Safety is the cornerstone of autonomous driving vehicles. For autonomously controlled
vehicles driving safely in complex and dynamic traffic scenarios, it is essential to precisely …

Kalman filter was pioneered by Rudolf Emil Kalman in 1960, originally designed and
developed to solve the navigation problem in Apollo Project. Since then, numerous …

The motion planning framework is one of the challenging tasks in autonomous driving cars.
During motion planning, predicting of trajectory is computed by Gaussian propagation …

A smart city is emerging as an application of information and communication technologies to
mitigate the problems generated by the urban population growth. One of the smart city …

This paper presents a novel approach for freeway traffic state estimation. Although there is
currently a wide variety of estimation methods, new designs and technologies can still be …

Short-term traffic condition forecasting has long been argued as essential for developing
proactive traffic control systems that could alleviate the growing congestion in the United …

In this paper, we develop a mobile positioning method for mobile position tracking and
velocity estimation in a network-based wireless location system. The time of arrival (TOA) …

This paper formulates the traffic flow forecasting task by introducing a maximum correntropy
deduced Kalman filter. The traditional Kalman filter is based on minimum mean square error …

Travel-time prediction has been an interesting research subject for decades, and various
prediction models have been developed. A prediction model was derived by integrating path …

Travel time information is a vital component of many Intelligent Transportation Systems (ITS)
applications such as Route Guidance Systems (RGS), Advanced Traveler Information …