Application of particle filter tracking algorithm in autonomous vehicle navigation

K. R. Li, G. T. Lin, L. Y. Lee, J. C. Juang

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

1 Citation (Scopus)

Abstract

The paper describes the design, implementation, and test of an autonomous vehicle navigation system using vehicle model and particle filter tracking algorithm. Typically, a vehicle navigation system comprises of real-time environment perception, vehicle localization, collision avoidance, path planning, and path following. In order to achieve the features for intelligent autonomous vehicle, a sensor suite of integrated inertial measurement unit (IMU), GNSS receiver, and incremental encoder is developed for vehicle position estimation. A map-aided path planning strategy is employed to generate a reference route. To this end, a UMI (User Machine Interface) is developed to facilitate the observation of a goal-oriented path tracking situation. The system utilizes particle filter algorithm to guide the vehicle following the planned path in terms of vehicle estimation control. The recursive particle filter is able to weight the cells and response the angle as well as estimated position information. All the sensors are integrated into an embedded computer platform and able to assess the autonomous driving capability. The test is conducted on campus by installing the sensor suite and embedded computer platform into an electric vehicle.

Original languageEnglish
Title of host publication2013 CACS International Automatic Control Conference, CACS 2013 - Conference Digest
Pages250-255
Number of pages6
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 CACS International Automatic Control Conference, CACS 2013 - Nantou, Taiwan
Duration: 2013 Dec 22013 Dec 4

Publication series

Name2013 CACS International Automatic Control Conference, CACS 2013 - Conference Digest

Other

Other2013 CACS International Automatic Control Conference, CACS 2013
CountryTaiwan
CityNantou
Period13-12-0213-12-04

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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