Truck and Passenger Car Connected Vehicle Penetration on Indiana Roadways

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Journal of Transportation Technologies

ISSN Print: 2160-0473
ISSN Online: 2160-0481
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"Truck and Passenger Car Connected Vehicle Penetration on Indiana Roadways"
written by Rahul Suryakant Sakhare, Margaret Hunter, Justin Mukai, Howell Li, Darcy Michael Bullock,
published by Journal of Transportation Technologies, Vol.12 No.4, 2022

has been cited by the following article(s):

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[3]	Comparison at Scale of Traffic Signal Cycle Split Failure Identification from High-Resolution Controller and Connected Vehicle Trajectory Data
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[4]	An Update on Passenger Vehicle Speeds at Roundabouts
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[5]	Applications of using connected vehicle data for pavement quality analysis
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[6]	Intersection Type Classification from Connected Vehicle Data Using a Convolutional Neural Network
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[7]	Application of Connected Truck Data to Evaluate Spatiotemporal Impact of Rest Area Closures on Ramp Parking
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[8]	Development of Latitude/Longitude (and Route/Milepost) Model for Positioning Traffic Management Cameras
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[9]	Statewide Identification and Ranking of Signalized Intersections Needing Capacity Improvements
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[10]	TECHNIQUES FOR REDUCING TRAFFIC MANAGEMENT CENTER CAMERA POSITIONING LATENCY FOR ACCELERATED INCIDENT RESPONSE
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[11]	Connected Vehicle-Centric Dashboards for TMC of the Future
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[12]	Actionable Traffic Signal Performance Measures from Large-scale Vehicle Trajectory Analysis
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[13]	Impact of Rain Intensity on Interstate Traffic Speeds Using Connected Vehicle Data. Vehicles 2023, 5, 133–155
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[14]	Analysis of Connected Vehicle Data to Quantify National Mobility Impacts of Winter Storms for Decision Makers and Media Reports
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[16]	Correlating Connected Vehicle Estimated Deceleration Events with Crash Incidents near Interstate Interchanges
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[17]	Methodology for Automatically Setting Camera View to Mile Marker for Traffic Incident Management
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[18]	Impact of Rain Intensity on Interstate Traffic Speeds Using Connected Vehicle Data
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[19]	Systemwide Identification of Signal Retiming Opportunities with Connected Vehicle Data to Reduce Split Failures
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[20]	Comparison of arrivals on green estimations from vehicle detection and connected vehicle data
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[21]	Methodology for the identification of shock wave type and speed in a traffic stream using connected vehicle data
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[22]	Comparison of estimated cycle split failures from high-resolution controller event and connected vehicle trajectory data
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[23]	Using connected vehicle data to evaluate national trip trends
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[24]	Continuous Flow Intersection Performance Measures Using Connected Vehicle Data
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[25]	National Mobility Analysis for All Interstate Routes in the United States: December 2022
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[26]	Impacts to Traffic Behavior from Queue Warning Truck: Current Pilot Project
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[1]	Applications of using connected vehicle data for pavement quality analysis Frontiers in Future Transportation, 2024 DOI:10.3389/ffutr.2023.1239744

[2]	Intersection Type Classification from Connected Vehicle Data Using a Convolutional Neural Network Data Science for Transportation, 2024 DOI:10.1007/s42421-023-00087-6

[3]	Intersection Type Classification from Connected Vehicle Data Using a Convolutional Neural Network Data Science for Transportation, 2024 DOI:10.1007/s42421-023-00087-6

[4]	Systemwide Identification of Signal Retiming Opportunities with Connected Vehicle Data to Reduce Split Failures Transportation Research Record: Journal of the Transportation Research Board, 2023 DOI:10.1177/03611981231168844

[5]	Comparison of Arrivals on Green Estimations from Vehicle Detection and Connected Vehicle Data Transportation Research Record: Journal of the Transportation Research Board, 2023 DOI:10.1177/03611981231168116

[6]	Systemwide Identification of Signal Retiming Opportunities with Connected Vehicle Data to Reduce Split Failures Transportation Research Record: Journal of the Transportation Research Board, 2023 DOI:10.1177/03611981231168844

[7]	Comparison of Arrivals on Green Estimations from Vehicle Detection and Connected Vehicle Data Transportation Research Record: Journal of the Transportation Research Board, 2023 DOI:10.1177/03611981231168116

[8]	Systemwide Identification of Signal Retiming Opportunities with Connected Vehicle Data to Reduce Split Failures Transportation Research Record: Journal of the Transportation Research Board, 2023 DOI:10.1177/03611981231168844

[9]	Comparison of Arrivals on Green Estimations from Vehicle Detection and Connected Vehicle Data Transportation Research Record: Journal of the Transportation Research Board, 2023 DOI:10.1177/03611981231168116

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