This study aims to improve the desired distance adaptability of the cooperative adaptive cruise control (CACC) during car-following. In this study, the characteristics of the desired distance in different traffic flow states were analyzed. The general functional form of the desired distance in the car-following process was formulated. Then, a car-following platoon was constructed to compare the car-following effect of the platoon under different conditions, using the following speed and the lead vehicle disturbance, as the observed variable and the simulation condition, respectively. The car-following effect of the platoon under different parameters was also compared, based on the improved CACC model. The results show that the improved CACC model exhibited more advantages in car-following efficiency, it can better describe the state of the car-following queue under different traffic flow parameters and car-following behavior conditions, it has a strong anti-interference ability for the fluctuation of the car-following queue and is conducive to further improving the intelligent operation of car-following queue.
With the development of intelligent connected vehicles (ICVs) and communication technology, collaborative operation among vehicles will become the trend of the future. Thus, traffic flow will be mixed with manual driving vehicles and ICVs. A mixed traffic flow is a traffic flow state lying between autonomous and manual traffic flows. In order to describe the car-following characteristics in a mixed traffic flow, the cooperative adaptive cruise control (CACC) car-following model and the intelligent driver model (IDM) were adopted. The car-following characteristics of different platoons from these two car-following models were analyzed. The CACC mixing ratio was used to describe the mixed traffic flow. The fixed states and disturbance states of the car-following platoons were simulated. The fixed states can be divided into three categories: the steady state, acceleration state, and deceleration state. The effects of different car-following cases and different mixing ratios on mixed traffic flow in different states were discussed. The results show that (1) in the steady state with a smaller mixing ratio, the operating speed and traffic volume of the mixed traffic flow were positively correlated. The overall traffic volume decreased with the increase in the mixing ratio, and the gap gradually narrowed. At a larger mixing ratio, the operating speed and traffic volume were negatively correlated. The overall traffic volume increased with the increase in the mixing ratio. (2) In the acceleration state, the maximum traffic volume in the platoon and the optimal mixing ratio were linearly related to the acceleration. (3) In the deceleration state with a fixed mixing ratio, the traffic volume decreased with the increase in the deceleration, with slight differences in the changing trend of the volume of the mixed flow. Under disturbances, the mixed traffic volume was positively correlated with the mixing ratio, i.e., at a larger mixing ratio, the anti-interference ability of the mixed traffic flow was higher.
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