A comparative assessment of the LWR-IM traffic model using linear regression

Traffic models used for predictions of traffic parameters needs to be validated. This paper presents a comparative assessment to validate the predictive ability of the Lighthill-Witham-Richards - Integrated Model (LWR-IM) traffic model in simulating average delays in urban arterials using linear reg...

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Published in:2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
Main Author: Ng K.M.; Reaz M.B.I.; Ali M.A.M.; Razak N.A.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018184158&doi=10.1109%2fICAEES.2016.7888122&partnerID=40&md5=381b727b5445d3e59321ee5095f0f09d
id 2-s2.0-85018184158
spelling 2-s2.0-85018184158
Ng K.M.; Reaz M.B.I.; Ali M.A.M.; Razak N.A.
A comparative assessment of the LWR-IM traffic model using linear regression
2016
2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016


10.1109/ICAEES.2016.7888122
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018184158&doi=10.1109%2fICAEES.2016.7888122&partnerID=40&md5=381b727b5445d3e59321ee5095f0f09d
Traffic models used for predictions of traffic parameters needs to be validated. This paper presents a comparative assessment to validate the predictive ability of the Lighthill-Witham-Richards - Integrated Model (LWR-IM) traffic model in simulating average delays in urban arterials using linear regression. For this purpose, the LWR-IM, TRANSYT, CTM and HCM 2000 are applied to a test intersection. Average delays are simulated by these models based on 20 different traffic scenarios. Average delays simulated by these traffic models are analyzed using the linear regression to assess how closely fitted the delays simulated by the LWR-IM with delays simulated by TRANSYT, CTM and HCM 2000. The regression reveals high degrees of correspondence with R2 exceeding 0.9 for linear regression of average delays from the LWR-IM with predictions from the other traffic models. © 2016 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper

author Ng K.M.; Reaz M.B.I.; Ali M.A.M.; Razak N.A.
spellingShingle Ng K.M.; Reaz M.B.I.; Ali M.A.M.; Razak N.A.
A comparative assessment of the LWR-IM traffic model using linear regression
author_facet Ng K.M.; Reaz M.B.I.; Ali M.A.M.; Razak N.A.
author_sort Ng K.M.; Reaz M.B.I.; Ali M.A.M.; Razak N.A.
title A comparative assessment of the LWR-IM traffic model using linear regression
title_short A comparative assessment of the LWR-IM traffic model using linear regression
title_full A comparative assessment of the LWR-IM traffic model using linear regression
title_fullStr A comparative assessment of the LWR-IM traffic model using linear regression
title_full_unstemmed A comparative assessment of the LWR-IM traffic model using linear regression
title_sort A comparative assessment of the LWR-IM traffic model using linear regression
publishDate 2016
container_title 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering, ICAEES 2016
container_volume
container_issue
doi_str_mv 10.1109/ICAEES.2016.7888122
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018184158&doi=10.1109%2fICAEES.2016.7888122&partnerID=40&md5=381b727b5445d3e59321ee5095f0f09d
description Traffic models used for predictions of traffic parameters needs to be validated. This paper presents a comparative assessment to validate the predictive ability of the Lighthill-Witham-Richards - Integrated Model (LWR-IM) traffic model in simulating average delays in urban arterials using linear regression. For this purpose, the LWR-IM, TRANSYT, CTM and HCM 2000 are applied to a test intersection. Average delays are simulated by these models based on 20 different traffic scenarios. Average delays simulated by these traffic models are analyzed using the linear regression to assess how closely fitted the delays simulated by the LWR-IM with delays simulated by TRANSYT, CTM and HCM 2000. The regression reveals high degrees of correspondence with R2 exceeding 0.9 for linear regression of average delays from the LWR-IM with predictions from the other traffic models. © 2016 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
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record_format scopus
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