Radar sensors were among the first perceptual sensors used for automated driving.
Although several other technologies such as lidar, camera, and ultrasonic sensors are …

Time series data naturally exist in many domains including medical data analysis,
infrastructure sensor monitoring, and motion tracking. However, a very small portion of …

Intelligent transportation systems play a crucial role in modern traffic management and
optimization, greatly improving traffic efficiency and safety. With the rapid development of …

The core value of simulation-based autonomy tests is to create densely extreme traffic
scenarios to test the performance and robustness of the algorithms and systems. Test …

Limit order books are a fundamental and widespread market mechanism. This paper
investigates the use of conditional generative models for order book simulation. For …

We propose a unified deep learning framework for the generation and analysis of driving
scenario trajectories, and validate its effectiveness in a principled way. To model and …

Human driving behavior can be a unique fingerprint to identify individual drivers and can be
used for vehicle theft detection. Prior research often uses supervised learning to classify …

Generative AI (GAI) has garnered significant attention recently with the upsurge of ChatGPT
and similar models. Research has shown that GAI technology has significantly contributed to …

Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of
intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets …

The future of transportation is tightly connected to Autonomous Driving (AD). While a lot of
progress has been made in recent years, there are still obstacles to overcome. One of the …