Cruise control

Denial-of-service attack

World Wide Web

Control (management)

Engineering

Transport engineering

Automation

Platoon

Spoofing attack

Computer security

The Internet

Computer science

Environmental health

Cyber-attack

Critical infrastructure

Computer network

Mechanical engineering

Microsimulation

Poison control

VisSim

Leverage (statistics)

Artificial intelligence

Medicine

Programming language

Crash

Intersection (aeronautics)

Intelligent transportation system

Machine learning

Cooperative Adaptive Cruise Control

Accident Analysis & Prevention

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. These results pave the way for future design of secure systems from a monitoring perspective.

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes