Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of
ground transportation. It is anticipated that ordinary vehicles will one day be replaced with …

Real-time, accurate, and robust localisation is critical for autonomous vehicles (AVs) to
achieve safe, efficient driving, whilst real-time performance is essential for AVs to achieve …

This paper proposes a dead-reckoning (DR)/WiFi fingerprinting/magnetic matching (MM)
integration structure that uses off-the-shelf sensors in consumer portable devices and …

In this paper, we propose a novel localization methodology to enhance the accuracy from
two aspects, ie, adapting to the uncertain noise of microelectromechanical system-based …

Over the last decades, the development of Advanced Driver Assistance Systems (ADAS) has
become a critical endeavor to attain different objectives: safety enhancement, mobility …

In this paper, an innovative optimal information fusion methodology based on adaptive and
robust unscented Kalman filter (UKF) for multi-sensor nonlinear stochastic systems is …

This article focusses on the fusion of information from various automotive sensors like radar,
video, and lidar for enhanced safety and traffic efficiency. Fusion is not restricted to data from …

This paper describes a lane-level localization algorithm based on a map-matching method
for application to automated driving in urban environments. The lane-level localization …

Abstract Evaluation of UAV systems is mostly based on simulation tools that are manually
configured to define the trajectory (ground truth trajectory) for comparing with the system …

Aimed at the challenge of generating indoor localization databases with daily life
crowdsourcing-based inertial sensor data, this paper proposes an anchor point-based …