Exploring the potential of market-available connected vehicle data in border crossing time estimation

This study evaluates the potential of market-available crowdsourced driving data—connected vehicle (CV) data in estimating crossing times for passenger vehicles at ports of entry (POEs). Two months of CV data collected from a POE at the US-Mexico border in El Paso, Texas were processed using cloud c...

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المؤلفون الرئيسيون: Jalilifar, E, Li, X, Martin, M, Huang, X
التنسيق: Journal article
اللغة:English
منشور في: SAGE Publications 2024
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author Jalilifar, E
Li, X
Martin, M
Huang, X
author_facet Jalilifar, E
Li, X
Martin, M
Huang, X
author_sort Jalilifar, E
collection OXFORD
description This study evaluates the potential of market-available crowdsourced driving data—connected vehicle (CV) data in estimating crossing times for passenger vehicles at ports of entry (POEs). Two months of CV data collected from a POE at the US-Mexico border in El Paso, Texas were processed using cloud computation tools to generate hourly aggregated border crossing times (CV-Time). In addition, this study also generated different variables to characterize the speed profile of CVs at different locations along a POE. Different regression models were developed to estimate border crossing times based on CV-generated variables and compared with ground truth observations from existing monitoring systems. The results show that the CV-Time is strongly correlated with the ground truth observations with a correlation rate of 0.82. The best-fitted Gradient Boost Regression model achieved an RMSE of 15.50 and MAPE of 25%. Our findings suggest that market-available CV data is promising for monitoring border crossing times, especially for supplementing physical monitoring systems when they are down for maintenance.
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spelling oxford-uuid:bf0f6ab5-f8b4-42f7-b0e3-231f7f6edf472024-11-28T11:55:13ZExploring the potential of market-available connected vehicle data in border crossing time estimationJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bf0f6ab5-f8b4-42f7-b0e3-231f7f6edf47EnglishSymplectic ElementsSAGE Publications2024Jalilifar, ELi, XMartin, MHuang, XThis study evaluates the potential of market-available crowdsourced driving data—connected vehicle (CV) data in estimating crossing times for passenger vehicles at ports of entry (POEs). Two months of CV data collected from a POE at the US-Mexico border in El Paso, Texas were processed using cloud computation tools to generate hourly aggregated border crossing times (CV-Time). In addition, this study also generated different variables to characterize the speed profile of CVs at different locations along a POE. Different regression models were developed to estimate border crossing times based on CV-generated variables and compared with ground truth observations from existing monitoring systems. The results show that the CV-Time is strongly correlated with the ground truth observations with a correlation rate of 0.82. The best-fitted Gradient Boost Regression model achieved an RMSE of 15.50 and MAPE of 25%. Our findings suggest that market-available CV data is promising for monitoring border crossing times, especially for supplementing physical monitoring systems when they are down for maintenance.
spellingShingle Jalilifar, E
Li, X
Martin, M
Huang, X
Exploring the potential of market-available connected vehicle data in border crossing time estimation
title Exploring the potential of market-available connected vehicle data in border crossing time estimation
title_full Exploring the potential of market-available connected vehicle data in border crossing time estimation
title_fullStr Exploring the potential of market-available connected vehicle data in border crossing time estimation
title_full_unstemmed Exploring the potential of market-available connected vehicle data in border crossing time estimation
title_short Exploring the potential of market-available connected vehicle data in border crossing time estimation
title_sort exploring the potential of market available connected vehicle data in border crossing time estimation
work_keys_str_mv AT jalilifare exploringthepotentialofmarketavailableconnectedvehicledatainbordercrossingtimeestimation
AT lix exploringthepotentialofmarketavailableconnectedvehicledatainbordercrossingtimeestimation
AT martinm exploringthepotentialofmarketavailableconnectedvehicledatainbordercrossingtimeestimation
AT huangx exploringthepotentialofmarketavailableconnectedvehicledatainbordercrossingtimeestimation