The prediction of lane changes has been proven to be useful for collision avoidance support
in road vehicles. This paper proposes an interactive multiple model (IMM)-based method for …

This paper presents a low-cost real-time lane-determination system that fuses micro-
electromechanical systems inertial sensors (accelerometers and gyroscopes), global …

A multiple-model framework of adaptive extended Kalman filters (EKF) for predicting vehicle
position with the aid of Global Positioning System (GPS) data is proposed to improve …

Many intelligent transportation system (ITS) applications will increasingly rely on lane-level
vehicle positioning that requires high accuracy, bandwidth, availability, and integrity. Lane …

In the near future, multi-sensor fusion will be the core component to navigate the
autonomous driving platforms. This paper proposes new strategies to cope with the …

Abstract Global Navigation Satellite Systems (GNSS) has been widely used in the provision
of Intelligent Transportation System (ITS) services. Current meter level system availability …

Collision avoidance in roads can be addressed in several ways, being cooperative systems
one of the most promising options. In cooperative collision avoidance support systems …

Depending on driver intention and current motion state of vehicle, an infinite set of possible
future trajectories exists. In this paper we present a stochastic filter which is able to select a …

Estimating a driver's lane-change (LC) intent is very important so as to avoid traffic accidents
caused by improper LC maneuvers. This paper proposes a lane-change Bayesian network …

Predicting lane change maneuvers is critical for autonomous vehicles and traffic
management as lane change may cause conflict in traffic flow. Most existing studies do not …