Validation of highly automated or autonomous vehicles is still a major challenge. One main
reason is the need to identify the uncountable potential situations in which the vehicle …

Abstract Autonomous Vehicles (AVs) ie, self-driving cars, operate in a safety-critical domain,
since errors in the autonomous driving software can lead to huge losses. Statistically, road …

Automotive industry is currently shifting from automated driving assistance systems to
conditionally automated vehicles. Traditional automotive component testing methodologies …

Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor
savings. Over the past few years, the number of simulators for autonomous driving has …

In order to facilitate acceptance and ensure safety, autonomous vehicles must be tested not
only in typical and relatively safe scenarios but also in dangerous and less frequent …

Connected and automated vehicles (CAVs) can bring safety, mobility, and energy benefits to
transportation systems. Ideally, CAV applications would be fully evaluated and validated …

Testing autonomous driving algorithms on real autonomous vehicles is extremely costly and
many researchers and developers in the field cannot afford a real car and the corresponding …

Closed field testing of Connected and Automated Vehicles (CAV) is an essential pillar for
verifying the functionality and performance of CAV and promoting its large-scale …

The increasingly used approach of combining different simulation softwares in testing of
automated driving systems (ADSs) increases the need for potential and convenient software …

Most existing studies on connected and automated vehicle (CAV) applications apply
simulation to evaluate system effectiveness. Model accuracy, limited data for calibration, and …