Intra-driver heterogeneity is defined as transition of driver’s behavior between usual and unusual, which is an intrinsic feature of drivers while yet to be extensively explored. This study used a large-scale naturalistic driving data set to investigate intra-driver heterogeneity in car-following. We constructed an IDM-based baseline model to represent a driver’s usual behavior; by measuring difference between observed behavior with baseline, unusual behavior was identified. Then, multi-level logit model with random effects was fitted to uncover contributing factors. Among 41 drivers’ 1356 trips, intra-driver heterogeneity was identified in 3194 episodes, which accounts for 15% of the time. Within investigated 24 factors, we found that intra-driver heterogeneity was statistically related with vehicle kinematic features, then traffic flow and surrounding environment, but not driver sociodemographics. Being cut in is the most prominent trigger for intra-driver heterogeneity. These findings garner some remarkable insights into improvement of car-following modeling and many other engineering practices.
Investigating the intra-driver heterogeneity in car following behaviour based on large-scale naturalistic driving study
Transportmetrica B: Transport Dynamics ; 11 , 1 ; 1363-1383
31.12.2023
21 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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