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.

Toward Optimal MEC Resource Dimensioning for a Vehicle Collision Avoidance System: A Deep Learning Approach

Abstract: Collision detection and avoidance between vehicles is one of the key services envisioned in the Internet of Vehicles. Such services are usually deployed at the multi-access edge computing (MEC) to ensure low-latency communication and thus guarantee real-time reactions to avoid collisions between vehicles. In order to maximize the coverage of the road and ensure that all vehicles are connected to an optimal MEC host (in terms of geographical location), the collision avoidance application needs to be instantiated on all the MEC hosts. This may add a burden on the computing resources available at the latter. In this article, we propose an AI-empowered framework that aims to optimize the computing resources at the MEC hosts. Our framework uses deep learning to predict the vehicle density to be served by a MEC host and derive the exact computing resources required by the collision detection application to run optimally. We evaluate the proposed framework using a real dataset representing vehicle mobility in a big city. Obtained results show the accuracy of our prediction model, and hence the efficiency of our resources assignment framework to exactly deduce the optimal computing resources needed by each instance of the application.

UAS Collision Avoidance Algorithm Minimizing Impact on Route Surveillance

Abstract: A collision avoidance algorithm is developed and implemented that is applicable to many different unmanned aerial systems ranging from a single platform with the ability to perform all collision avoidance functions independently to multiple vehicles performing functions as a cooperative group with collision avoidance commands computed at a ground station. The algorithm leverages advances in several theoretical fields including robotics, homing guidance, and airspace management, and considers several approaches to conflict detection and resolution including the collision cone approach. The collision avoidance system is exercised and tested using operational hardware and platforms. Novel developments using an aggregated collision cone approach allows each unmanned aircraft to detect and avoid collisions with two or more other aircraft simultaneously. The collision avoidance system is implemented using a miniature unmanned aircraft with an onboard autopilot. Various simulation and flight test cases are used to demonstrate the algorithm’s robustness to different collision encounters at various engagement angles. The flight test results are compared with ideal, software-in-the-loop, and hardware-in-the-loop tests. The results presented are the first known flight tests of a global, three-dimensional, geometric collision avoidance system on an unmanned aircraft system.

Collision avoidance system for snowmobiles

Abstract: A collision avoidance system for snowmobiles includes an array of sensors positioned on a front side of the snowmobile for detecting the presence and location of an approaching obstacle. The sensors include both heat sensors and speed sensors. A control unit is provided for processing signals received from the sensors and outputting audio signals indicative of the detected location of the approaching obstacle. A wireless transmitter transmits the audio signals to a receiver and speaker system contained in a headset or helmet. The speaker system includes left and right speakers contained in the headset or helmet which are adapted to be positioned near or within the driver's left and right ears and provide audible warnings to the driver. The control unit varies a loudness of the audible warnings in the left and right speakers to indicate a direction from which the detected obstacle is approaching.

Self-correcting wavelength collision avoidance system

Abstract: A method includes detecting wavelength collision including identifying a pair or pairs of ONTs that transmit the colliding wavelengths and recovering from collision wherein wavelengths of the pair or pairs of ONTs that cause collisions are re-adjusted to eliminate the collision.

Evaluation of rear-end collision avoidance technologies based on real world crash data

Abstract: Over the last decade, collision avoidance technologies targeting rear-end collisions have been introduced by many vehicle manufacturers. However, evaluation of the real world performance of these systems are rare. The objective of this study was to evaluate the real world effectiveness of systems called Forward Collision Warning and Brake support combined with Adaptive Cruise Control (CWB+ACC). These systems were introduced as optional equipment in Volvo car models in 2006. The data analyzed comes from a detailed, representative dataset based on insurance claims. The rate of rear-end frontal collisions was compared for cars with and without CWB+ACC, controlling for different generations of CWB+ACC as well as presence of Low-speed Emergency Braking functionality. For cars with CWB+ACC, rear-end crashes with frontal impacts were reduced with 38%. Also, the data showed a clear progress in crash avoidance efficiency as a function of CWB+ACC development. For the third generation of CWB+ACC, the estimated collision avoidance effect was 45%. In future studies, the additional safety performance that collision avoidance technologies bring in the form of crash mitigation needs to be investigated.