A Physics-Based Longitudinal Driver Model for Automated Vehicles

Rahman, Mizanur; Islam, Rafiul; Chowdhury, Mashrur; Khan, Taufiquar

doi:10.1109/access.2022.3193997

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2023

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“…However, CAV behavior with this model is not realistic because under actual traffic conditions, the drivers take longer to achieve a smooth car-following behavior and the variations in headway are greater [36]. The ID model has also been incorporated into cooperative and Adaptive Cruise Control (ACC) systems [37,38]. Unfortunately, the safe distance between vehicles with this model is too small when the velocity is high, which can result in accidents when employed in ACC and related systems.…”

Section: Introductionmentioning

confidence: 99%

A Microscopic Traffic Model Considering Time Headway and Distance Headway

et al. 2023

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A microscopic traffic model is presented which employs differences in velocity to characterize driver behavior. The Intelligent Driver (ID) model is based on an acceleration constant which cannot capture different traffic conditions. Further, it is not based on traffic physics and so can produce inaccurate results. The proposed model is an improved ID model and both are evaluated on a 2000 m circular road. The results obtained show that the proposed model can appropriately characterize traffic flow and density. Further, the variations in flow and velocity are smoother than with the ID model. This is because the proposed model is based on actual traffic parameters rather than an unrealistic traffic exponent.

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Section: Introductionmentioning

confidence: 99%