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Optimization Model and Method of Variable Speed Limit for Urban Expressway
Author(s) -
Shubin Li,
Tao Wang,
Hualing Ren,
Baiying Shi,
Xiangke Kong
Publication year - 2021
Publication title -
journal of advanced transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.577
H-Index - 46
eISSN - 2042-3195
pISSN - 0197-6729
DOI - 10.1155/2021/9950417
Subject(s) - speed limit , traffic flow (computer networking) , limit (mathematics) , variable (mathematics) , computer science , traffic congestion , traffic generation model , traffic congestion reconstruction with kerner's three phase theory , network traffic control , network traffic simulation , simulation , traffic simulation , real time computing , transport engineering , engineering , computer network , mathematics , microsimulation , mathematical analysis , network packet
The urban expressway network is the main part of the urban traffic network carrying most of the city’s traffic pressure for its continuity and rapidity, but the control method of the traffic flow was too simple to other control methods in application in addition to the ramp control and the fixed speed control. In this paper, the theory of variable speed limit (VSL) was used to develop an optimal control model based on the improved traffic flow simulation model according to the characteristics of urban expressway traffic flow. The objective of the proposed model is to minimize the delay and maximize the traffic flow. It can adjust the traffic flow on the network in space time so that the whole network is in a state of equilibrium which not only is conducive to the control of the local traffic congestion and avoids the spread of congestion but also improves the traffic safety. The SPSA-based solution algorithm was proposed by taking into account the needs of real-time online applications. It can not only ensure the accuracy of the solution but also meet the requirements of the simulation time. The simulation results show that the variable speed limit can be optimized in moderate demand, and the proposed model and algorithm are effective and feasible in this paper. The conclusions are useful to help the traffic management department to formulate reasonable traffic control strategies.

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