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Automated Vehicle Control and Sensing Technology

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Prof. Dr. Timothy Gordon

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Guest Editor

School of Engineering, University of Lincoln, Lincoln LN6 7TS, UK
Interests: vehicle control systems; vehicle dynamics; active safety; collision avoidance; autonomous systems including self-driving cars
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Prof. Dr. Jun Wang

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Guest Editor

College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
Interests: autonomous driving; vehicle dynamics; sensing and fusion; planning and control

Special Issue Information

Dear Colleagues,

This Special Issue welcomes the submission of new research and review articles related to automated and autonomous ground vehicles. The emphasis is on bridging critical gaps leading to real-world implementation, “making the dream a reality” in the next few years. The Special Issue is open to a wide range of topics on vehicle automation: guidance and control, sensor technology, sensor systems, redundancy and data security, collision avoidance, safety, V2X communications, etc. Contributions relating to overall system design and operation are also of interest, including niche applications such as self-parking, racing, freight operations, construction vehicles, etc.

Prof. Dr. Timothy Gordon
Prof. Dr. Jun Wang
Guest Editors

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Keywords

automated and autonomous vehicles
integrated vehicle control
localization
sensor fusion
vehicle guidance
collision avoidance

Published Papers (1 paper)

Research

16 pages, 4140 KiB

Open AccessArticle

Intersection Vehicle Turning Control for Fully Autonomous Driving Scenarios

by Zhizhong Ding, Chao Sun, Momiao Zhou, Zhengqiong Liu and Congzhong Wu

Sensors 2021, 21(12), 3995; https://doi.org/10.3390/s21123995 - 09 Jun 2021

Cited by 8 | Viewed by 2829

Abstract

Currently the research and development of autonomous driving vehicles (ADVs) mainly consider the situation whereby manual driving vehicles and ADVs run simultaneously on lanes. In order to acquire the information of the vehicle itself and the environment necessary for decision-making and controlling, the ADVs that are under development now are normally equipped with a lot of sensing units, for example, high precision global positioning systems, various types of radar, and video processing systems. Obviously, the current advanced driver assistance systems (ADAS) or ADVs still have some problems concerning high reliability of driving safety, as well as the vehicle’s cost and price. It is certain, however, that in the future there will be some roads, areas or cities where all the vehicles are ADVs, i.e., without any human driving vehicles in traffic. For such scenarios, the methods of environment sensing, traffic instruction indicating, and vehicle controlling should be different from that of the situation mentioned above if the reliability of driving safety and the production cost expectation is to be improved significantly. With the anticipation that a more sophisticated vehicle ad hoc network (VANET) should be an essential transportation infrastructure for future ADV scenarios, the problem of vehicle turning control based on vehicle to everything (V2X) communication at road intersections is studied. The turning control at intersections mainly deals with three basic issues, i.e., target lane selection, trajectory planning and calculation, and vehicle controlling and tracking. In this paper, control strategy, model and algorithms are proposed for the three basic problems. A model predictive control (MPC) paradigm is used as the vehicle upper layer controller. Simulation is conducted on the CarSim-Simulink platform with typical intersection scenes. Full article

(This article belongs to the Special Issue Automated Vehicle Control and Sensing Technology)

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