@article{ref1,
title="Collision avoidance support in roads with lateral and longitudinal maneuver prediction by fusing GPS/IMU and digital maps",
journal="Transportation research part C: emerging technologies",
year="2010",
author="Toledo-Moreo, Rafael and Zamora-Izquierdo, Miguel A.",
volume="18",
number="4",
pages="611-625",
abstract="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 (CCASS) the vehicles which constitute a scene share by means of communication links information that can be useful to detect a potentially risky situation. Typically, this information describes the kinematic state of each vehicle and can be complemented with a prediction of its next state. Indeed, the timely prediction of the next maneuver of a vehicle results beneficial to estimate the risk factor of a scene. This article presents a solution to the problem of maneuver prediction which employs a reduced number of sensors: a Global Navigation Satellite System (GNSS) receiver, one gyro, one accelerometer and the odometry. Predictions are made by a bi-dimensional interactive multiple model (2D-IMM) filter in which longitudinal and lateral motions of the vehicle are distinguished and maneuvering states are described by different kinematic models. A number of experiments were carried out with two vehicle prototypes in several circuits. The results achieved prove the suitability of the proposed method for the problem under consideration.<p />",
language="en",
issn="0968-090X",
doi="10.1016/j.trc.2010.01.001",
url="http://dx.doi.org/10.1016/j.trc.2010.01.001"
}