z-logo
open-access-imgOpen Access
Variable Speed Limit Strategies Based on the Macro Hierarchical Control Traffic Flow Model
Author(s) -
Shubin Li,
Tao Wang,
Hualing Ren,
Baiying Shi,
Xiangke Kong,
Jianyong Chai,
Xuejuan Wang
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 - 10.1155/2021/9910097
Subject(s) - speed limit , traffic flow (computer networking) , traffic congestion reconstruction with kerner's three phase theory , macro , variable (mathematics) , traffic generation model , transport engineering , floating car data , computer science , control (management) , traffic congestion , traffic conflict , limit (mathematics) , simulation , engineering , real time computing , computer network , mathematics , mathematical analysis , artificial intelligence , programming language
The superior traffic control system can promote the efficiency of mainstream expressway. As the effective method to smooth traffic system, the variable speed limits (VSL) strategies are discussed in an expressway traffic network. The dynamic OD estimation model is used to produce the real traffic information, which is loaded to the traffic network. Then, the prediction information of traffic variables and the VSL strategy are introduced to macro hierarchical control traffic flow model. A solution algorithm is further developed to find the optimal parameters of VSL by minimizing the total travel time and delay. The simulation results show that the proposed strategy perfects well, the traffic congestion is effectively alleviated, and the traffic efficiency of the road section is significantly improved. This framework can be adopted by transit managers for traffic efficiency.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom