research-article

Toward a crowdsourcing solution to estimate border crossing times using market-available connected vehicle data

Authors:

Ehsan Jalilifar,

Xiao Li,

Michael Martin,

Xiao HuangAuthors Info & Claims

GeoIndustry '22: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications

Article No.: 3, Pages 1 - 4

https://doi.org/10.1145/3557922.3567669

Published: 14 November 2022 Publication History

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Abstract

Effectively monitoring border crossing time is of great importance to various stakeholders. Border crossing information systems currently implemented along the United States-Mexico border require a large installed base of sensors, costly for installation and maintenance. This study provides a preliminary assessment of market-available connected vehicle (CV) data in border crossing time estimation. We evaluated one week of CV data collected at the Paso del Norte (PDN) port of entry (POE). We used a set of big data analytic tools to process big CV datasets and generated CV-based border crossing times (CV-Time). Then, we evaluated the correlation between the CV-Time and the existing Bluetooth-generated border crossing times (Bluetooth-Time) at the PDN POE. Last, we built a regression model to estimate the Bluetooth-Time (ground truth data) based on CV-based variables. The results demonstrate that the CV-Time is strongly correlated with the Bluetooth-Time, with a correlation rate of approximately 0.89. This study demonstrates that the market-available CV data is a potential data source for monitoring border crossing times.

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Cited By

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Huang XWang SYang DHu TChen MZhang MZhang GBiljecki FLu TZou LWu CPark YLi XLiu YFan HMitchell JLi ZHohl A(2024)Crowdsourcing Geospatial Data for Earth and Human Observations: A ReviewJournal of Remote Sensing10.34133/remotesensing.01054Online publication date: 22-Jan-2024
https://doi.org/10.34133/remotesensing.0105
Sakhare RDesai JSaldivar-Carranza EBullock D(2024)Methodology for Monitoring Border Crossing Delays with Connected Vehicle Data: United States and Mexico Land Crossings Case StudyFuture Transportation10.3390/futuretransp40100074:1(107-129)Online publication date: 2-Feb-2024
https://doi.org/10.3390/futuretransp4010007
Jalilifar ELi XMartin MHuang X(2024)Exploring the potential of market-available connected vehicle data in border crossing time estimationTransactions in Urban Data, Science, and Technology10.1177/275412312412267303:1-2(31-45)Online publication date: 31-Jan-2024
https://doi.org/10.1177/27541231241226730

Index Terms

Toward a crowdsourcing solution to estimate border crossing times using market-available connected vehicle data
1. Applied computing
  1. Operations research
    1. Transportation
2. Information systems
  1. Information systems applications

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Published In

GeoIndustry '22: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications

November 2022

30 pages

ISBN:9781450395359

DOI:10.1145/3557922

Editors:
Yiqun Xie
University of Maryland
,
Jia Yu
Washington State University, Apache Software Foundation
,
Emre Eftelioglu
Amazon
,
Heba Aly
Amazon

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 November 2022

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Center for International Intelligent Transportation Research, Texas A&M Transportation Institute

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SIGSPATIAL

SIGSPATIAL '22: The 30th International Conference on Advances in Geographic Information Systems

November 1, 2022

Washington, Seattle

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Huang XWang SYang DHu TChen MZhang MZhang GBiljecki FLu TZou LWu CPark YLi XLiu YFan HMitchell JLi ZHohl A(2024)Crowdsourcing Geospatial Data for Earth and Human Observations: A ReviewJournal of Remote Sensing10.34133/remotesensing.01054Online publication date: 22-Jan-2024
https://doi.org/10.34133/remotesensing.0105
Sakhare RDesai JSaldivar-Carranza EBullock D(2024)Methodology for Monitoring Border Crossing Delays with Connected Vehicle Data: United States and Mexico Land Crossings Case StudyFuture Transportation10.3390/futuretransp40100074:1(107-129)Online publication date: 2-Feb-2024
https://doi.org/10.3390/futuretransp4010007
Jalilifar ELi XMartin MHuang X(2024)Exploring the potential of market-available connected vehicle data in border crossing time estimationTransactions in Urban Data, Science, and Technology10.1177/275412312412267303:1-2(31-45)Online publication date: 31-Jan-2024
https://doi.org/10.1177/27541231241226730

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Census big data analytics use: international cross case analysis

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