Modeling Evaluation of Eco–Cooperative Adaptive Cruise Control in Vicinity of Signalized Intersections

Author:

Ala Mani Venkat1,Yang Hao2,Rakha Hesham13

Affiliation:

1. Charles E. Via, Jr., Department of Civil and Environmental Engineering, College of Engineering, 200 Patton Hall, Blacksburg, VA 24061

2. Department of Civil and Environmental Engineering, College of Engineering, Lamar University, 2622 Cherry Engineering Building, Beaumont, TX 77710

3. Virginia Tech Transportation Institute, Virginia Polytechnic Institute and State University, 3500 Transportation Research Plaza, Blacksburg, VA 24061

Abstract

Vehicle stops caused by traffic signals reduce vehicle fuel economy ratings along arterial roadways. Eco–cooperative adaptive cruise control (eco-CACC) systems are being developed in an attempt to improve vehicle fuel efficiency in the vicinity of signalized intersections. These eco-CACC systems utilize traffic signal phasing and timing data received through vehicle-to-infrastructure communication, together with vehicle queue predictions, to compute fuel-optimum vehicle trajectories that are continuously updated as the vehicle travels in the vicinity of signalized intersections. The algorithm computes a desired speed for the vehicle that is either displayed to the driver or directly integrated into the vehicle’s adaptive cruise control system. In this paper, the INTEGRATION microscopic traffic assignment and simulation software is used to evaluate the performance of a proposed eco-CACC algorithm to assess its networkwide energy and environmental impacts. A simulation sensitivity analysis demonstrates that as the market penetration rate of CACC-equipped vehicles increases, the energy and environmental benefits also increase, and that the overall savings in fuel consumption are as high as 19% when the market penetration rate is 100%. On multilane roads, the algorithm may produce networkwide increases in the fuel consumption level when the market penetration rate is less than 30%. The analysis also demonstrates that the length of control segments, the signal phasing and timing plan, and the traffic demand levels significantly affect the algorithm performance. The study further demonstrates that the algorithm may produce increases in fuel consumption levels when the network is oversaturated; thus, further work is needed to enhance the algorithm for these conditions.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 21 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Eco-driving strategy for connected vehicles at signalized intersections considering human driver error;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2023-09-19

2. Optimization of Vehicle Trajectories Considering Uncertainty in Actuated Traffic Signal Timings;IEEE Transactions on Intelligent Transportation Systems;2023-07

3. Ecological Cooperative Adaptive Control of Connected Automate Vehicles in Mixed and Power-Heterogeneous Traffic Flow;Electronics;2023-05-09

4. Energy-Optimal Speed Control for Autonomous Electric Vehicles Up- and Downstream of a Signalized Intersection;World Electric Vehicle Journal;2023-02-17

5. A Speed Guidance Strategy for Connected Autonomous Vehicle at Signalized Intersection;2022 IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE);2022-11-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3