Can the Perception Data of Autonomous Vehicles Be Used to Replace Mobile Mapping Surveys?—A Case Study Surveying Roadside City Trees
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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24
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Remote Sensing, Volume 15, issue 7
Abstract
The continuous flow of autonomous vehicle-based data could revolutionize current map updating procedures and allow completely new types of mapping applications. Therefore, in this article, we demonstrate the feasibility of using perception data of autonomous vehicles to replace traditionally conducted mobile mapping surveys with a case study focusing on updating a register of roadside city trees. In our experiment, we drove along a 1.3-km-long road in Helsinki to collect laser scanner data using our autonomous car platform ARVO, which is based on a Ford Mondeo hybrid passenger vehicle equipped with a Velodyne VLS-128 Alpha Prime scanner and other high-grade sensors for autonomous perception. For comparison, laser scanner data from the same region were also collected with a specially-planned high-grade mobile mapping laser scanning system. Based on our results, the diameter at breast height, one of the key parameters of city tree registers, could be estimated with a lower root-mean-square error from the perception data of the autonomous car than from the specially-planned mobile laser scanning survey, provided that time-based filtering was included in the post-processing of the autonomous perception data to mitigate distortions in the obtained point cloud. Therefore, appropriately performed post-processing of the autonomous perception data can be regarded as a viable option for keeping maps updated in road environments. However, point cloud-processing algorithms may need to be adapted for the post-processing of autonomous perception data due to the differences in the sensors and their arrangements compared to designated mobile mapping systems. We also emphasize that time-based filtering may be required in the post-processing of autonomous perception data due to point cloud distortions around objects seen at multiple times. This highlights the importance of saving the time stamp for each data point in the autonomous perception data or saving the temporal order of the data points.Description
Funding Information: We gratefully acknowledge the Henry Ford Foundation for the grant “Towards Automatic Mapping of Road Environment for Civil and Other Engineering Applications Using Autonomous Big Data”, the Academy of Finland, who supported this research through several grants, including “Forest-Human-Machine Interplay—Building Resilience, Redefining Value Networks and Enabling Meaningful Experiences (337656)”, “Feasibility of Inside-Canopy UAV Laser Scanning for Automated Tree Quality Surveying” (334002), “Autonomous Driving on Snow-Covered Terrain” (318437), and “Lidar-based energy efficient ICT solutions” (319011), and the Ministry of Agriculture and Forestry for the research grant “Future forest information system at individual tree level” (VN/3482/2021). Publisher Copyright: © 2023 by the authors.
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Hyyppä, E, Manninen, P, Maanpää, J, Taher, J, Litkey, P, Hyyti, H, Kukko, A, Kaartinen, H, Ahokas, E, Yu, X, Muhojoki, J, Lehtomäki, M, Virtanen, J P & Hyyppä, J 2023, 'Can the Perception Data of Autonomous Vehicles Be Used to Replace Mobile Mapping Surveys?—A Case Study Surveying Roadside City Trees', Remote Sensing, vol. 15, no. 7, 1790. https://doi.org/10.3390/rs15071790