The Logit lane assignment model: first results

Farhi, Nadir; Haj-Salem, Habib; Khoshyaran, Megan M.; Lebacque, Jean-Patrick; Salvarani, Francesco; Schnetzler, Bernard; Vuyst, Florian De

doi:10.48550/arxiv.1302.0142

Cited by 1 publication

(2 citation statements)

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“…The detailed data improve the accuracy of the model. Farhi et al [23] introduced a logit lane allocation model to describe multi-lane traffic flow from a macroscopic perspective. Each available lane has a specific utility for the driver in the process of running the vehicle, and the driver will choose the lane with the highest utility.…”

Section: Logit Modelsmentioning

confidence: 99%

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Vehicle Lane Change Models—A Historical Review

Liu,

Hong,

Lin

2023

Applied Sciences

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Lane changing is a complex operation that has a significant impact on traffic safety. The accurate identification and assessment of potential risks in the driving environment before lane changing is crucial for the safe and smooth completion of a lane change. In this paper, the research status of vehicle lane change models is reviewed. Firstly, various factors affecting lane change models are analyzed. Different drivers will be affected by vehicle dynamic parameters, vehicle driving states, and driver characteristics under various road environments. Secondly, the vehicle lane change models are divided into four types: the empirical model of lane changing, the physical model of lane changing, the cognitive model of lane changing, and the mixed model of lane changing. The advantages and disadvantages of different types of lane change models are analyzed, and the key problems to be solved by different lane change models are expounded, respectively, from the aspects of input variables and reasoning algorithms. Finally, according to the advantages and disadvantages of different lane change models, a future research direction is proposed.

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Section: Logit Modelsmentioning

confidence: 99%

“…Input Variables Algorithm Key Issues to Be Resolved [23] Multi-lane macro traffic flow Logit The multi-lane traffic flow is described from a macroscopic perspective [24] Traffic accident data Mixed (random parameters) logit model…”

Section: Papermentioning

confidence: 99%