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.

A Vehicle Safety Distance Model for Collision Avoidance System Based on Emergency Lane Change Motion

Abstract: As the basis of determining the safe driving situation of the vehicle,and the fundamental of active risk avoidance control,the determination of the safety distance is one crucial part of the automotive collision warning/collision avoidance(CW/CA) system.Based on the optimal trajectory planning strategy,an obstacle avoidance solution was proposed by means of longitudinal velocity adjusting and emergency lane change movement.The safety distance model based on emergency lane-change vehicle motion was put forward,and the influence from the different vehicle speed adjusting time on vehicle trajectory and safety distance was analyzed.The validity of the model was demonstrated by the simulation results for statistics obstacle avoidance situation.

Research on autonomic collision avoidance method for UAV

Abstract: For the collision avoidance problem which relates to the Unmanned Aerial Vehicle's(UAV) safety,an autonomic collision avoidance method based on an optimization theory is proposed.By analyzing the process of the UAV autonomic collision avoidance,the integrated autonomic collision avoidance system for UAV is established;the collision avoidance methods in different phases of the system are analyzed,and then the three dimensional,on-line collision prediction and collision avoidance method is proposed based on the optimization theory.Finally the avoidance strategy is translated into the maneuver control commands for the UAV collision avoidance.Simulations verify the effectiveness of the proposed method.

Safety-critical scenarios and virtual testing procedures for automated cars at road intersections

Abstract: This thesis addresses the problem of road intersection safety with regard to a mixed population of automated vehicles and non-automated road users. The work derives and evaluates safety-critical scenarios at road junctions, which can pose a particular safety problem involving automated cars. A simulation and evaluation framework for car-to-car accidents is presented and demonstrated, which allows examining the safety performance of automated driving systems within those scenarios. Given the recent advancements in automated driving functions, one of the main challenges is safe and efficient operation in complex traffic situations such as road junctions. There is a need for comprehensive testing, either in virtual testing environments or on real-world test tracks. Since it is unrealistic to cover all possible combinations of traffic situations and environment conditions, the challenge is to find the key driving situations to be evaluated at junctions. Against this background, a novel method to derive critical pre-crash scenarios from historical car accident data is presented. It employs k-medoids to cluster historical junction crash data into distinct partitions and then applies the association rules algorithm to each cluster to specify the driving scenarios in more detail. The dataset used consists of 1,056 junction crashes in the UK, which were exported from the in-depth On-the-Spot database. The study resulted in thirteen crash clusters for T-junctions, and six crash clusters for crossroads. Association rules revealed common crash characteristics, which were the basis for the scenario descriptions. As a follow-up to the scenario generation, the thesis further presents a novel, modular framework to transfer the derived collision scenarios to a sub-microscopic traffic simulation environment. The software CarMaker is used with MATLAB/Simulink to simulate realistic models of vehicles, sensors and road environments and is combined with an advanced Monte Carlo method to obtain a representative set of parameter combinations. The analysis of different safety performance indicators computed from the simulation outputs reveals collision and near-miss probabilities for selected scenarios. The usefulness and applicability of the simulation and evaluation framework is demonstrated for a selected junction scenario, where the safety performance of different in-vehicle collision avoidance systems is studied. The results show that the number of collisions and conflicts were reduced to a tenth when adding a crossing and turning assistant to a basic forward collision avoidance system. Due to its modular architecture, the presented framework can be adapted to the individual needs of future users and may be enhanced with customised simulation models. Ultimately, the thesis leads to more efficient workflows when virtually testing automated driving at intersections, as a complement to field operational tests on public roads.

Collision avoidance system and method

Abstract: A collision avoidance system for sensing a presence of objects within a critical distance is provided. The system comprises a collision avoidance array disposed on a face of the system component, the collision avoidance array comprising a plurality of plates configured to detect a presence of objects and generate a corresponding electrical signal. In addition, the system further comprises a multiplexer configured to selectively couple the plurality of plates to a sensing circuit. The sensing circuit configured to sense the electrical signal and generate a corresponding electric field around the collision avoidance array to prevent the object from colliding with the system sub-component.

Adjustable object avoidance proximity threshold based on presence of propeller guard(s)

Abstract: Various embodiments include methods, devices, and aerial robotic vehicles for adjusting a proximity threshold implemented in a collision avoidance system based on whether propeller guards are installed. Methods may include an aerial robotic vehicle processor determining whether a propeller guard is installed, setting, a proximity threshold for collision avoidance based on the determination as to whether propeller guard(s) is/are installed on the aerial robotic vehicle, and controlling one or more motors of the aerial robotic vehicle using the proximity threshold for collision avoidance. When propeller guards are installed, the proximity threshold may be set at a smaller distance than when propeller guards are not installed. The determination of whether a propeller guard is installed may be based on sensor data from one or more sensors configured to detect or indicate the presence of a propeller guard, and/or based on rotor revolution rates determined from a motor or motor controller.