Bibliographic Details
| Title: |
Research on Optimization Method of Vehicle Speed in Urban Road Conditions Based on Interval Analysis. |
| Authors: |
ZHU, Lingyun1 zhuly1028@126.com, SHI, Haozhang2 1442756147@qq.com, WANG, Lei3 1974727584@qq.com, QIU, Mingming2 hfutqmm@hfut.edu.cn, ZHAO, Han2 hanzhaoff@qq.com |
| Source: |
Mechanika. 2026, Vol. 32 Issue 2, p116-131. 16p. |
| Subjects: |
Interval analysis, Energy consumption, City traffic, Traffic flow, Predictive control systems, Autonomous vehicles |
| Abstract: |
Energy saving is the theme of automobile development, and intelligence and networking are the inevitable trend of automobile technology development. Aiming at the influence of traffic information on vehicle energy consumption, an economic speed planning method for intelligent connected vehicles based on interval analysis is proposed. Firstly, based on cellular automata and confidence interval theory, traffic information rules are introduced, and a road speed interval extraction method considering traffic density and traffic signal phase information is established. Secondly, according to the vehicle driving energy consumption model, the objective function of economic speed planning is established, and the traffic speed interval under different driving conditions is taken as the dynamic constraint condition, and the optimal control problem model of vehicle economic speed planning under urban road conditions is established; Then, the optimal control problem of vehicle economic speed is transformed into a model predictive control problem, and the DP algorithm is used to solve the optimal control sequence in each predictive domain, and the optimal speed sequence is planned by cyclic rolling optimization. Finally, through simulation and experimental verification, the results show that the method proposed in this paper can not only achieve all-green traffic at signal intersections, but also achieve good energy-saving effect, and the planning algorithm has fast calculation speed. [ABSTRACT FROM AUTHOR] |
|
Copyright of Mechanika is the property of Mechanika and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |
