Vehicle merging algorithm for automated transportation systems using fuzzy logics

Jahng Hyon Park; Seyoung Lee

doi:10.1117/12.290322

26 September 1997 Vehicle merging algorithm for automated transportation systems using fuzzy logics

Jahng Hyon Park, Seyoung Lee

Proceedings Volume 3208, Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling; (1997) https://doi.org/10.1117/12.290322
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States

Abstract

A merging algorithm is proposed for smooth and efficient merges of vehicles at intersections of an automated transportation system. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, a decision algorithm is designed to determine the sequence of vehicles entering a converging section. The sequencing algorithm is based on fuzzy rules considering relative vehicle speed, distance, and priority of the lane. The membership function of the fuzzy system is determined not by an intuitive method but by a learning method using a neural net, where a cost function considering energy consumption and ride comfortability is used for training of the neural net. Finally, feasibility of the algorithm is investigated and validated through a simulation. The vehicle merging algorithm can be used for a PRT (personal rapid transit) system as well as for IVHS (intelligent vehicle- highway system).

Citation Download Citation

Jahng Hyon Park and Seyoung Lee "Vehicle merging algorithm for automated transportation systems using fuzzy logics", Proc. SPIE 3208, Intelligent Robots and Computer Vision XVI: Algorithms, Techniques, Active Vision, and Materials Handling, (26 September 1997); https://doi.org/10.1117/12.290322

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