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For safe driving and decrasing the risk of traffic accidents, it is important to control the driver mental status. In this paper, we implement an intelligent system based on Fuzzy Logic (FL) for deciding Driver Mental Status (DMS). We call this system FL-based DMS System (FLDMSS). The input parameters for FLDMSS are Driver Anxiety Level (DAL), Traffic Situation (TS) and Driving Operating Time (DOT). The output parameter is DMS. We evaluated the implemented system by computer simulations. The simulation results show that DMS is very good when the driving operating time is short. With increasing of DAL and DOT values, the DMS value is decreased. But when TS is good, the DMS value is increased.

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A Fuzzy-Based System for Decision of Driver Mental Status Considering Driver Anxiety Level, Traffic Situation and Driving Operating Time

  • 会议论文

  • 发表日期：

    2025年

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  • Yi Liu,
  • Leonard Barolli

摘要

For safe driving and decrasing the risk of traffic accidents, it is important to control the driver mental status. In this paper, we implement an intelligent system based on Fuzzy Logic (FL) for deciding Driver Mental Status (DMS). We call this system FL-based DMS System (FLDMSS). The input parameters for FLDMSS are Driver Anxiety Level (DAL), Traffic Situation (TS) and Driving Operating Time (DOT). The output parameter is DMS. We evaluated the implemented system by computer simulations. The simulation results show that DMS is very good when the driving operating time is short. With increasing of DAL and DOT values, the DMS value is decreased. But when TS is good, the DMS value is increased.