Lessons Learned From Deploying Autonomous Vehicles at UC San Diego

EasyChair Preprint 1295

Abstract

While most autonomous driving efforts reported are directed for general driving and mainly on major roads, there are numerous applications for autonomous vehicles for last mile mobility–from person mobility and mail delivery to flexible recharging of cars in parking structures. Over the last year, we have designed vehicles for the micro-mobility challenge. Our approach was based on adoption of the open source Autoware system. The system was taken as a starting point for the design of a robust solution. Proposed requirements include a robust control design, a shift towards increased use of image data over LiDAR data, handling of a richer set of vehicles / pedestrians in a last mile scenario, and overall system characterization and evaluation. We present an overview of the overall design and the design decisions for construction of a vehicles for last-mile delivery.

Keyphrases: Autonomous, Dense point cloud, Ego vehicle, Intelligent, LiDAR data, Point Cloud Library, STOP sign, San Diego, Transportation, Vehicles, autonomous navigation, autonomous vehicle, development platform, ground removal, last-mile transportation, local planner, micro-transit, open source, point cloud, point cloud map, systems, uc san diego, vision based lane detection

@booklet{EasyChair:1295,
  author    = {David Paz and Po-Jung Lai and Sumukha Harish and Hengyuan Zhang and Nathan Chan and Chun Hu and Sumit Binnani and Henrik Christensen},
  title     = {Lessons Learned From Deploying Autonomous Vehicles at UC San Diego},
  howpublished = {EasyChair Preprint 1295},
  year      = {EasyChair, 2019}}