; Chen Li; Shuang Liu; Changsong Dong

doi:10.7250/bjrbe.2025-20.666

Multi-Objective Optimisation of a Variable Speed Limit Control Strategy in a Tunnel Maintenance Work Zone of the Mountain Highway

Authors

Zhipeng Fu CCCC First Highway Consultants Co., Ltd.,National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment, Xi’an, Shaanxi, China https://orcid.org/0009-0005-3085-7237
Ruizhen Kang College of Transportation Engineering, Chang’an University, Xi’an, Shaanxi, China https://orcid.org/0009-0008-9263-7645
Chen Li CCCC First Highway Consultants Co., Ltd.,National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment, Xi’an, Shaanxi, China https://orcid.org/0009-0001-6129-0481
Shuang Liu College of Transportation Engineering, Chang’an University, Xi’an, Shaanxi, China https://orcid.org/0009-0007-9550-9385
Changsong Dong CCCC First Highway Consultants Co., Ltd.,National Key Laboratory of Green and Long-Life Road Engineering in Extreme Environment, Xi’an, Shaanxi, China https://orcid.org/0009-0008-1227-1955

DOI:

https://doi.org/10.7250/bjrbe.2025-20.666

Keywords:

MPC control strategy, multi-objective optimization, NSGA-II, SUMO simulation, tunnel maintenance work zone, VSL control

Abstract

Variable Speed Limit (VSL) control is essential for managing highway tunnel maintenance work, as it adjusts speed limits based on road conditions to regulate traffic flow. Developing a VSL control strategy that balances traffic efficiency and safety during maintenance can be challenging. This paper addresses this issue by proposing a VSL control strategy based on Model Predictive Control (MPC) that considers the spatial characteristics of traffic flow in a tunnel maintenance work zone. The strategy aims to minimise total travel time, reduce speed variance, and maximise traffic flow through a multi-objective optimisation approach using a Non-dominated Sorting Genetic Algorithm II (NSGA-II). With the Qinling Tiantai Mountain Tunnel selected as the experimental object, a simulation section is constructed based on the SUMO model with the measured data, and a comparative experiment of different speed limit control cycles in the maintenance work zone is designed. The results show that the method of this paper can effectively reduce the total travel time under the influence of maintenance operations by more than 17.5%, reduce the standard deviation of speed by about 22.1%, and enhance the traffic volume by about 7.8%, which can effectively improve the efficiency of road access and safety level.

Supporting Agencies

CCCC First Highway Consultants Co., Ltd., Xi’an, China,, Scientific Research Project of Shaanxi Provincial Department of Transportation #1” under Grant No.21-42X, Innovation Capability Support Program of Shaanxi #2” under Grant No.2022TD-16

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