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Zhang, X., Hamedi, M., Haghani, A., Zhang, X., Building, E.L., Hamedi, M., Haghani, A. and Hall, G.L.M. (2015) Arterial Travel Time Validation and Augmentation with Two Independent Data Sources. Transportation Research Record: Journal of the Transportation Research, 2526, 79-89.
https://doi.org/10.3141/2526-09

has been cited by the following article:

• TITLE: Truck and Passenger Car Connected Vehicle Penetration on Indiana Roadways

  AUTHORS: Rahul Suryakant Sakhare, Margaret Hunter, Justin Mukai, Howell Li, Darcy Michael Bullock

  KEYWORDS: Connected Vehicle Data, Trucks, Penetration, Big Data

  JOURNAL NAME: Journal of Transportation Technologies, Vol.12 No.4, August 31, 2022

  ABSTRACT: Commercially available connected vehicle (CV) probe data has been demonstrated to provide scalable and near-real-time methodologies to evaluate the performance of road networks for various applications. However, one of the major concerns of probe data for agencies is data sampling, particularly during low-volume overnight hours. This paper reports on an evaluation that looked at both connected passenger cars and connected trucks. This study analyzed 40 continuous count stations in Indiana that recorded more than 10.8 million vehicles and more than 13 million trips (3 billion records) from CV data over a 1-week period from May 9th to 15th in 2022. The average truck penetration was observed to be 3.4% during overnight hours from 1 AM to 5 AM when the connected passenger car penetration was at the lowest. When both connected trucks and connected car penetration were analyzed, the overall CV penetration was 6.32% on interstates and 5.30% on non-interstate roadways. The paper concludes by recommending that both connected car and connected truck data be used by agencies to increase penetration and reduce the hourly variation in CV penetration. This is particularly important during overnight hours.