Acceleration models for two-wheelers and cars in mixed traffic: effect of unique vehicle-following interactions and driving regimes

CURRENT SCIENCE(2022)

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摘要
Driving behaviour in mixed traffic conditions is characterized by vehicle heterogeneity and lane-less movement. In such traffic conditions, the following response of a vehicle may be discontinuous and gets triggered when certain thresholds on relative speed and spacing with the leaders are crossed. In this context, the present study segments vehicular response into driving regimes using vehicle trajectory data based on relative speed and position. Acceleration models are formulated by featuring driving regimes and their interactions with mixed traffic attributes. These models are used to study the differences in the following behaviour of two-wheelers and cars. The proposed models capture the asymmetric behaviour and account for differences across driving regimes, resulting in a significantly better fit and realistic representation of mixed traffic.
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关键词
Acceleration models, driving regimes, mixed traffic attributes, local area concentration, vehicle trajec- tory extraction
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