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.

Real-Time Sonar Classification for Autonomous Underwater Vehicles.

Abstract: : The Naval Postgraduate School autonomous underwater vehicle (AUV) Phoenix did not have any sonar classification capabilities and only a basic collision avoidance system. The Phoenix also did not have the capability of dynamically representing its environment for path planning purposes. This thesis creates a sonar module that handles real time object classification and enables collision avoidance at the Tactical level. The sonar module developed communicates directly with the available sonar and preprocesses raw data to a range - bearing data pair. The module then processes the range - bearing data using parametric regression to form line segments. A polyhedron building algorithm combines line segments to form objects and classifies them based on their attributes. When the Phoenix is transiting, the classifying algorithm detects collision threats and initiates collision avoidance procedures. The result of this thesis is a fully implemented sonar module on the Phoenix. This module was tested in a virtual world, test tank and in the first ever sea-water testing of the Phoenix. The sonar module has demonstrated real time sonar classification, run time collision avoidance and the ability to dynamically update the representation of the unknown environment. The sonar module is a forked process written in the 'C' language, functioning at the Tactical level. Source code and output from an actual Phoenix mission displaying the object classification of the sonar module are included.

Use of Fuzzy technique for Calculating Degree of Collision Risk in Obstacle Avoidance of Unmanned Underwater Vehicles

Abstract: This paper introduces a technique for calculating the degree of collision risk used in collision avoidance system of AUVs. The collision risk will be reckoned with the fuzzy inference, which uses TCPA(Time of the Closest Point of Approach) and DCPA(Distance of the Closest Point of Approach) as factors. A method to obtain TCPA and DCPA for 3-dimension is suggested. The degree of collision risk is provided to collision avoidance system, and is verified the effectiveness through simulation.

Collision Detection Algorithm of Successive Frames for Automated Air Traffic Control

Abstract: The existing collision detection techniques have not addressed the problem of detecting collisions of very fast moving objects involving situations where the instance of collisions may not even be visible to the eyes, occurring between two frames For this purpose a simple and novel approach have been devised This is based on the assumption that if two objects pass through the same region in a sufficiently small time window, then we should consider that they have collided Mathematically this translates into linking the scene geometry of two successive time frames by taking the convex hull of vertex locations of an object at two successive frames The inter-flame collision detection method in this paper can easily be adapted for determining possible time and/or distance to collision between airplanes

Research on Collision Risk in Free Flight Based on Fuzzy Stochastic Differential Equations

Abstract: It was held by the authors that free flight was an effective way to solve the crowed air traffic,so research on the collision risk in free flight environment was particularly important.A model for collision risk in free flight was built using random differential equations with the effects of communication navigation and surveillance(CNS) system performance,human factors and collision avoidance system performance on the risk taken into account.Fuzzy sets of intensity values of the above three random factors were introduced.A rapid method for solving the differential equations was worked out after Runge-Kutta method.The example shows that the collision probability decreases with the increase in the minimum safe distance,and that the model is credible.

The virtual bumper: a control based collision avoidance system for highway vehicles

Abstract: This report summarizes research on a new collision avoidance strategy, the virtual bumper. The research involves development and simulation testing of the virtual bumper, a two-dimensional control strategy that provides steering, throttle, and braking actuation to maneuver a vehicle in a dynamic environment with the goal of avoiding obstacles and other vehicles. The concept applies to both normal and emergency driving conditions. Under all circumstances, the virtual bumper incorporates vehicle dynamic limits to ensure that the control commands are within safe levels. The virtual bumper will attempt to avoid a collision and will, at least, minimize the magnitude of an unavoidable collision. To test the functionality of the virtual bumper, researchers evaluated several driving scenarios. The scenarios consider both normal driving situations and emergency driving conditions. The normal driving scenarios demonstrated that the control algorithm operates the vehicle similar to the way a human would. This is important because a comfortable and predictable (i.e., intuitive) system response is required for achieving driver acceptance. The emergency scenarios demonstrated that the strategy is capable of reacting appropriately while maintaining safe acceleration/deceleration levels for the vehicle. This evaluation showed that the virtual bumper can provide safe vehicle control for a broad range of driving situations.