中文核心期刊
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重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2021, Vol. 40 ›› Issue (08): 7-14.DOI: 10.3969-j.issn.1674-0696.2021.08.02

• 交通+大数据人工智能 • 上一篇    下一篇

自动驾驶混合交通流的交通和环境效益评估

胡明伟1,2,3，施小龙1，翟素云4,刘鹏1   

  1. (1. 深圳大学 土木与交通工程学院，广东 深圳 518060；2. 深圳大学 滨海城市韧性基础设施教育部重点实验室， 广东 深圳 518060； 3. 深圳大学 未来地下城市研究院，广东 深圳 518060； 4. 弘达交通咨询（深圳）有限公司，广东 深圳 518060)
  • 收稿日期:2020-03-18 修回日期:2020-09-15 出版日期:2021-08-20 发布日期:2021-08-25
  • 作者简介:胡明伟(1972—)，男，广东深圳人，教授，博士，主要从事智能交通方面的研究。E-mail：humw@szu.edu.cn
  • 基金资助:
    中国工程科技发展战略广东研究院2020年咨询研究项目（2020-GD-04-1-1）；中国工程科技发展战略广东研究院2019年咨询研究项目（2019-GD-03）

Evaluation of Traffic and Environmental Benefits for the Mixed Traffic Flow of Autonomous Vehicles

HU Mingwei1,2,3, SHI Xiaolong1, ZHAI Suyun4, LIU Peng1   

  1. (1.College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, Guangdong, China; 2.Key Laboratory of Coastal Urban Resilient Infrastructures, Shenzhen University, Ministry of Education, Shenzhen 518060, Guangdong, China; 3. Underground Polis Academy, Shenzhen University, Shenzhen 518060, Guangdong, China; 4.MVA Transport Consultants (Shenzhen) Co., Ltd., Shenzhen 518060, Guangdong, China)
  • Received:2020-03-18 Revised:2020-09-15 Online:2021-08-20 Published:2021-08-25

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摘要： 为研究自动驾驶混合交通流的交通和环境效益，利用VISSIM微观仿真模型和MOVES机动车尾气排放模型，搭建一套基于自动驾驶车辆的驾驶行为的综合仿真体系，对不同市场渗透率的自动驾驶车辆运行过程进行仿真模型研究。考虑不同交通流水平（高峰期、平峰期、低峰期），选用总出行时间、平均速度、平均停车次数和平均延误4个交通效益评估指标，PM2.5、NOx、CO污染物排放量和能源消耗量4个环境效益评估指标。研究结果表明：随着自动驾驶车辆市场渗透率的递增，混合交通流的交通和环境效益均呈递增趋势，且高峰期优于平峰期，平峰期优于低峰期；以交通效益为例，在高峰期时，当自动驾驶车辆的占比达到100%，可降低45.59%的总出行时间、98.77%的停车次数和96.46%的平均延误，提升122.73%的平均旅行速度；在平峰期时，可降低84.43%的平均延误和86.42%的停车次数；而在低峰期时，只降低了1.62%的总出行时间，提升了1.03%的平均旅行速度。

关键词: 交通运输工程；自动驾驶车辆；混合交通流；VISSIM；MOVES；交通效益；环境效益

Abstract: In order to explore traffic and environmental benefits of the mixed traffic flow of autonomous vehicles, a comprehensive simulation system of driving behavior based on autonomous vehicle was established by use of microscopic traffic simulation tool VISSIM and MOVES emission model. The simulation model of the operation process of autonomous vehicles with different market penetration rate was studied. Considering different traffic flow levels (peak period, flat peak period and low peak period), total travel time, average speed, average parking times and average delay were selected as traffic benefit evaluation indexes, and PM2.5, NOx, CO emission and energy consumption were selected as environmental benefit evaluation indexes. The research results show that the traffic and environmental benefits of the mixed traffic flow increase with the market penetration rate rising of the autonomous vehicles. Moreover, the traffic and environmental benefits during peak period is better than those during flat peak period; the traffic and environmental benefits during flat peak period is better than those during low peak period. Taking traffic benefits as an example, in peak period, when the proportion of autonomous vehicles reaches 100%, the total travel time can be reduced by 45.59%, the number of stops can be reduced by 98.77%, the average delay can be reduced by 96.46%, and the average travel speed can be increased by 122.73%. During the flat peak period, the average delay can be reduced by 84.43% and the number of stops can be reduced by 86.42%; during the low peak period, the total travel time is only reduced by 1.62% and the the average travel speed is increased by 1.03%.

Key words: traffic and transportation engineering; autonomous vehicles; mixed traffic flow; VISSIM; MOVES; traffic benefit; environmental benefit

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