Volume 43 Issue 4
Aug.  2025
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JU Yunjie, CHEN Feng. Driver Workload and Behavioral Characteristics at Urban Unsignalized Intersections Under the Influence of Human-machine Interaction Systems[J]. Journal of Transport Information and Safety, 2025, 43(4): 129-138. doi: 10.3963/j.jssn.1674-4861.2025.04.013
Citation: JU Yunjie, CHEN Feng. Driver Workload and Behavioral Characteristics at Urban Unsignalized Intersections Under the Influence of Human-machine Interaction Systems[J]. Journal of Transport Information and Safety, 2025, 43(4): 129-138. doi: 10.3963/j.jssn.1674-4861.2025.04.013

Driver Workload and Behavioral Characteristics at Urban Unsignalized Intersections Under the Influence of Human-machine Interaction Systems

doi: 10.3963/j.jssn.1674-4861.2025.04.013
  • Received Date: 2025-01-01
  • Human-machine interaction systems (HMIs) play a vital role in enhancing the driving experience. However, whether additional interaction information overloads driver workload and affects behavioral performance remains unclear. For this purpose, the study recruits 29 participants for a driving-simulator experiment. It measures the detection response task (DRT), NASA Task Load Index (NASA-TLX), and driving behavior parameters, and analyzes driver workload and behavioral characteristics across HMI systems and conflict types, while considering their interaction effects. Results show that: ①Under integrated visual-auditory information, drivers'DRT response time decreases 12.1% and hit rate increases 5.8%—48.5%. This suggests drivers establish high situational awareness and can allocate more cognitive resources to DRT requests. Additionally, in cross-conflict environments, drivers frequently monitor surrounding traffic to determine other road users'positions and trajectories. As a result, DRT response time increases 14.8%, and hit rate decreases 22.6%. ②Based on NASA-TLX, under integrated visual-auditory information, effort scores decrease 21.7%—22.8%. Drivers consider they can reach expected performance levels more easily than others. Perceived time pressure decreases 19.8%, indicating a more relaxed and composed driving pace. Frustration scores decrease 31.4%—32.9%, and negative emotions including insecurity, discouragement, irritability, tension, and annoyance decrease. ③With sufficient space and time margins for safety-critical events, drivers with integrated visual-auditory information show a 32.1% reduction in speed standard deviation. Acceleration noise decreases 26.9%, and lateral offset standard deviation decreases 7.1%. Driving becomes smoother and more comfortable, with better lane-keeping ability and improved lateral control stability.

     

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