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.

Highlights

  • The research and development of advanced driver assistance systems (ADAS) mainly focus on the oncoming market demand [1]. It is conducted by companies such as Tesla, Google, Baidu, etc., and the traffic situation they envision is usually that of humans driving vehicles, and with autonomous driving vehicles (ADV) or driverless vehicles occurring concurrently on the roads

  • In order to acquire the information of the vehicle itself and the environment, which is necessary for decision-making and controlling, the ADVs under development are normally equipped with a lot of sensing systems, e.g., globe positioning system, lidar, millimeter wave radar, infrared radar, video system or vision system, and so on

  • ADV scenarios where vehicle ad hoc network (VANET) could be expected to be an essential infrastructure of the future transportation system

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Summary

Introduction

The research and development of advanced driver assistance systems (ADAS) mainly focus on the oncoming market demand [1] It is conducted by companies such as Tesla, Google, Baidu, etc., and the traffic situation they envision is usually that of humans driving vehicles, and with autonomous driving vehicles (ADV) or driverless vehicles occurring concurrently on the roads. To improve the driving safety and to reduce the production cost, in such scenarios, the way of environment sensing, traffic instruction indicating and vehicle controlling might be different from what is used in current ADAS or ADV. Propose an approach to the problem of controlling the turning maneuver at intersections for ADV scenarios, which is based on V2X communication instead of various sensing systems, such as lidar, millimeter radar, and video system.

Related Work
Turning for ADV
Driving
Target Lane Selection
Trajectory Planning and Calculation
Maximum Speed of Turning Vehicle
Acceleration Model of Turning Vehicle
Vehicle Controlling and Tracking
Results
Target
Verify the Effectiveness
U-turn result:
Test the Performance of the Proposed Method
Method
Conclusions
Full Text
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