Safety is the most important requirement for autonomous vehicles; hence, the ultimate
challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver …

Rigorous and comprehensive testing plays a key role in training self-driving cars to handle a
variety of situations that they are expected to see on public roads. The physical testing on …

With the increment of connected vehicles, the level of intelligence becomes more and more
irregular, so the difficulties of determining the dynamic safety of self-driving in mixed …

Drive‐by structural health monitoring (SHM) is a cost‐efficient alternative to the direct SHM
of short‐to medium‐size bridges requiring no sensors to be installed on the structure …

Introduction: Teaching autonomous driving is a challenging task. Indeed, most existing
autonomous driving teaching activities focus on a few of the technologies involved. This not …

Urban traffic simulations are of great importance for smart cities research. However, city-
scale simulators can be both process and memory-intensive, and hard to scale. To speed up …

Abstract Validation of Autonomous Vehicle behavior algorithms requires thorough testing
against a wide range of test scenarios. It is not financially and practically feasible to conduct …

The deployment of autonomous vehicles in real-world scenarios requires thorough testing to
ensure sufficient safety levels. Driving simulators have proven to be useful testbeds for …

Autonomous driving is a safety-critical system, and the occupancy of its environmental
resources affects the safety of autonomous driving. In view of the lack of safety verification of …

Alluxio is a popular distributed memory storage system, which becomes increasingly
important in big data ecosystem by providing high performance storage for computing …