Active Sensing on a Bicycle for Simultaneous Search and Tracking of Multiple Rear Vehicles

Woongsun Jeon, Rajesh Rajamani

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This paper uses an inexpensive single-beam laser sensor mounted on a rotationally controlled platform to simultaneously search for and track multiple vehicles that are behind a bicycle. Vehicles in the bicycle's lane and in the adjacent left lane are both considered. The tasks involved are searching both lanes to detect the presence of vehicles, tracking a vehicle's trajectory once it has been detected, and switching between searching and tracking as needed. A rigorous search algorithm that minimizes the number of sensor rotational angles needed to search the entire region of interest is developed. An error covariance matrix approach is utilized to switch between tracking vehicles and searching the region of interest. Detailed simulation results are presented to show how the developed system handles the absence and presence of vehicles in the two lanes and handles different types of lane change maneuvers while tracking multiple vehicles. Since the developed system uses an inexpensive lightweight sensor that is suitable for on-bicycle implementation, it can be used to detect the danger of a collision and provide a corresponding horn-like audio alert to the motorist.

Original languageEnglish (US)
Article number8692650
Pages (from-to)5295-5308
Number of pages14
JournalIEEE Transactions on Vehicular Technology
Volume68
Issue number6
DOIs
StatePublished - Jun 2019

Bibliographical note

Funding Information:
Manuscript received July 30, 2018; revised November 24, 2018, February 1, 2019, and March 27, 2019; accepted April 1, 2019. Date of publication April 16, 2019; date of current version June 18, 2019. This work was supported in part by National Science Foundation under Grant PFI-1631133. The review of this paper was coordinated by Dr. A. Chatterjee. (Corresponding author: Rajesh Rajamani.) The authors are with the Department of Mechanical Engineering, University of Minnesota, Twin Cities, MN 55455 USA (e-mail: jeonx121@umn.edu; rajamani@umn.edu). Digital Object Identifier 10.1109/TVT.2019.2911572

Funding Information:
This work was supported in part by National Science Foundation under Grant PFI-1631133.

Publisher Copyright:
© 1967-2012 IEEE.

Keywords

  • Smart bicycle
  • collision prevention
  • collision warning
  • estimation
  • vehicle tracking

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