A novel merging strategy model considering the remaining distance in the acceleration lane

Abstract The driver of a merging vehicle must account for both the lane‐changing risk and the remaining distance in the acceleration lane (RD) during a merging decision‐making process. To investigate the impact of RD on merge decisions, a typical freeway merging section was selected and monitored wi...

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Bibliographic Details
Main Authors: Menglu Gu, Yanqi Su, Chang Wang, Rui Fu, Yingshi Guo, Wei Yuan
Format: Article
Language:English
Published: Wiley 2023-09-01
Series:IET Intelligent Transport Systems
Subjects:
Online Access:https://doi.org/10.1049/itr2.12381
Description
Summary:Abstract The driver of a merging vehicle must account for both the lane‐changing risk and the remaining distance in the acceleration lane (RD) during a merging decision‐making process. To investigate the impact of RD on merge decisions, a typical freeway merging section was selected and monitored with a millimetre radar and a high‐resolution digital camera, which were mounted on the guardrail in the gore area. More than 2000 merging vehicles were captured during the data collection process. The effects of the surrounding vehicles on the merging behaviour were analyzed, and a merging strategy model considering RD that was based on the random forest algorithm was constructed. The results show that the following vehicle in the target lane is the main factor that affects the merging behaviour of the merging vehicle. When the decision time window was set to 0.6 s, the proposed merging decision model could distinguish ‘Merge’ events and ‘Wait’ events with accuracies of 97.2% and 89.4%, respectively. The overall accuracy of the model was 94.9%, which was 3.9% higher than for a corresponding merging decision model that excluded RD influence. The proposed merging decision model can aid merging processes and give cues for human‐like merge decisions of automated vehicles.
ISSN:1751-956X
1751-9578