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 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 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.
Back of queue crashes on Interstates are a major concern for all state transportation departments. In 2020, Indiana DOT begin deploying queue warning trucks with message boards, flashers and digital alerts that could be transmitted to navigation systems such as Waze. This study reports on the deployment and impact evaluation of digital alerts on motorist's assistance patrols and 19 Queue trucks in Indiana. The motorist assistance patrol evaluation is provided qualitatively. A novel analysis of queue warning trucks equipped with digital alerts was conducted during the months of May-July in 2021 using connected vehicle data. This new data set reports locations of anonymous hard-braking events from connected vehicles on the Interstate. Hard-braking events were tabulated for when queueing occurred with and without the presence of a queue warning truck. Approximately 370 hours of queueing with queue trucks present and 58 hours of queueing without queue trucks present were evaluated. Hard-braking events were found to decrease approximately 80% when queue warning trucks were used to alert motorists of impending queues.
There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving within. These markings are also used by original equipment manufacturers (OEM) for implementing advanced safety features such as lane keep assist (LKA) and eventually autonomous operation. However, pavement markings deteriorate over time due to the fact of weather and wear from tires and snowplow operations. Furthermore, their performance varies depending upon lighting (day/night) as well as surface conditions (wet/dry). This paper presents a case study in Indiana where over 5000 miles of interstate were driven and LKA was used to classify pavement markings. Longitudinal comparisons between 2020 and 2021 showed that the percentage of lanes with both lines detected increased from 80.2% to 92.3%. This information can be used for various applications such as developing or updating standards for pavement marking materials (infrastructure), quantifying performance measures that can be used by automotive OEMs to warn drivers of potential problems with identifying pavement markings, and prioritizing agency pavement marking maintenance activities.
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