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Cárdenas-Benítez, N., Aquino-Santos, R., Magaña-Espinoza, P., Aguilar-Velazco, J., Ed-wards-Block, A. and Medina Cass, A. (2016) Traffic Congestion Detection System through Connected Vehicles and Big Data. Sensors, 16, Article No. 5.
https://doi.org/10.3390/s16050599

has been cited by the following article:

• TITLE: Quantifying the Impact of In-Cab Alerts on Truck Speed Reductions in Ohio

  AUTHORS: Jairaj Desai, Jijo K. Mathew, Darcy M. Bullock

  KEYWORDS: In-Cab Alerts, Connected Truck Data, Driver Alerts, Dangerous Slowdowns

  JOURNAL NAME: Journal of Transportation Technologies, Vol.14 No.3, May 17, 2024

  ABSTRACT: In-cab alerts warn commercial vehicle drivers of upcoming roadway incidents, slowdowns and work zone construction activities. This paper reports on a study evaluating the driver response to in-cab alerts in Ohio. Driver response was evaluated by measuring the statistical trends of vehicle speeds after the in-cab alerts were received. Vehicle speeds pre and post in-cab alert were collected over a 47 day period in the fall of 2023 for trucks traveling on interstate roadways in Ohio. Results show that approximately 22% of drivers receiving Dangerous Slowdown alerts had reduced their speeds by at least 5 mph 30 seconds after receiving such an alert. Segmenting this analysis by speed found that of vehicles traveling at or above 70 mph at the time of alerting, 26% reduced speeds by at least 5 mph. These speed reductions suggest drivers taking actional measures after receiving alerts. Future studies will involve further analysis on the impact of the types of alerts shown, roadway characteristics and overall traffic conditions on truck speeds passing through work zones.