The practice of vehicle platooning for managing mixed traffic can greatly enhance
safety on the roads, augment overall traffic flow, and boost fuel efficiency,
garnering considerable focus in transportation. Existing research on vehicle
platoon control of mixed traffic has primarily focused on using the state
information of the leading or head vehicle as control input for following
vehicles without accounting for the driving variability of Human-driven Vehicles
(HDVs), which does not conform to the driving conditions of vehicles in reality.
Inspired by this, this paper presents a car-following model for Connected and
Automated Vehicles (CAVs) that utilizes communication with multiple preceding
vehicles in mixed traffic. The study further investigates the impact of
parameters such as the speed and acceleration of preceding vehicles on the
car-following behavior of CAVs, as well as the overall effect of different CAV
penetration rates on mixed traffic flow. Firstly, a mixed-vehicle platoon model
is constructed, and an improved multi-vehicle-following topology controller is
proposed. Secondly, based on the multi-leading-vehicle communication topology,
the head-to-tail transfer function of the vehicle platoon is derived, and the
impact of the communication topology on platoon stability is analyzed under
different CAV penetration rates. Finally, the proposed vehicle-following model
is verified on the SUMO simulation platform. The experimental results
demonstrate that, compared to the Intelligent Driver Model(IDM), the proposed
model exhibits more minor speed fluctuations and superior following efficiency.
Additionally, under the proposed car-following model, the stability of mixed
traffic flows can be enhanced as the penetration rate of CAVs increases. This
research provides theoretical and technical support for vehicle platoon control
issues in mixed-traffic environments.