Research on longitudinal control algorithm for intelligent automatic driving

2021 ◽  
Author(s):  
Rong Xie ◽  
Xiaosen Tian ◽  
Qingyu Zhang ◽  
Xia Pan
Keyword(s):  
Control Algorithm ◽  
Longitudinal Control ◽  
Automatic Driving

Implementation and vehicle tests of a vehicle stop-and-go cruise control system

2002 ◽  
Vol 216 (7) ◽  
pp. 537-544 ◽  
Author(s):  
K Yi ◽  
N Ryu ◽  
H J Yoon ◽  
K Huh ◽  
D Cho ◽  
...  
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Speed Control ◽  
Step Motor ◽  
Cruise Control ◽  
Longitudinal Control ◽  
Linear Quadratic Optimal Control ◽  
Millimetre Wave ◽  
Stop And Go ◽  
Wave Radar

Implementation and vehicle tests of a vehicle longitudinal control algorithm for stop-and-go cruise control have been performed. The vehicle longitudinal control scheme consists of a set-speed control algorithm, a speed control algorithm, and a distance control algorithm. A desired acceleration for the vehicle for the control of vehicle-to-vehicle relative speed and clearance has been designed using linear quadratic optimal control theory. Performance of the control algorithm has been investigated via vehicle tests. Vehicle tests have been conducted using two test vehicles. A 2000 cm3 passenger car equipped with a radar distance sensor, throttle/brake actuators and a controller has been used as a subject vehicle in the vehicle tests. A millimetre wave radar sensor has been used for distance measurement. A step motor and an electronic vacuum booster have been used for throttle/brake actuators. It has been shown that the implemented vehicle longitudinal control system can provide satisfactory performance in vehicle set-speed control and vehicle clearance control at lower speeds.

scholarly journals Shockwave-Based Automated Vehicle Longitudinal Control Algorithm for Nonrecurrent Congestion Mitigation

2017 ◽  
Vol 2017 ◽  
pp. 1-10
Author(s):  
Liuhui Zhao ◽  
Joyoung Lee ◽  
Steven Chien ◽  
Cheol Oh
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Control Algorithm ◽  
Continuous Wavelet ◽  
Market Penetration ◽  
Longitudinal Control ◽  
Automated Vehicle ◽  
Vehicular Speed ◽  
Simulation Results ◽  
Improved Accuracy

A shockwave-based speed harmonization algorithm for the longitudinal movement of automated vehicles is presented in this paper. In the advent of Connected/Automated Vehicle (C/AV) environment, the proposed algorithm can be applied to capture instantaneous shockwaves constructed from vehicular speed profiles shared by individual equipped vehicles. With a continuous wavelet transform (CWT) method, the algorithm detects abnormal speed drops in real-time and optimizes speed to prevent the shockwave propagating to the upstream traffic. A traffic simulation model is calibrated to evaluate the applicability and efficiency of the proposed algorithm. Based on 100% C/AV market penetration, the simulation results show that the CWT-based algorithm accurately detects abnormal speed drops. With the improved accuracy of abnormal speed drop detection, the simulation results also demonstrate that the congestion can be mitigated by reducing travel time and delay up to approximately 9% and 18%, respectively. It is also found that the shockwave caused by nonrecurrent congestion is quickly dissipated even with low market penetration.

Derivation and Evaluation of a Poincare-Bendixson Theorem Based Target Acceleration Computation Algorithm for Autonomous Driving on Inverse TTC and Time Headway Plane

2020 ◽  
Author(s):  
Hye-Won Lee ◽  
Kwang-Seok Oh ◽  
Young-Min Yoon ◽  
Kyong-Su Yi
Keyword(s):  
Real Time ◽  
Control Algorithm ◽  
Human Factor ◽  
Autonomous Vehicle ◽  
Autonomous Driving ◽  
Longitudinal Control ◽  
Time To Collision ◽  
Time Headway ◽  
Target Acceleration ◽  
Computation Algorithm

Abstract This paper describes derivation algorithm and evaluation results of a Poincare-Bendixson theorem based target acceleration computation algorithm for autonomous driving on inverse time to collision and time headway plane. Derivation of target acceleration is needed for longitudinal autonomous driving. Ellipsoidal driving area is derived for considering driver’s driving characteristic and safety in time headway-inverse time to collision (TTC) plane. And target acceleration computation algorithm has been proposed based on Poincare-Bendixson theorem. Ellipsoidal driving areas are divided main driving area and real-time driving area. Main driving area is derived based on limit of inverse TTC and time headway for takeover time and human factor, real-time driving area is derived through current driving point with ratio of main driving area. It is designed to computation the target acceleration after deriving the target direction by applying a specific angle based on the normal to the current driving point through the real-time driving area. Specific angle is arbitrary value applied acceleration limitation of actual vehicle. The performance evaluation of target acceleration computation algorithm is has been conducted in Matlab/Simulink environment. It is expected that the proposed algorithm can be used for longitudinal control algorithm for safety and personalization of autonomous vehicle.

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