Topic
Collision avoidance
About: Collision avoidance is a research topic. Over the lifetime, 8014 publications have been published within this topic receiving 111414 citations.
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TL;DR: In this article, a distributed and real-time anti-collision decision support formulation is proposed for collision avoidance in a multi-ship encounter scenario, where the initial decision on collision avoidance by course alteration or speed changing is made according to the encounter situation between own ship and target ships.
144 citations
25 Oct 2012
TL;DR: A new tool for optimizing the movements of autonomous vehicles through intersections: iCACC, to control vehicle trajectories using Cooperative Adaptive Cruise Control systems to avoid collisions and minimize intersection delay.
Abstract: Recently several artificial intelligence labs have suggested the use of fully equipped vehicles with the capability of sensing the surrounding environment to enhance roadway safety. As a result, it is anticipated in the future that many vehicles will be autonomous and thus there is a need to optimize the movement of these vehicles. This paper presents a new tool for optimizing the movements of autonomous vehicles through intersections: iCACC. The main concept of the proposed tool is to control vehicle trajectories using Cooperative Adaptive Cruise Control (CACC) systems to avoid collisions and minimize intersection delay. Simulations were executed to compare conventional signal control with iCACC considering two measures of effectiveness - delay and fuel consumption. Savings in delay and fuel consumption in the range of 91 and 82 percent relative to conventional signal control were demonstrated, respectively.
143 citations
31 Oct 2000
TL;DR: This paper presents a new real-time collision avoidance approach for mobile robots that performs a high level information extraction and interpretation of the environment and uses this information to generate the motion commands.
Abstract: This paper presents a new real-time collision avoidance approach for mobile robots. The nearness diagram method (ND) performs a high level information extraction and interpretation of the environment. Subsequently, this information is used to generate the motion commands. The proposed approach is well-suited to deal with unknown, unstructured and dynamic environments, where problems of other approaches are avoided. Some experimental results are shown using an holonomic mobile base to demonstrate the usefulness of the method.
142 citations
09 Oct 2006
TL;DR: This paper gives a survey of recent research on pedestrian collision avoidance systems and reviews various approaches based on cues such as shape, motion, and stereo used for detecting pedestrians from visible as well as non-visible light sensors.
Abstract: This paper gives a survey of recent research on pedestrian collision avoidance systems. Collision avoidance not only requires detection of pedestrians, but also collision prediction using pedestrian dynamics and behavior analysis. The paper reviews various approaches based on cues such as shape, motion, and stereo used for detecting pedestrians from visible as well as non-visible light sensors. This is followed by the study of research dealing with probabilistic modeling of pedestrian behavior for predicting collisions between pedestrian and vehicle. The literature review is also condensed in tabular form for quick reference
142 citations
TL;DR: In this paper, a new approach to path planning in dynamic environments based on Ant Colony Optimisation (ACO) is presented, which can be applied in decision support systems on board a ship or in an intelligent obstacle detection and avoidance system, which constitutes a component of Unmanned Surface Vehicle (USV) Navigation, Guidance and Control systems.
Abstract: Swarm Intelligence (SI) constitutes a rapidly growing area of research. At the same time trajectory planning in a dynamic environment still constitutes a very challenging research problem. This paper presents a new approach to path planning in dynamic environments based on Ant Colony Optimisation (ACO). Assumptions, a concise description of the method developed and results of real navigational situations (case studies with comments) are included. The developed solution can be applied in decision support systems on board a ship or in an intelligent Obstacle Detection and Avoidance system, which constitutes a component of Unmanned Surface Vehicle (USV) Navigation, Guidance and Control systems.
140 citations