Dynamic guidance of an autonomous vehicle with spatio-temporal GIS

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Abstract

Most of computer-vision systems for vehicle guidance are tuned for highway scenarios. Developing autonomous or driver-assistance systems for complex urban traffic pose new algorithmic and system architecture challenges. This paper introduces a novel system that uses Spatio-Temporal GIS principles and a new traffic determination algorithm. The prototype system can be used as a part of autonomous vehicles controlling structure with analytical capabilities. For these purposes, predicting vehicle motion is done through trajectories. The trajectories are generated using spatial and aspatial information in GIS environment. Then, vehicle is navigated by GPS and a fuzzy logic map matching is used to locate the vehicle position on the map. Traffic congestion algorithm, which passed through 82.5% of evaluations cases successfully, is performed by vehicle’s velocity in the third step. Finally, heuristic real-time route finding algorithm is used for dynamic updating of planned vehicle trajectory. Furthermore, the system is open so that further extensions such as controlling autonomous vehicle for avoiding or leaving the banned regions are possible.

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APA

Vafaeinejad, A. (2017). Dynamic guidance of an autonomous vehicle with spatio-temporal GIS. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10407 LNCS, pp. 502–511). Springer Verlag. https://doi.org/10.1007/978-3-319-62401-3_36

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