Collision avoidance system

About: Collision avoidance system is a research topic. Over the lifetime, 1788 publications have been published within this topic receiving 23667 citations.

Dual-Mode Forward Collision Avoidance Algorithm Based on Vehicle-to-Vehicle (V2V) Communication

Abstract: This paper proposes a Vehicle-to-Vehicle (V2V) communication-based forward collision avoidance algorithm by alarming the driver for the normal driver mode and controlling the driving wheel for the self-governed (autonomous) driving mode. The proposed algorithm benefits from the information exchange between the host vehicle and the leading vehicle to calculate the safe distance between host vehicle and leading vehicle to guarantee the avoidance of the collision. The proposed system gives advisory and imminent warnings according to the predicted accident levels, using a three different levels of collision avoidance for the driver mode. Also, in the autonomous driving mode, it follows an alternative optimal path to avoid the collision. The simulation results are implemented using Prescan and MATLAB. The simulation results show that the proposed collision avoidance system makes a composite analysis of the collision risk and provides an accurate real-time warning and an alternative path for dual driving modes.

Collision Avoidance System for Collaborative Robotics

Abstract: In this paper a real-time collision avoidance algorithm, based on the method of artificial potentials an intended for collaborative robotics applications was studied. Within this work, the movements of a person are detected and acquired by a vision system and a dummy, developed to interact with a robot in a simulated workspace, replicates these actions. Ellipsoids are then defined to entirely include several parts of the dummy and the end-effector of the robot. The minimum distance between the ellipsoids of the dummy and the one of the end-effector is the input of the collision avoidance algorithm. The results of tests are presented to show the effectiveness of the algorithm. Finally, the influence of the velocity of the obstacle on the capability of the algorithm of ensuring safe collision avoidance is analyzed.

Collision avoidance system with cooperative adaptive cruise control in highway entrance ramp environment

Abstract: Although efforts have been done to solve collision avoidance using either environment recognition sensors or vehicle-to-vehicle (V2V) communication information, it is still a challenging problem in some specific scene, e.g. highway entrance ramp. In this paper, we propose a new cooperative adaptive cruise control (CACC) method which combines information of environment recognition sensors and V2V communication. A collision detection system of CACC will work based on the information of V2V communication before environment recognition sensors detecting obstacles accurately. Co-simulation experiment using PreScan and Simulink is conducted. The experimental results show that the intelligent vehicle with our method can pass the freeway entrance ramp more safely.

Bayesian-Monte Carlo Model for Collision Avoidance System Design of Cognitive Connected Vehicle

Abstract: Cognitive connected vehicles will require a number of essential features, including collision avoidance advice and adaptive longitudinal control Their design should integrate intelligent technology and human factors This paper describes a self-calibrating adaptive model for aiding the design of a warning system for preventing rear and side swipe collisions The cognitive vehicle is expected to have the capability of information on location and distance between vehicles obtained on-line In off-line research, such information is obtainable from off-line simulation devices The location and distance information is used in association with a Monte Carlo simulation and Bayesian decision model to identify pre-crash conditions Here, the case of human control is covered and the system provides advice for avoiding rear or side swipe accidents while minimizing false alarms The model structure and algorithm are presented and an illustrative example of a distracted driver is provided The crash warning system is mainly intended for on-line use in actual driving conditions Also, it can be used in driving simulators for off-line safety and traffic flow studies in association with microsimulators of traffic