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arXiv Computer Vision By Marcello Cellina, Akos Kriston, Antonio Migneco, Davide Maggi, Stefano Favelli, Fabrizio Re, Fabrizio Minarini, Andrea Nuovo, Riccardo Dona, Biagio Ciuffo

Beyond the Proving Ground: Independent Public-Road Testing of Assisted Lane Change Systems using LiDAR

Read the original on arXiv Computer Vision →

This study introduces a method for independently testing Assisted Lane Change (ALC) systems on public roads using LiDAR-based vehicle detection and tracking. A campaign on the A31 French motorway evaluated 27 lane‑change maneuvers, finding that 18 were completed, 9 were suppressed, and in six cases the system permitted maneuvers that violated regulatory minimum distance requirements. The results confirm LiDAR’s suitability for such assessments and provide a framework that can aid market surveillance and future regulatory updates.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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