MULTI-SENSOR POS/NAV FOR CAVS WORKSHOP

For Virtual Presentation guidelines: Presentation Instructions_VTCFall-2020_for_authors – Final

Call for Papers
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Important Dates:
Paper Submission,
June 19, 2020 [Closed]
Notification of Acceptance,
July 06, 2020
Final Paper Submission,
July 14, 2020 (FIRM by IEEE)

Welcome

Connected and autonomous vehicles (CAVs) promise to improve the safety and efficiency of our transportation system, reduce collisions, traffic congestion, and emissions, and improve mobility for a growing population. Increasing demand for CAVs is shaping the future of the automotive industry by connecting vehicles to one another and the surrounding infrastructure, transforming the in-vehicle experience and paving the way to autonomous driving. CAVs that are capable of sensing the environment and navigating without human input require robust high precision positioning and orientation information at all times in all environments. Standalone GNSS-based positioning and navigation systems suffer from satellite signal blockage, interference and multipath. Integration with motion sensors (speedometers, accelerometers and gyroscopes) can only enhance the performance for a limited period of time.
Future land vehicles, drones, autonomous systems and portable devices will be equipped with vision cameras, radar, ultrasound and LiDAR sensors and systems that will be utilized for various reasons. The availability of these sensors and systems provide an attractive opportunity to further increase the positioning and navigation system accuracy and robustness in GNSS-challenging environment. The advent of new sensors, integration techniques, and navigation applications are active topics of research in multi-sensor systems. The purpose of this workshop is to invite submissions on the latest developments and advancement in multi-sensor systems for positioning and navigation. The focus of the contributions will be on discussing the research results about scientific advances in sensors, innovative data processing and machine intelligence techniques, multi-sensor fusion methods, and potential applications.