Mixed-traffic vehicle dynamics: analysis and comparison of microscopic Gipp’s car-following Model and Intelligent Driver Model

Car-following models describe the driver behaviour along the longitudinal direction in a traffic stream at a microscopic level. Therefore, the associated vehicle dynamics (i.e., velocity, acceleration) for different vehicles moving in pairs and platoons under mixed traffic situations using the car-following theory needs further exploration. Moreover, the response of a subject vehicle in mixed traffic stream depends upon the vehicle type and the manoeuvring capability. In this paper, we aim to evaluate some existing car-following models such as Gipp's car-following Model and the Intelligent Driver Model (IDM) for mixed traffic situations. Field trajectory data of mixed traffic flow on Kuala Lumpur urban highway were utilised in this study. From the field data, the leader-follower pairs are identified. Various parameters such as reaction time, speed and vehicle types affecting the vehicle-following behaviour for different leader-follower pairs are examined. Calibration and validation of these models are performed for different vehicle following pairs. The results show that the parameters used in the model vary based on the subject vehicle type and vehicle following pairs. It is concluded that Gipps model produces better results for a mixed platoon of vehicles by including vehicle-dependent parameter, whereas IDM model produces better and more stable results as compared to the Gipps model under the homogeneous car-following regime. This work has a significant influence in the development of a hybrid model for a realistic description of mixed traffic conditions.