共享网约车和自动驾驶出租车服务综述

IF 3.3 2区 工程技术 Q2 TRANSPORTATION Transportmetrica B-Transport Dynamics Pub Date : 2022-06-28 DOI:10.1080/21680566.2022.2092231
Weiliang Zeng, Miaosen Wu, Peng Chen, Zhiguang Cao, Shengli Xie
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Review of shared online hailing and autonomous taxi services
As the technology of autonomous vehicle develops, online hailing autonomous taxi system is regarded as one of the most popular public transportation services in the future. Studies related to demand forecasting, ride matching, path planning, relocation, and pricing strategy for shared online hailing and autonomous taxi services have emerged in recent years. In this study, we conducted a survey based on 141 representative literatures from 1995 to 2022 to understand the state-of-the-art of the key problems of operating autonomous taxi service. First, a comprehensive review of the components of the shared autonomous taxi modelling is presented. Then, how the emerging technologies such as internet of vehicles, big data, cloud and edge computing, and blockchain can be used to enhance the autonomous taxi service is discussed. Last, the current research challenges and the concern or hurdle in public’s adoption of autonomous taxi services are identified.
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来源期刊
Transportmetrica B-Transport Dynamics
Transportmetrica B-Transport Dynamics TRANSPORTATION SCIENCE & TECHNOLOGY-
CiteScore
5.00
自引率
21.40%
发文量
53
期刊介绍: Transportmetrica B is an international journal that aims to bring together contributions of advanced research in understanding and practical experience in handling the dynamic aspects of transport systems and behavior, and hence the sub-title is set as “Transport Dynamics”. Transport dynamics can be considered from various scales and scopes ranging from dynamics in traffic flow, travel behavior (e.g. learning process), logistics, transport policy, to traffic control. Thus, the journal welcomes research papers that address transport dynamics from a broad perspective, ranging from theoretical studies to empirical analysis of transport systems or behavior based on actual data. The scope of Transportmetrica B includes, but is not limited to, the following: dynamic traffic assignment, dynamic transit assignment, dynamic activity-based modeling, applications of system dynamics in transport planning, logistics planning and optimization, traffic flow analysis, dynamic programming in transport modeling and optimization, traffic control, land-use and transport dynamics, day-to-day learning process (model and behavioral studies), time-series analysis of transport data and demand, traffic emission modeling, time-dependent transport policy analysis, transportation network reliability and vulnerability, simulation of traffic system and travel behavior, longitudinal analysis of traveler behavior, etc.
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