NDLI: Performance Comparison of Filtering Techniques for Real Time Traffic Density Estimation under Indian Urban Traffic Scenario

Content Provider	IEEE Xplore Digital Library
Author	Dhivyabharathi, B. Fulari, S. Amrutsamanvar, R. Vanajakshi, L. Subramanian, S.C. Panda, M.
Copyright Year	2015
Description	Author affiliation: Centre for Adv. Internet Archit., Swinburne Univ. of Technol., Hawthorn, VIC, Australia (Panda, M.) \|\| Dept. of Eng. Design, Indian Inst. of Technol., Chennai, Chennai, India (Subramanian, S.C.) \|\| Dept. of Civil Eng., Indian Inst. of Technol. Madras, Chennai, India (Dhivyabharathi, B.; Fulari, S.; Amrutsamanvar, R.; Vanajakshi, L.)
Abstract	Real time traffic state estimation is important to facilitate better traffic management in urban areas and is a prime concern from a traffic engineer's viewpoint. Traffic density is a key traffic variable that can be used to characterize the traffic system and can be a valuable input to the functional areas of Intelligent Transportation Systems (ITS). However, measurement of density in the field is difficult due to several practical limitations. This creates a need for inferring density from other traffic variables that are easily measurable in the field. In this paper, model based approaches for the estimation of traffic density are discussed. The non-linear model equations are based on the conservation principle and the fundamental traffic flow. The technique used for recursive estimation of density in real time plays a key role in terms of estimation accuracy. The Extended Kalman Filter (EKF) is a common tool for recursive estimation for nonlinear systems. This study investigates the application of particle filter (PF) and Unscented Kalman Filter (UKF) as alternatives to (EKF) for non-linear traffic state estimation in the context of traffic conditions in India. The estimated density values were corroborated using manually extracted field density values. The performance of these methods was also compared with a base model, where the fundamental traffic flow equation was used for calculating density. The convergence properties of these filters were also analyzed.
Starting Page	1442
Ending Page	1447
File Size	287984
Page Count	6
File Format	PDF
ISSN	21530017
e-ISBN	9781467365963
DOI	10.1109/ITSC.2015.238
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-15
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematical model Estimation Kalman filters Vehicles Roads Accuracy Data models
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in