RCMS: Risk-Aware Crash Mitigation System for Autonomous Vehicles

Author:

Tariq Faizan M.1,Isele David2,Baras John S.1,Bae Sangjae2

Affiliation:

1. University of Maryland,College Park,MD,USA

2. Honda Research Institute,San Jose,CA,USA

Publisher

IEEE

Reference28 articles.

1. Evaluation of rear-end collision avoidance technologies based on real world crash data;Isaksson-Hellman;Proceedings of the Future Active Safety Technology Towards zero traffic accidents (FASTzero), Gothenburg, Sweden,2015

2. A fuzzy aid rear-end collision warning/avoidance system

3. Animal-vehicle crash mitigation using advanced technology: phase ii, system effectiveness and system acceptance;Huijser;Oregon. Dept. of Transportation. Research Unit, Tech. Rep.,2009

4. Machine Learning Based Prediction of Crash Severity Distributions for Mitigation Strategies

5. Collision Avoidance/Mitigation System: Motion Planning of Autonomous Vehicle via Predictive Occupancy Map

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1. Systematic Selective Limits Application Using Decision-Making Engines to Enhance Safety in Highly Automated Vehicles;SAE International Journal of Connected and Automated Vehicles;2024-08-01

2. AV-Occupant Perceived Risk Model for Cut-In Scenarios with Empirical Evaluation;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Multi-Profile Quadratic Programming (MPQP) for Optimal Gap Selection and Speed Planning of Autonomous Driving;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

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