Multiple hypothesis tracking for automated vehicle perception
作者： George Thomaidis , Leonidas Spinoulas , Panagiotis Lytrivis , Malte Ahrholdt , Grant Grubb
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摘要: The use of multiple hypothesis tracking has proven to provide significant performance benefits over the single GNN or PDA algorithm. Automotive sensors like radars, laser-scanners vision systems are being integrated into vehicles for commercial scientific purposes, in increasing numbers last years. As a result, there is profound literature on this area and several approaches have been proposed problem multi-target, multi-sensor target tracking. most advanced vehicle applications allow highly even fully automated driving. Of course, these require an accurate, robust reliable perception output so that can be driven autonomously. HAVEit EU project investigates application validation applications, technologies going great impact transport safety comfort. In paper MHT algorithm applied real sensor data, installed Volvo Technology demonstrating Automated Queue Assistance. conjunction with simulated scenarios, compared conventional presented.
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