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 dur ing low-volume overnight hours. This paper reports on an evaluation that looked at both connected passenger cars and connected trucks. This stud y 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 9 th to 15 th 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 w ere 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.
KeywordsConnected Vehicle DataTrucksPenetrationBig Data
Federal Highway Administration (2019) Highway Statistics 2019. https://www.fhwa.dot.gov/policyinformation/statistics/2019/
Indiana Department of Transportation (2022) Traffic Data. https://www.in.gov/indot/resources/traffic-data/
Mathew, J., Desai, J., Sakhare, R.S., Kim, W., Li, H. and Bullock, D. (2021) Big Data Applications for Managing Roadways. ITE Journal, 91, 28-35.
Sakhare, R.S., Desai, J., Li, H., Kachler, M.A. and Bullock, D.M. (2022) Methodology for Monitoring Work Zones Traffic Operations Using Connected Vehicle Data. Safety, 8, Article No. 41. https://doi.org/10.3390/safety8020041
Sakhare, R.S., Desai, J.C., Mathew, J.K., McGregor, J.D. and Bullock, D.M. (2021) Evaluation of the Impact of Presence Lighting and Digital Speed Limit Trailers on Interstate Speeds in Indiana Work Zones. Journal of Transportation Technologies, 11, 157-167. https://doi.org/10.4236/jtts.2021.112010
Desai, J., Sakhare, R., Rogers, S., Mathew, J.K., Habib, A. and Bullock, D. (2021) Using Connected Vehicle Data to Evaluate Impact of Secondary Crashes on Indiana Interstates. 2021 IEEE International Intelligent Transportation Systems Conference, Indianapolis, 19-22 September 2021, 4057-4063. https://doi.org/10.1109/ITSC48978.2021.9564653
Desai, J., Mahlberg, J., Kim, W., Sakhare, R., Li, H., McGuffey, J. and Bullock, D.M. (2021) Leveraging Telematics for Winter Operations Performance Measures and Tactical Adjustment. Journal of Transportation Technologies, 11, 611-627. https://doi.org/10.4236/jtts.2021.114038
McNamara, M., Sakhare, R.S., Li, H., Baldwin, M. and Bullock, D. (2017) Integrating Crowdsourced Probe Vehicle Traffic Speeds into Winter Operations Performance Measures. Transportation Research Board 96th Annual Meeting, Washington DC, 8-12 January 2017, No. 17-00161.
Li, H., Sakhare, R.S., Mathew, J.K., Mackey, J. and Bullock, D.M. (2018) Estimating Intersection Control Delay Using High Fidelity Commercial Probe Vehicle Trajectory Data. Transportation Research Board Annual Meeting, Washington DC, 7-11 January 2018, No. 18-00345.
Saldivar-Carranza, E.D., Hunter, M., Li, H., Mathew, J. and Bullock, D.M. (2021) Longitudinal Performance Assessment of Traffic Signal System Impacted by Long-Term Interstate Construction Diversion Using Connected Vehicle Data. Journal of Transportation Technologies, 11, 644-659. https://doi.org/10.4236/jtts.2021.114040
Saldivar-Carranza, E., Li, H., Mathew, J., Hunter, M., Sturdevant, J. and Bullock, D.M. (2021) Deriving Operational Traffic Signal Performance Measures from Vehicle Trajectory Data. Transportation Research Record: Journal of the Transportation Research Board, 2675, 1250-1264. https://doi.org/10.1177/03611981211006725
Sakhare, R.S., Desai, J., Mathew, J., Kim, W., Mahlberg, J., Li, H. and Bullock, D.M. (2021) Evaluating the Impact of Vehicle Digital Communication Alerts on Vehicles (No. FHWA/IN/JTRP-2021/19). Purdue University. Joint Transportation Research Program.
Day, C., McNamara, M., Li, H., Sakhare, R., Desai, J., Cox, E., Horton, D. and Bullock, D. (2016) 2015 Indiana Mobility Report and Performance Measure Dashboards. Purdue University, West Lafayette. https://doi.org/10.5703/1288284316352
Hunter, M., Mathew, J.K., Cox, E., Blackwell, M. and Bullock, D.M. (2021) Estimation of Connected Vehicle Penetration Rate on Indiana Roadways. Purdue University, West Lafayette. https://doi.org/10.5703/1288284317343
Coleri, S., Cheung, S.Y. and Varaiya, P. (2004) Sensor Networks for Monitoring Traffic. Allerton Conference on Communication, Control and Computing, Monticello, 29 September-1 October 2004, 32-40.
Wang, Y. and Nihan, N.L. (2003) Can Single-Loop Detectors Do the Work of Dual-Loop Detectors? Journal of Transportation Engineering, 129, 169-176. https://doi.org/10.1061/(ASCE)0733-947X(2003)129:2(169)
Cheung, S.Y., Ergen, S.C. and Varaiya, P. (2005) Traffic Surveillance with Wireless Magnetic Sensors. Proceedings of the 12th ITS World Congress, Vol. 1917, San Francisco, 6-10 November 2005, Article ID: 173181.
Bikowitz, E.W. and Ross, S.P. (1985) Evaluation and Improvement of Inductive Loop Traffic Detectors. Transportation Research Record, 1010, 76-80.
Sun, C., Ritchie, S.G. and Tsai, K. (1998) Algorithm Development for Derivation of Section-Related Measures of Traffic System Performance Using Inductive Loop Detectors. Transportation Research Record: Journal of the Transportation Research Board, 1643, 171-180. https://doi.org/10.3141/1643-21
Li, C., Ikeuchi, K. and Sakauchi, M. (1999) Acquisition of Traffic Information Using a Video Camera with 2D Spatio-Temporal Image Transformation Technique. Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383), Tokyo, 5-8 October 1999, 634-638. https://doi.org/10.1109/ITSC.1999.821135
Anderson, C.A., Michalopoulos, P.G. and Jacobson, R.D. (1995) Cost Benefit Analysis of Video-Based Vehicle Detection. Pacific Rim TransTech Conference. 1995 Vehicle Navigation and Information Systems Conference Proceedings. 6th International VNIS. A Ride into the Future, Seattle, 30 July-2 August 1995, 508-515. https://doi.org/10.1109/VNIS.1995.518885
Tseng, B.L., Lin Ching-Yung, and Smith, J.R. (2002) Real-Time Video Surveillance for Traffic Monitoring Using Virtual Line Analysis. Proceedings. IEEE International Conference on Multimedia and Expo, Vol. 2, Lausanne, 26-29 August 2002, 541-544. https://doi.org/10.1109/ICME.2002.1035671
Cerutti-Maori, D., Klare, J., Brenner, A.R. and Ender, J.H.G. (2008) Wide-Area Traffic Monitoring With the SAR/GMTI System PAMIR. IEEE Transactions on Geoscience and Remote Sensing, 46, 3019-3030. https://doi.org/10.1109/TGRS.2008.923026
Alimenti, F., Placentino, F., Battistini, A., Tasselli, G., Bernardini, W., Mezzanotte, P., Rascio, D., Palazzari, V., Leone, S., Scarponi, A., Porzi, N., Comez, M. and Roselli, L. (2007) A Low-Cost 24GHz Doppler Radar Sensor for Traffic Monitoring Implemented in Standard Discrete-Component Technology. 2007 European Microwave Conference, Munich, 9-12 October 2007, 1441-1444. https://doi.org/10.1109/EUMC.2007.4405476
Samczynski, P., Kulpa, K., Malanowski, M., Krysik, P. and Maslikowski, L. (2011) A Concept of GSM-Based Passive Radar for Vehicle Traffic Monitoring. 2011 Microwaves, Radar and Remote Sensing Symposium, Kiev, 25-27 August 2011, 271-274. https://doi.org/10.1109/MRRS.2011.6053652
Jain, N.K., Saini, R.K. and Mittal, P. (2019) A Review on Traffic Monitoring System Techniques. In: Ray, K., Sharma, T., Rawat, S., Saini, R. and Bandyopadhyay, A., Eds., Soft Computing: Theories and Applications, Vol. 742, 569-577. https://doi.org/10.1007/978-981-13-0589-4_53
Herrera, J.C., Work, D.B., Herring, R., (Jeff) Ban, X., Jacobson, Q. and Bayen, A.M. (2010) Evaluation of Traffic Data Obtained via GPS-Enabled Mobile Phones: The Mobile Century Field Experiment. Transportation Research Part C: Emerging Technologies, 18, 568-583. https://doi.org/10.1016/j.trc.2009.10.006
Leduc, G. (2008) Road Traffic Data: Collection Methods and Applications. Working Papers on Energy, Transport and Climate Change, 1, 1-55.
Cao, J. and Ding, Q. (2019) Present Situation and Development of Service Trade for Advanced Passenger Car in Xi’an. Modern Economy, 10, 1090-1094. https://doi.org/10.4236/me.2019.104073
Quiroga, C.A. and Bullock, D. (1998) Travel Time Studies with Global Positioning and Geographic Information Systems: An Integrated Methodology. Transportation Research Part C: Emerging Technologies, 6, 101-127. https://doi.org/10.1016/S0968-090X(98)00010-2
Wang, D. (2007) Google Official Blog: Stuck in Traffic? https://googleblog.blogspot.com/2007/02/stuck-in-traffic.html
Levine, U. (2019) From the Co-Founder of Waze, a Blueprint to Eliminate Traffic Jams. Forbes. https://www.forbes.com/sites/startupnationcentral/2019/01/27/from-the-co-founder-of-waze-a-blueprint-to-eliminate-traffic-jams/?sh=1bc2ec1aa8f7
Indiana Department of Transportation (2022) Innovative Operations. https://www.in.gov/indot/current-programs/innovative-programs/innovative-operations/
Hoseinzadeh, N., Liu, Y., Han, L.D., Brakewood, C. and Mohammadnazar, A. (2020) Quality of Location-Based Crowdsourced Speed Data on Surface Streets: A Case Study of Waze and Bluetooth Speed Data in Sevierville, TN. Computers, Environment and Urban Systems, 83, Article ID: 101518. https://doi.org/10.1016/j.compenvurbsys.2020.101518
Kim, S. and Coifman, B. (2014) Comparing INRIX Speed Data against Concurrent Loop Detector Stations over Several Months. Transportation Research Part C: Emerging Technologies, 49, 59-72. https://doi.org/10.1016/j.trc.2014.10.002
Haghani, A., Hamedi, M. and Sababadi, K.F. (2009) I-95 Corridor Coalition Vehicle Probe Project: Validation of INRIX Data July-September 2008 Final Report. I-95 Corridor Coalition, No. January, 1-110.
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
Sakhare, R. and Vanajakshi, L. (2020) Reliable Corridor Level Travel Time Estimation Using Probe Vehicle Data. Transportation Letters, 12, 570-579. https://doi.org/10.1080/19427867.2019.1671041
Ahsani, V., Amin-Naseri, M., Knickerbocker, S. and Sharma, A. (2019) Quantitative Analysis of Probe Data Characteristics: Coverage, Speed Bias and Congestion Detection Precision. Journal of Intelligent Transportation Systems, 23, 103-119. https://doi.org/10.1080/15472450.2018.1502667
Zhang, C., Wang, J., Lai, J., Yang, X., Su, Y. and Dong, Z. (2019) Extracting Origin-Destination with Vehicle Trajectory Data and Applying to Coordinated Ramp Metering. Journal of Advanced Transportation, 2019, Article ID: 8469316. https://doi.org/10.1155/2019/8469316
Day, C.M., Li, H., Richardson, L.M., Howard, J., Platte, T., Sturdevant, J.R. and Bullock, D.M. (2017) Detector-Free Optimization of Traffic Signal Offsets with Connected Vehicle Data. Transportation Research Record: Journal of the Transportation Research Board, 2620, 54-68. https://doi.org/10.3141/2620-06
Day, C.M. and Bullock, D.M. (2016) Detector-Free Signal Offset Optimization with Limited Connected Vehicle Market Penetration: Proof-of-Concept Study. Transportation Research Record: Journal of the Transportation Research Board, 2558, 54-65. https://doi.org/10.3141/2558-06
Waddell, J.M., Remias, S.M., Kirsch, J.N. and Trepanier, T. (2020) Utilizing Low-Ping Frequency Vehicle Trajectory Data to Characterize Delay at Traffic Signals. Journal of Transportation Engineering, Part A: Systems, 146, Article ID: 04020069. https://doi.org/10.1061/JTEPBS.0000382
Ma, W., Wan, L., Yu, C., Zou, L. and Zheng, J. (2020) Multi-Objective Optimization of Traffic Signals Based on Vehicle Trajectory Data at Isolated Intersections. Transportation Research Part C: Emerging Technologies, 120, Article ID: 102821. https://doi.org/10.1016/j.trc.2020.102821
Mekker, M.M., Remias, S.M., McNamara, M.L. and Bullock, D.M. (2020) Characterizing Interstate Crash Rates Based on Traffic Congestion Using Probe Vehicle Data. Purdue University, West Lafayette. https://doi.org/10.5703/1288284317119
Sakhare, R.S., Desai, J.C., Mahlberg, J., Mathew, J.K., Kim, W., Li, H., McGregor, J.D. and Bullock, D.M. (2021) Evaluation of the Impact of Queue Trucks with Navigation Alerts Using Connected Vehicle Data. Journal of Transportation Technologies, 11, 561-576. https://doi.org/10.4236/jtts.2021.114035
Li, H., Day, C.M. and Bullock, D.M. (2016) Virtual Detection at Intersections Using Connected Vehicle Trajectory Data. 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, 1-4 November 2016, 2571-2576. https://doi.org/10.1109/ITSC.2016.7795969
Hunter, M., Mathew, J.K., Li, H. and Bullock, D.M. (2021) Estimation of Connected Vehicle Penetration on US Roads in Indiana, Ohio, and Pennsylvania. Journal of Transportation Technologies, 11, 597-610. https://doi.org/10.4236/jtts.2021.114037
Hunter, M. (2022) An Assessment of Connected Vehicle Data: The Evaluation of Intersections for Elevated Safety Risks and Data Representativeness. Purdue University, West Lafayette.
Federal Highway Administration (2016) Travel Monitoring and Traffic Volume. https://www.fhwa.dot.gov/policyinformation/tmguide/
Indiana Department of Transportation (2022) Traffic Statistics. https://www.in.gov/indot/about-indot/central-office/asset-data-collection/traffic-statistics/
Federal Highway Administration (2013) Traffic Monitoring Guide. Office of Highway Policy Information, Washington DC. https://www.fhwa.dot.gov/policyinformation/tmguide/tmg_2013/vehicle-types.cfm