| Abstrakt: |
The vehicular trajectory offset represents a critical controlling element in the design of lane width. In light of the paucity of extant research on the lane widths for dedicated autonomous vehicle lanes, this study deployed the PreScan-Simulink co-simulation platform. Based on the established typical lateral and longitudinal control methods for autonomous vehicles, we initially identified the primary factors influencing trajectory offset through multifactorial coupled analysis. Subsequently, we conducted quantitative research on vehicle trajectory offset using S-shaped curves to elucidate the patterns in geometric elements' impact on trajectory offset. Following this, we established a model of the relationship between design speed and trajectory offset under different vehicle types. Ultimately, we calculated the lane width values for scenarios involving varying positions and numbers of dedicated lanes. The results demonstrate that vehicle speed significantly impacts the trajectory offsets of autonomous vehicles. For passenger cars, the mean offset at speeds between 60 and 130 km/h is approximately 10 cm. At higher speeds of 140–150 km/h, the offset is more variable. The range of offset exhibited by trucks at speeds between 60 and 100 km/h is [8 cm, 16 cm]. In the case of a single dedicated lane, the width of the inner lanes intended for passenger cars is [2.60 m, 3.00 m], while the outer lanes designed to accommodate trucks have a width of [3.00 m, 3.20 m]. In scenarios with two dedicated lanes, the width of lanes for passenger cars can be reduced further, whereas the required lane width for trucks remains largely unchanged compared to that for single-lane setups. The conclusions show that the width of lanes adapted to autonomous vehicles could be reduced, which could help to optimize the use of road space, thus potentially reducing the occupation of land resources, reducing the environmental impact of road construction, and contributing to sustainable development. This study also provides valuable insights for the design of lanes dedicated to autonomous vehicles. [ABSTRACT FROM AUTHOR] |
