Research on Lateral Active Collision Avoidance Algorithms for Intelligent Vehicles

2020 ◽  
pp. 527-541
Author(s):  
Jiaxiang Qin ◽  
Rui He ◽  
Yan Liu ◽  
Weiwen Deng ◽  
Sumin Zhang
Keyword(s):  
Collision Avoidance ◽  
Intelligent Vehicles

Fuzzy Control of Autonomous Intelligent Vehicles for Collision Avoidance Using Integrated Dynamics

2018 ◽  
Vol 11 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Youssef Sabry ◽  
Mahmoud Aly ◽  
Walid Oraby ◽  
Samir El-demerdash
Keyword(s):  
Fuzzy Control ◽  
Collision Avoidance ◽  
Intelligent Vehicles

scholarly journals Usability Analysis of Collision Avoidance System in Vehicle-to-Vehicle Communication Environment

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Cho ◽  
Gyoung-Eun Kim ◽  
Byeong-Woo Kim
Keyword(s):  
Collision Avoidance ◽  
Obstacle Detection ◽  
Intelligent Vehicles ◽  
Control Logic ◽  
Detection Range ◽  
V2v Communication ◽  
Emergency Braking ◽  
Vehicle To Vehicle ◽  
Communication Environment ◽  
Dynamics And Control

Conventional intelligent vehicles have performance limitations owing to the short road and obstacle detection range of the installed sensors. In this study, to overcome this limitation, we tested the usability of a new conceptual autonomous emergency braking (AEB) system that employs vehicle-to-vehicle (V2V) communication technology in the existing AEB system. To this end, a radar sensor and a driving and communication environment constituting the AEB system were simulated; the simulation was then linked by applying vehicle dynamics and control logic. The simulation results show that the collision avoidance relaxation rate of V2V communication-based AEB system was reduced compared with that of existing vehicle-mounted-sensor-based system. Thus, a method that can lower the collision risk of the existing AEB system, which uses only a sensor cluster installed on the vehicle, is realized.

scholarly journals Emergency collision avoidance control strategy based on four-wheel steering and differential braking

2021 ◽  
Author(s):  
Haiqing Li ◽  
Yongfu Li ◽  
Taixiong Zheng ◽  
Jiufei Luo ◽  
Zonghuan Guo
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
Control Strategy ◽  
Tracking Control ◽  
Development Trend ◽  
Path Tracking ◽  
Intelligent Vehicles ◽  
Control Mode ◽  
Avoidance Control ◽  
Driving Stability

Abstract Path tracking control strategy of emergency collision avoidance is the research hotspot for intelligent vehicles, and active four-wheel steering and integrated chassis control such as differential braking are the development trend for the control system of intelligent vehicle. Considering both driving performance and path tracking performance, an active obstacle avoidance controller integrated with four-wheel steering (4WS), active rear steering (ARS) and differential braking control (RBC) based on adaptive model predictive theory (AMPC) is proposed. The designed active obstacle avoidance control architecture is composed of two parts, a supervisor and an MPC controller. The supervisor is responsible for selecting the appropriate control mode based on driving vehicle information and threshold of lateral and roll stability. In addition, a non-linear predict model is employed to obtain the future states of the driving vehicle. Then the AMPC is used to calculate the desired steering angle and differential braking toque when the driving stability indexes exceed the safety threshold. Finally, the proposed collision avoidance path tracking control strategy was simulated under emergency conditions via Carsim-Simulink co-simulation. The results show that the controller based on AMPC can be used to tracking the path of obstacle avoidance and has good performance in driving stability under emergencies.

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