Research on Evaluation of Vehicle Dangerous Traveling State Based on Information Fusion Method

Abstract:

An evaluation system of vehicle traveling state was proposed,and an unsafe vehicle traveling state recognition system was established using multi-level information fusion method. In view of the effects of the complexity of the driving environment, a variety of working conditions and the diversity of vehicle traveling characteristics, combing BP neural network with Dempster-Shafer evidence theory technique, the multi-information decision-level fusion was proposed to estimate the different kind model of the vehicle status. To verify the proposed strategies,the vehicle traveling posture evaluation system was established. The lane departure parameters and the relative distance parameters were studied in order to get the characterization of the vehicle traveling status information. The simulation results indicate that the adaptability and accuracy and the intelligence level of driving characterization estimation are significantly improved by using the pattern classification and decision technology of multi-source information fusion.

• Periodical: Advanced Materials Research (Volumes 791-793)
• Pages: 1018-1022
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.791-793.1018
• Online since: September 2013
• Authors: Peng Wang, Zhi Qiang Liu
• Keywords: BP Neural Network (BPNN), Dempster-Shafer Rule, Information Fusion, Pattern Classification, Safe Rules, Vehicle Traveling State

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