In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …

There has been a paradigm-shift in urban logistic services in the last years; demand for real-
time, instant mobility and delivery services grows. This poses new challenges to logistic …

This survey presents a review of state-of-the-art deep neural network architectures,
algorithms, and systems in speech and vision applications. Recent advances in deep …

Applying and adapting deep reinforcement learning (DRL) to tackle transportation problems
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …

In this paper, an IRS-aided integrated sensing and communications (ISAC) system operating
in the terahertz (THz) band is proposed to maximize the system capacity. Transmit …

Accurate and real-time tracking for real-world urban logistics has become a popular
research topic in the field of intelligent transportation. While the routing of urban logistic …

We consider the problem of designing sample efficient learning algorithms for infinite
horizon discounted reward Markov Decision Process. Specifically, we propose the …

The growth in online goods delivery is causing a dramatic surge in urban vehicle traffic from
last-mile deliveries. On the other hand, ride-sharing has been on the rise with the success of …

Significant development of ride-sharing services presents a plethora of opportunities to
transform urban mobility by providing personalized and convenient transportation while …

Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among
different locations in a city. Recent advances primarily rely on deep reinforcement learning …