Estimating Vehicle Speed with Consumer Grade Mobile LiDAR

LiDAR (Light Detection and Ranging) is an emerging sensor technology that measures the time of flight of an emitted laser to measure the depth of surrounding objects. While historically LiDAR has been relegated to industrial and research spaces due to its prohibitive pricing and large form factor, recent developments have made it possible to include short range LiDAR on mobile devices. It is reasonable to postulate that technological developments will enable further adoption and performance enhancements. The high accuracy and resilience of LiDAR proves critical in providing autonomous vehicles robust information on their surroundings. But what if this capability could also be used to enhance the safety of the estimated 50 million commuters using bicycles, e-bikes, and scooters - micromobility riders - sharing the road, often dangerously, with cars? We explore the feasibility of reliably and accurately determining vehicle speed using a LiDAR-enabled mobile device mounted to a bicycle. We implemented an iOS application to gather real-world driving data, created a vehicle track matching algorithm to ascertain ground truth speed, and evaluated both a heuristic and a learned approach to estimate speed on LiDAR data.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Wang, Ming

Advisor dc:contributor.advisor

• Balakrishnan, Hari

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/144817

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/144817