The connected vehicle is promising to enhance traffic efficiency, travel safety, and energy savings. However, the connected vehicle applies wireless communication in an open-access environment, which makes the vehicle vulnerable to cyber threats. Existing studies mainly focus on the impact of attacks on a single lane by using extended car-following models and simulation platforms. To fill this gap, this paper expands to investigate the effects of cyber attacks, especially the car-following behaviors under cyber attacks. In detail, we develop an extended car-following model by employing the classical car-following model, i.e., intelligence driver model (IDM). Furthermore, we propose an improved car-following model based on Intelligent Driver Model (IDM) to describe vehicles’ behaviors in the multi-lane. In the end, a serial of simulations is conducted to illustrate that different malicious behavior such as falsified acceleration, velocity and position can cause congestion and collision. This work sheds light on the theoretical analysis to prevent connected vehicle collision and catastrophic traffic congestion facing cyber attacks.

CICTP