Information and communication technologies can greatly improve traffic capacity, efficiency, and stability, but most connected-vehicle and signal management advances focus on motor vehicles, leaving a major gap for vulnerable road […]
As robot taxi increasingly share roads with human drivers, creating human-like driving agents has emerged as a promising approach for seamless integration into mixed-autonomy environments. Achieving effective vehicle human interaction […]
The emerging Automated Vehicle (AV) technology has the potential to address impaired driving (i.e., driving under the influence of alcohol or drugs), a significant contributor to road fatalities. Previous research […]
With the rapid advancement of deep learning technology, feature extraction backbones that are effectively trained have found increasing use in various traffic perception tasks, such as vehicle recognition and roadway […]
From autonomous vehicles to collaborative robots, drones, and wearable health devices, intelligent systems are increasingly defined by the tight coupling between AI algorithms and computing hardware. These systems must see, […]
Computing-enabled Automated Traffic Systems (ATS) are rapidly gaining popularity for autonomous vehicles and smart infrastructure, leading to increased power consumption and energy costs. This paper first demonstrates that the computational […]
Traffic surveillance cameras are the eyes of the Intelligent Transportation Systems (ITS). However, they are currently isolated and can only extract information from each of their fixed views. To track […]
Autonomous vehicles, open-world robots, and other automated systems rely on accurate, efficient perception modules for real-time object detection. Although high-precision models improve reliability, their processing time and computational overhead can […]
Truck drivers nationwide experience significant productivity losses and heightened safety risks due to inadequate and deteriorating parking facilities, exacerbated by stringent operational regulations and informational barriers. The core innovation is […]
Transportation planning plays a vital role in developing efficient and sustainable transportation systems to meet the evolving needs of communities. As technology advances, the field of transportation planning could benefit […]
Trustworthy LLM for traffic forecasting, advances explainable deep and generative models that fuse multimodal sensing with traffic theory to forecast congestion and freight bottlenecks in real time, laying the groundwork […]
Predicting expected traffic crashes and designing targeted interventions are highly challenging due to the inherent complexity of crash data and persistent concerns over the prediction trustworthiness. We introduce SafeTraffic Copilot that […]
We utilize available epidemiological surveillance data (cases, hospitalizations, wastewater), travel data, land use patterns, climate data, sociodemographic data, behavioural data, policy and ecological models within statistical, machine learning and AI […]