Print Email Facebook Twitter Evaluating the Quality of Lane Change Event Detection Title Evaluating the Quality of Lane Change Event Detection: Effect of Situational Variables Author Geurts, M. Hogema, J. Silvas, E. Souman, J. Rahman, A. Hiller, J. Publication year 2022 Abstract To develop safe automated driving functions, knowing road-user’s lane change behaviour is critical. This detection problem may depend on multiple aspects such as road conditions, location, and weather. To understand the effect of these situational variables, this work introduces a lane change detection algorithm and assessed its performance under various light conditions, road types and weather conditions. The algorithm has developed in L3Pilot: a large-scale European pilot project on level 3 automation. In the current study, the algorithm was tested with data from a Dutch Field Operational Test on SAE Level 2 systems. The algorithm was assessed against manually annotated video recordings. New is that validation was executed with Dutch Field Operational Test data of different participants and vehicles, distinguishing three situational variables factors. These were day vs night, motorways vs trunk roads and dry vs rain. A bootstrap procedure was used to assess the statistical significance of differences among the conditions. The conclusion is that the algorithm in combination with the provided data is effective in detecting lane changes when data is collected on a sample of Dutch motorways, irrespective of light and precipitation conditions. However, the quality of the sensor signals was worse on trunk roads, yielding significantly worse lane change detection performance (for all light and precipitation conditions). Subject Event DetectionVehicle DrivingIntelligent VehiclesLane Change Detection To reference this document use: http://resolver.tudelft.nl/uuid:c97b9850-2161-4a16-883e-f5f5f9a317b1 DOI https://doi.org/10.5220/0010998400003191 TNO identifier 968451 Publisher SCITEPRESS – Science and Technology Publications, Lda. ISBN 9789897585739 ISSN 2184-495X Source In Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2022), 36-45 Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.