Digital map and GNSS fusion to enhance localization for intelligent vehicle applications

Abstract

This thesis aims to enhance vehicle localization through the fusion of digital maps and vehicular communication. A particle lter based algorithm for fusing global navigation satellite system (GNSS) receiver, odometer, and digital maps is proposed and implemented. Implementation deployed on an embedded system and tested in the eld. Field tests were carried out di erent in parts of _Istanbul to measure the performance of the algorithm in di erent satellite visibility conditions. Results show that algorithm selects the correct road segment on the digital map with 96% success rate. The proposed algorithm was further enhanced with the addition of mutual positioning on vehicular ad-hoc networks (VANETs). The measurement-based statistical model of relative distance as a function of Time-of-Arrival(TOA) is experimentally obtained. The mutual positioning procedure is investigated in terms of positioning accuracy and network performance through realistic simulation studies with a di erent number of collaborative vehicles, and the proposed mutual positioning procedure is experimentally evaluated by a eet of ve IEEE 802.11p radio modem equipped vehicles. It is shown that collaboration in a VANET improves the availability of position measurement and its accuracy up to 40% in comparison with the stand-alone GNSS receiver. Local integrity heat map concept is introduced as a new local integrity methodology. Local integrity heat map is implemented and tested with extensive eld tests. Algorithm is successful in detecting urban canyons and can be used as an augmentation for GNSS. It is concluded that our fusion framework with the use of digital maps and inter-vehicle communications can be e ciently used for ADAS applications and our local integrity method can further enhance fusion and localization.