Publication Type:

Conference Proceedings

Source:

2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2017)

Keywords:

adaptive control, adaptive cruise control, adaptive particle filter, anti-lock breaking systems, automobile safety, Automobiles, Cruise control, Estimation, Hidden Markov models, Kalman filters, lateral prediction, mathematical model, Noise measurement, Particle filter, Particle filters, Road safety, road traffic control, Stability, target selection, vehicle stability control systems

Abstract:

As of recently, there are more than half a billion cars on the road throughout the world and hence arises the necessity for making safety a higher priority in vehicle technologies. Modern automobiles contain various functions that assist the driver and enhance safety. Anti-lock breaking systems and vehicle stability control systems are few of the technologies that are used to implement vehicular safety and one such technology is cruise control. Ordinary cruise control has been used in high-end premium cars for some years now; adaptive cruise control is an upgraded version. Adaptive cruise control (ACC) is an automotive feature that helps a vehicle's cruise control system to adapt the vehicle's speed according to the traffic environment. This paper discusses the advantages of adaptive particle filter compared to the existing methods in lateral prediction of a vehicle in an ACC.

Cite this Research Publication

J. Badrinath, Anita, J. P., and Sudheesh, P., “Lateral Prediction in Adaptive Cruise Control using Adaptive Particle Filter”, 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). 2017.