Evaluating Autonomous Urban Perception and Planning in a 1/10th Scale MiniCity
Name
sensors-22-06793.pdf
Size
17.9 MB
Format
Adobe PDF
Checksum (MD5)
76ba14d3fab0aca6d2925d00d1fb7c51
Author(s)
Buckman, Noam
Hansen, Alex
Karaman, Sertac
Rus, Daniela
Date Issued
September 8, 2022
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Sensors 22 (18): 6793 (2022)
Version
Final published version
Abstract
We present the MiniCity, a multi-vehicle evaluation platform for testing perception hardware and software for autonomous vehicles. The MiniCity is a 1/10th scale city consisting of realistic urban scenery, intersections, and multiple fully autonomous 1/10th scale vehicles with state-of-the-art sensors and algorithms. The MiniCity is used to evaluate and test perception algorithms both upstream and downstream in the autonomy stack, in urban driving scenarios such as occluded intersections and avoiding multiple vehicles. We demonstrate the MiniCity’s ability to evaluate different sensor and algorithm configurations for perception tasks such as object detection and localization. For both tasks, the MiniCity platform is used to evaluate the task itself (accuracy in estimating obstacle pose and ego pose in the map) as well as the downstream performance in collision avoidance and lane following, respectively.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.3390/s22186793
