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Driver's Response to Speed Advisory System and Implications on Traffic Performances
A Case Study of COBRA
This study investigates driver responses to a cooperative speed advisory system based on the Cooperative Breakdown Prevention Algorithm (COBRA) in a simulated two-lane highway bottleneck. Twenty-one participants completed 12 scenarios in a driving simulator, with controlled variations in adjacent-lane deceleration timing and gap position at advisory onset. Results show that visible adjacent-lane deceleration significantly accelerated compliance, while its absence led to delayed or hesitant responses. Across all conditions, minimum time-to-collision exceeded 6 s, indicating no elevated collision risk. The target speed of 80 km/h was consistently reached, though mean deceleration (−1.74 m/s2) was less than the nominal −2.00 m/s2. Lane-change timing was strongly influenced by adjacent-lane cues, but initial gap size had limited effect. The findings suggest COBRA can maintain safety and efficiency in human-driven, two-lane contexts, but real-world application requires adaptive trigger logic, integration of lane interactions, and consideration of driver comfort.
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This study investigates driver responses to a cooperative speed advisory system based on the Cooperative Breakdown Prevention Algorithm (COBRA) in a simulated two-lane highway bottleneck. Twenty-one participants completed 12 scenarios in a driving simulator, with controlled variations in adjacent-lane deceleration timing and gap position at advisory onset. Results show that visible adjacent-lane deceleration significantly accelerated compliance, while its absence led to delayed or hesitant responses. Across all conditions, minimum time-to-collision exceeded 6 s, indicating no elevated collision risk. The target speed of 80 km/h was consistently reached, though mean deceleration (−1.74 m/s2) was less than the nominal −2.00 m/s2. Lane-change timing was strongly influenced by adjacent-lane cues, but initial gap size had limited effect. The findings suggest COBRA can maintain safety and efficiency in human-driven, two-lane contexts, but real-world application requires adaptive trigger logic, integration of lane interactions, and consideration of driver comfort.