GPSenseCar -A Collision Avoidance Support System Using Real-Time GPS Data in a Mobile Vehicular Network

2006 ◽  
Author(s):  
Yin-jun Chen ◽  
Ching-chung Chen ◽  
Shou-nian Wang ◽  
Han-en Lin ◽  
Roy C. Hsu
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Support System ◽  
Vehicular Network ◽  
Gps Data

Planning Emergency Manoeuvres

2008 ◽  
Vol 62 (1) ◽  
pp. 79-91 ◽  
Author(s):  
Rafal Szlapczynski
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Real Time ◽  
Collision Avoidance ◽  
Support System ◽  
Visualization Tool ◽  
Collision Risk ◽  
The Real ◽  
Target Behaviour ◽  
Avoidance Manoeuvre

The paper addresses the issue of planning emergency manoeuvres and re-planning ship trajectories in case of unpredicted target behaviour. It introduces two methods. The first is responsible for monitoring other ships parameters, estimating the probability of illegal target behaviour and re-planning own trajectory in case of unpredicted events. The second is a visualization tool that enables the navigator to assess collision risk in an encounter situation and choose a collision avoidance manoeuvre if necessary. This tool is based on the Collision Threat Parameters Area display and offers new features: fuzzy sectors of forbidden speed and course values and the possibility to use any given ship domain. Both methods are fast enough to be applied in the real-time decision-support system.

Pedestrian Oriented Vehicular Collision Avoidance Support System: P-VCASS

2010 ◽  
Vol E93-A (4) ◽  
pp. 679-688 ◽  
Author(s):  
Tomotaka WADA ◽  
Yuki NAKANISHI ◽  
Ryohta YAMAGUCHI ◽  
Kazushi FUJIMOTO ◽  
Hiromi OKADA
Keyword(s):  
Collision Avoidance ◽  
Support System ◽  
System P

Longitudinal and lateral collision avoidance control strategy for intelligent vehicles

2021 ◽  
pp. 095440702110240
Author(s):  
Ziyu Zhang ◽  
Chunyan Wang ◽  
Wanzhong Zhao ◽  
Jian Feng
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Decentralized Control ◽  
Control Strategy ◽  
Centralized Control ◽  
Lateral Control ◽  
Time Performance ◽  
Collision Avoidance Control ◽  
Avoidance Control ◽  
Control Accuracy

In order to solve the problems of longitudinal and lateral control coupling, low accuracy and poor real-time of existing control strategy in the process of active collision avoidance, a longitudinal and lateral collision avoidance control strategy of intelligent vehicle based on model predictive control is proposed in this paper. Firstly, the vehicle nonlinear coupling dynamics model is established. Secondly, considering the accuracy and real-time requirements of intelligent vehicle motion control in pedestrian crossing scene, and combining the advantages of centralized control and decentralized control, an integrated unidirectional decoupling compensation motion control strategy is proposed. The proposed strategy uses two pairs of unidirectional decoupling compensation controllers to realize the mutual integration and decoupling in both longitudinal and lateral directions. Compared with centralized control, it simplifies the design of controller, retains the advantages of centralized control, and improves the real-time performance of control. Compared with the decentralized control, it considers the influence of longitudinal and lateral control, retains the advantages of decentralized control, and improves the control accuracy. Finally, the proposed control strategy is simulated and analyzed in six working conditions, and compared with the existing control strategy. The results show that the proposed control strategy is obviously better than the existing control strategy in terms of control accuracy and real-time performance, and can effectively improve vehicle safety and stability.

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

scholarly journals A Probabilistic Model for Real-Time Semantic Prediction of Human Motion Intentions from RGBD-Data

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4141
Author(s):  
Wouter Houtman ◽  
Gosse Bijlenga ◽  
Elena Torta ◽  
René van de Molengraft
Keyword(s):  
Real Time ◽  
Collision Avoidance ◽  
Probabilistic Model ◽  
Real Life ◽  
Human Motion ◽  
Model Based ◽  
Multiple Hypotheses ◽  
Navigation Algorithms ◽  
The Right ◽  
Motion Behavior

For robots to execute their navigation tasks both fast and safely in the presence of humans, it is necessary to make predictions about the route those humans intend to follow. Within this work, a model-based method is proposed that relates human motion behavior perceived from RGBD input to the constraints imposed by the environment by considering typical human routing alternatives. Multiple hypotheses about routing options of a human towards local semantic goal locations are created and validated, including explicit collision avoidance routes. It is demonstrated, with real-time, real-life experiments, that a coarse discretization based on the semantics of the environment suffices to make a proper distinction between a person going, for example, to the left or the right on an intersection. As such, a scalable and explainable solution is presented, which is suitable for incorporation within navigation algorithms.

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