Autonomous truck platoons hold the potential for substantial economic and environmental advantages. However, there is a lack of comprehensive research on the interactions between drivers and different configurations of truck platoons at waving segments. This study aims to contribute to the literature by achieving three primary objectives: (1) examine the effects of various truck platoon configurations on merging and diverging behaviors [time to merge (TTM) and time to diverge (TTD)]; (2) explore the impact of individual characteristics such as age, gender, education level, and driving experience on TTM and TTD; and (3) investigate the decision-making associated with these maneuvers (merging or diverging in front of the platoon, behind the platoon or cut in through the platoon). A driving simulator study was conducted with 85 participants across 12 distinct scenarios, considering variations in platoon size, intraplatoon spacing, and platoon lane-change behavior. Several statistical methods were employed, including ANOVA, the Cox proportional hazards model, and machine-learning techniques, to analyze the factors impacting TTM and TTD. The results revealed that increasing the headway distances between trucks in a platoon to 13.72 m (45 ft) or 18.29 m (60 ft) substantially decreased TTM, enhancing traffic flow. Furthermore, splitting the truck platoon between two lanes of the freeway before the merging point significantly influenced other drivers’ merging decisions. When half of the trucks in a platoon switched to the left lane before the merging point, a larger proportion of participants chose to merge ahead of the platoon. Age, gender, education level, and self-assessment of driving skills were all found to significantly influence merging and diverging behaviors. Drivers with higher degrees took longer to merge, whereas older, male, and experienced drivers merged faster. The lowest average TTD was observed when half the platoon switched to the left lane before the diverging point.
Empirical Analysis of Drivers’ Merging and Diverging Responses to Autonomous Truck Platooning on Freeway Weaving Segments
J. Transp. Eng., Part A: Systems
2024-10-01
Article (Journal)
Electronic Resource
English
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