Vehicle lane change behavior, which is an important part of traffic flow theory, can have a
fundamental impact on the macro and micro characteristics of traffic flow. At the same time, it …

Current research and development in recognizing and predicting driving behaviors plays an
important role in the development of Advanced Driver Assistance Systems (ADAS). For this …

In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

False data injection (FDI) attacks aim to threaten the security of Internet of Things (IoT)
systems by falsifying a device's measurements without being detected. In this paper, we …

The significant contribution of human errors, accounting for approximately 94%(with a
margin of±2.2%), to road crashes leading to casualties, vehicle damages, and safety …

Lane change and crash risk prediction are critical technologies for autonomous driving. An
attention-based LSTM model is proposed in this paper for lane change behavior prediction …

Seamless human-robot manipulation in close proximity relies on accurate forecasts of
human motion. While there has been significant progress in learning forecast models at …

Ride-sourcing drivers enjoy flexibility in scheduling work hours and choosing platforms,
which generates multi-homing behavior on multiple platforms. It is challenging to observe …

With the availability of modern assistive techniques, ambient intelligence, and the Internet of
Things (IoT), various innovative assistive environments have been developed, such as …

The smart road stud (SRS) system can improve the driver's overtaking behavior through light
guidance, which shows great potential in raising the traffic efficiency of two-way two-lane …