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Detection of Optical Road Markings With Automotive Radar Sensors

Timo Grebner, Lizette Lorraine Tovar Torres, Vinzenz Janoudi, Pirmin Schoeder, Christian Waldschmidt

2023IEEE Sensors Letters11 citationsDOIOpen Access PDF

Abstract

Accurate environmental representations play a crucial role in trajectory planning for autonomous driving. In addition to localizing road users, obstacles, and road boundaries, the identification of optical road markings is vital for lane recognition. While optical systems, such as cameras and lidar sensors, are commonly employed for this task, they are susceptible to weather conditions. This letter introduces a novel approach that utilizes automotive chirp-sequence radar sensors exclusively for the detection of conventional road markings. This eliminates the need for additional particles or substances to be applied to the road markings, as demonstrated through an indicative analysis based on real-world measurements in public traffic.

Topics & Concepts

LidarAutomotive industryComputer scienceRadarAdvanced driver assistance systemsComputer visionIdentification (biology)Task (project management)TrajectoryArtificial intelligenceChirpObstacleIntelligent transportation systemRadar systemsReal-time computingRemote sensingEngineeringTransport engineeringGeographyTelecommunicationsSystems engineeringAerospace engineeringPhysicsLaserArchaeologyOpticsBiologyBotanyAstronomyAutonomous Vehicle Technology and SafetyAdvanced Optical Sensing TechnologiesRemote Sensing and LiDAR Applications
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