A Review of the Impact of Autonomous Driving on Transportation Planning

被引：0
|
作者：
Hu J. [1 ]
Luo S.-Y. [1 ]
Lai J.-T. [1 ]
Xu T. [2 ]
Yang X.-G. [1 ]
机构：
[1] Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai
[2] Transportation Planing and Technology Department, PTV Software Technology Co., Ltd., Karlsruhe
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2021年 / 21卷 / 05期
基金：
国家重点研发计划;
关键词：
Autonomous driving; Land use; Traffic prediction; Transportation network design; Transportation planning; Urban traffic;
D O I：
10.16097/j.cnki.1009-6744.2021.05.006
中图分类号：
学科分类号：
摘要：
As vehicle is an important component of the transportation system, the development and application of autonomous driving is triggering a revolution of the transportation system. This paper focuses on the impact of autonomous driving on transportation planning. By summarizing the technologies, status in quo and prospect of transportation planning, this paper reviews the revolution in data acquisition and management, land use, parking demand, supply-demand analysis, traffic prediction and transportation network design in the environment of autonomous driving. Furthermore, from the perspective of transportation planning, this paper refreshes the understanding of transportation system with consideration of autonomous driving. This paper also proposes novel philosophy and methods of transportation planning, which provide a new analysis framework and research methods for traffic demand forecasting and traffic network design in the environment of autonomous driving. The understanding of transportation system could be refreshed from three aspects. First, traffic data will be more fine-grained and fresh. Second, changes in land use patterns will cause cities to expand and de-industrialize, and the demand for parking will decrease. Third, the supply capacity and reliability of the transportation system will be improved, and greater dispersion will take place in the temporal and spatial distribution of travel demand. Changes in methodologies of the transportation system planning are reflected in two aspects: demand forecasting and traffic network design. First, the framework of demand forecasting will be transformed from a four-step framework to a framework of model combination and travel behavior integration. In addition, in each step of demand forecasting, the characteristics of autonomous driving and its systematic impact should be analyzed. Second, the traffic network design will adopt a continuous-time dependent design framework, which is expected to improve traditional network design by solving the issue of responsive delay. This framework can adapt to and serve the dynamic land use and traffic demand. This study suggests that future research should devote the major efforts to investigating the impact of autonomous driving on traffic safety, congestion, public transit planning and non-motorized transportation planning. In addition, the research difficulties will lay on the following aspects: solving the issue of lacking real-world data of autonomous driving; revealing the mechanism of the transportation operation in the heterogeneous-traffic stage; coping with the situation when demand exceeds supply due to the traffic demand rebound, and evaluating the external costs which are difficult to measure. Copyright © 2021 by Science Press.
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页码：52 / 65and76
页数：6524
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