Title: Driver Behavior Assessment Based on Loosely Coupled GPS/INS Integration in Harsh Environment
Author(s): Oussama Derbel, Mohamed Lajmi Cherif, René Jr. Landry
Published in: Proceedings of IEEE/ION PLANS 2018
April 23 - 26, 2018
Hyatt Regency Hotel
Monterey, CA
Pages: 1362 - 1367
Cite this article: Derbel, Oussama, Cherif, Mohamed Lajmi, Landry, René Jr., "Driver Behavior Assessment Based on Loosely Coupled GPS/INS Integration in Harsh Environment," Proceedings of IEEE/ION PLANS 2018, Monterey, CA, April 2018, pp. 1362-1367.
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Abstract: Commercial location-based services use mainly the Global Positioning System (GPS) receiver data to develop the driver assistance and monitoring systems. Nevertheless, the GPS receiver has a lot of problems, and the important one is the signal availability in harsh environment such as urban canyon, tunnel and bridge. To overcome this drawback, the Inertial Navigation System (INS) comes to aid the GPS receiver using Kalman filtering to compute precise the position, velocity and acceleration in these environments. This paper matches the two complementary areas which are: GPS/INS integration and Driver Behavior Assessment (DBA). In the literature, these two fields have been deeply investigated separately. However, an accurate analysis of the driver behavior requires precise and available data (position, velocity and acceleration) even in harsh environment. This paper presents a new method for driving behavior assessment based on the loosely coupled GPS/INS integration that allows a precise results, especially in case of GPS outages which can be modeled in the driver behavior assessment part. This assessment uses the belief theory, to fuse risk information given from the Driver, Vehicle and Environment entities, and the fuzzy theory to reduce the complexity of the fusion problem. The obtained real test results show good performance of the developed algorithms as well as the risk models. In addition, the presented results show the capability of the belief theory to model the GPS outages and the quality of signals.