首页|Potential effects of automated driving on vehicle travel demand:A comparison of three case cities

Potential effects of automated driving on vehicle travel demand:A comparison of three case cities

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Automated vehicles(AVs)hold the potential to reduce road accidents,mitigate traffic congestion,and improve travel experience.However,the possible countervailing impacts from the changes in underserved populations'vehicle travel demand tend to be over-looked.To determine the vehicle travel demand changes that resulted from underserved populations aged between 6 and 80,this paper explores the latent effect of AVs on vehicle kilometers traveled(VKT)in a fully AV environment using person trip survey data from the cities of Sanya,Shijiazhuang,and Shenzhen in China.This paper uses the natural decline hypothesis of travel demand and proposes a regression model to investigate the difference among the cities'latent vehicle travel demand.Results show that the average VKT of the overall population in Sanya,Shijiazhuang,and Shenzhen increased by 33.4%,47.0%,and 46.8%,respectively.The analysis of the regression model confirms that the current travel behavior of individuals can affect the degree of increase in their average VKT.Integrating AVs into public transport,increasing the acceptance of automated shared mobility options,transforming road space use type,and prototyping AV designs with various features and needs are potential methods to cope with the countervailing impacts.The total VKT of the overall population increased by approximately 10%-25%depending on the city.The con-clusions of this paper provide informative insights into the evaluation of VKT for under-served populations and contribute to the deployment of AVs to address equity and inclusion issues.

Automated vehiclesVehicle kilometers traveledAging populationTravel behaviorNatural decline hypothesis

Jingchen Dai、Ruimin Li、Zhiyong Liu

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School of Civil Engineering,Tsinghua University,Beijing 100084,China

Hang Lung Center for Real Estate,Tsinghua University,Beijing 100084,China

School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China

国家重点研发计划Tsinghua University-Toyota Research Center Project国家自然科学基金

2019YFB1600100TT-2019-0552302383

2024

交通运输工程学报(英文版)

交通运输工程学报(英文版)

CSTPCD
ISSN:2095-7564
年,卷(期):2024.11(2)
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