An Extended Intelligent Driver Model to Describe the Impact of Cyberattacks on Connected Vehicles

Connected vehicle technology has received considerable attention in recent years, due to its potential to significantly benefit in improving traffic efficiency, enhancing road safety, and reducing fuel consumption. However, vehicular wireless communication such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) is in an open-access environment, which makes connected vehicles vulnerable to cyber threats. In our research, we first summarize some typical cyberattacks that can disturb connected vehicles and found that these cyberattacks, in essence, can alter velocity, position, and acceleration of the subject vehicle. For understanding the mechanism of traffic disturbance under cyberattacks, we proposed an improved intelligent driver model to describe traffic dynamics of the connected vehicles under cyberattacks, especially when the attack is infectious. To clearly describe the impact of cyberattacks on vehicles, a two-layer system structure is proposed, where the upper layer describes the cyber information propagation and the lower describes the traffic flow dynamics. Finally, using the new dynamical model, extensive simulation cases studies are carried out to describe traffic dynamics with potential cyberattacks for connected vehicle platoons. These simulation results further indicate the proposed model could be applied to help avoid collisions and relieve traffic congestion.