CARLOC: Precisely tracking automobile position

Yurong Jiang, Hang Qiu, Matthew McCartney, Gaurav Sukhatme, Marco Gruteser, Fan Bai, Donald Grimm, Ramesh Govindan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Precise positioning of an automobile to within lane-level precision can enable better navigation and context-awareness. However, GPS by itself cannot provide such precision in obstructed urban environments. In this paper, we present a system called CARLOC for lanelevel positioning of automobiles. CARLOC uses three key ideas in concert to improve positioning accuracy: it uses digital maps to match the vehicle to known road segments; it uses vehicular sensors to obtain odometry and bearing information; and it uses crowd-sourced location estimates of roadway landmarks that can be detected by sensors available in modern vehicles. CARLOC unifies these ideas in a probabilistic position estimation framework, widely used in robotics, called the sequential Monte Carlo method. Through extensive experiments on a real vehicle, we show that CARLOC achieves sub-meter positioning accuracy in an obstructed urban setting, an order-of-magnitude improvement over a high-end GPS device.

Original languageEnglish (US)
Title of host publicationSenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery, Inc
Pages253-265
Number of pages13
ISBN (Electronic)9781450336314
DOIs
StatePublished - Nov 1 2015
Event13th ACM Conference on Embedded Networked Sensor Systems, SenSys 2015 - Seoul, Korea, Republic of
Duration: Nov 1 2015Nov 4 2015

Publication series

NameSenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

Other

Other13th ACM Conference on Embedded Networked Sensor Systems, SenSys 2015
CountryKorea, Republic of
CitySeoul
Period11/1/1511/4/15

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Keywords

  • Accuracy
  • GPS
  • Map

Fingerprint Dive into the research topics of 'CARLOC: Precisely tracking automobile position'. Together they form a unique fingerprint.

  • Cite this

    Jiang, Y., Qiu, H., McCartney, M., Sukhatme, G., Gruteser, M., Bai, F., Grimm, D., & Govindan, R. (2015). CARLOC: Precisely tracking automobile position. In SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems (pp. 253-265). (SenSys 2015 - Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/2809695.2809725