Collision avoidance

About: Collision avoidance is a research topic. Over the lifetime, 8014 publications have been published within this topic receiving 111414 citations.

A method of vehicle motion prediction and collision risk assessment with a simulated vehicular cyber physical system

Abstract: Vehicular cyber physical system (VCPS) can comprehensively acquire road traffic safety related information, and provide drivers with early warning or driving assistance in emergency, in order to assist them avoid vehicle crash in the driving process. Literature review shows that previous studies mainly rely on observed vehicle motion/location data for assessing vehicle collision risk, where predicted vehicle motion/location, driver behavior and road geometry (e.g., curvature) are rarely considered. In this study, based on the simulated VCPS, a collision avoidance system that can explicitly consider the above issues is designed and presented in detail. Within the proposed collision avoidance system, an assessment method, which can predict collision risk by comprehensively considering vehicles motion/location, driver behavior and road geometry information from the VCPS, is developed. Firstly, the short-term motion of the objective vehicle and surrounding vehicles are predicted based on the Kalman Filter (KF) algorithm and the vehicle motion model. Furthermore, the proposed method that can explicitly take driver behavior and road curvature into account is used to predict vehicle location and calculate the traveled distance among vehicles in real-time. Then, the predicted vehicle gaps are compared with a safe distance threshold and the vehicle collision risk is predicted. Finally, the accuracy of the proposed collision risk assessment method is examined with a receiver operating characteristic (ROC) curve analysis over a section of curved road. Simulation results show that the proposed method is effective for detecting collision risk and providing accurate warnings in a timely fashion.

Vehicle collision avoidance system

Abstract: An automatically guided vehicle (110) is disclosed which follows guide lines positioned in a predetermined guide path (102) on the floor. The guide path (102) includes coded markings and the vehicle comprises sensing circuitry (210) capable of sensing the markings and generating proximity signals indicative thereof. The coded markings can indicate approach of the vehicle into a "congestion" zone wherein other vehicles similarly situated can cause hazardous conditions therein. Radio frequency (RF) transmission circuitry (240) on the approaching vehicle (110) is responsive to the congestion zone indication signals to transmit and receive RF signals to and from other vehicles on the guide path (102). The approaching vehicle (110) performs various collision avoidance operations as determined by the received RF signals.

Design and experimental study of an ultrasonic sensor system for lateral collision avoidance at low speeds

Abstract: In this study, we-design and implement an ultrasonic sensor system for lateral collision avoidance of vehicles at low speeds The developed sensor system is useful for detecting vehicles, motorcycles, bicycles and pedestrians that pass by the lateral side of a vehicle The system can be adopted to enhance the rear-view mirrors of present vehicles, which have blind spots on the lateral sides Ultrasonic sensors, which have been widely used on cars for rear object detection during parking, are developed for lateral object detection at low speeds Detailed experimental studies are presented in this paper Experimental results show that the proposed system can detect a vehicle at speeds up to 40 km/hr with a maximum range of 6 meters Moreover, the influence of wind on the measurement is also investigated The developed sensor system gives satisfactory results for a wind speed up to 35 km/hr

Stereo-vision based imminent collision detection

Abstract: A stereo vision based collision avoidance systems having stereo cameras that produce imagery that is processed to produce a depth map of a scene. A potential threat is detected in the depth map. The size, position, and velocity of the detected potential threat are then estimated, and a trajectory analysis of the detected potential threat is determined using the estimated position and the estimated velocity. A collision prediction based on the trajectory analysis is determined, and then a determination is made as to whether a collision is imminent based on the collision prediction and on the estimated size of the potential threat.