How Do Vehicles Make Decisions during Implementation Period of Discretionary Lane Change? A Data-Driven Research

نویسندگان

چکیده

To investigate and compare the lane changing behavior of passenger cars heavy vehicles during implementation period (defined as interval from start time to end a change maneuver), this study applies gradient boosting decision tree (GBDT) method model cars, respectively. Results show that models vary with vehicle types directions. Different factors are considered by drivers when implementing changes different Partial dependence plots GBDT reveal influence independent variables on is nonlinear complicated, which means same variable leads various effects across In contrast other state-of-the-art methods, proposed can obtain more accurate results. The findings indicate it necessary build specific based directions for microscopic traffic simulators autonomous vehicles.

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ژورنال

عنوان ژورنال: Journal of Advanced Transportation

سال: 2023

ISSN: ['0197-6729', '2042-3195']

DOI: https://doi.org/10.1155/2023/2586372