Rachakonda, P.
, Mane, A.
, Schlenoff, C.
and Saidi, K.
(2025),
Methods to evaluate 3D lidars used for automated driving, Measurement, [online], https://doi.org/10.1016/j.measurement.2024.115464, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956735
(Accessed November 21, 2024)
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Methods to evaluate 3D lidars used for automated driving
Published
Author(s)
, Abhilash Mane, ,
Abstract
Evaluating perception sensor systems for on-road autonomous vehicles is still fraught with ambiguity due to the varying and dynamic environmental factors that these vehicles encounter. The critical safety of on-road AV operations is heavily dependent on perception sensors, systems, and technologies which form the "eyes" for these vehicles. For this reason, it is important that these systems provide high fidelity data with low uncertainties and latencies, and that they are robust and tamper-proof. This work is an effort to address some of those pressing needs. The needs are first addressed by developing a testbed with a common data acquisition platform, and second by developing various procedures to evaluate automotive lidars in a static environment.Citation
Measurement
Volume
239
Pub Type
Journals
Download Paper
Keywords
Lidars, 3D sensors, Evaluation, Performance, ROS, Automated driving
Citation
Issues
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Created January 1, 2025, Updated September 4, 2024