Optimization of Vehicular Trajectories under Gaussian Noise Disturbances

Future Internet

Juan-Bautista Tomas-Gabarron¹  Esteban Egea-Lopez² 

[1] Department of Information and Communication Technologies, Technical University of Cartagena (UPCT), Plaza del Hospital, 1, 30202 Cartagena, Spain;

关键词: vehicle safety;    optimum control;    optimum maneuvering;   

DOI  :  10.3390/fi5010001

来源: mdpi

【 摘 要 】

Nowadays, research on Vehicular Technology aims at automating every single mechanical element of vehicles, in order to increase passengers’ safety, reduce human driving intervention and provide entertainment services on board. Automatic trajectory tracing for vehicles under especially risky circumstances is a field of research that is currently gaining enormous attention. In this paper, we show some results on how to develop useful policies to execute maneuvers by a vehicle at high speeds with the mathematical optimization of some already established mobility conditions of the car. We also study how the presence of Gaussian noise on measurement sensors while maneuvering can disturb motion and affect the final trajectories. Different performance criteria for the optimization of such maneuvers are presented, and an analysis is shown on how path deviations can be minimized by using trajectory smoothing techniques like the Kalman Filter. We finalize the paper with a discussion on how communications can be used to implement these schemes.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.