Abstract
In car-navigation systems, car position measurement estimates the car's position and heading angle from the outputs of a GPS receiver and sensors, and calculates the position on a link that represents a road and is recorded in a digital road map. We focus on the latter process, which is map matching. If there are large errors in the car's estimated position and heading angle and in link position and direction angle, map matching selects an incorrect link. If map matching uses the data of the past route, it can select a correct link when the car is on a parallel road. This paper proposes a map-matching method using a chi-squared statistic for car-navigation systems. This method calculates a selection criterion that takes into account the errors in the car's estimated position and heading angle and in the link position and direction angle. This criterion is chi-squared distributed and is calculated from data points that were observed at constant distance intervals. The method's performance was experimentally evaluated using observation data collected in a car. It was found to be effective on roads that pose map matching difficulties, i.e., forks in roads, parallel roads, and roundabouts.
