IT Can Be Done: Reducing Payment Errors in Unemployment Insurance

The United States Unemployment Insurance Program is a very complex system where mistakes are inevitable, but information technology and communication innovations at the Department of Labor (DOL) have been successful at reducing the rate of improper payments. This issue of The Takeaway outlines how learning from the DOL’s strategies has the potential to benefit other government payment programs and save taxpayers money

Processes of Small Culvert Inspection and Asset Management

Proper drainage is essential for pavement to maximize life expectancy and minimize maintenance. Culverts are a critical asset to facilitate drainage. As with many assets, culverts deteriorate with age and require regular inspection. It is important to have a formalized process of inventory and inspection that is efficient and can effectively support culvert asset management. The current culvert inspection and asset management processes for the Indiana Department of Transportation (INDOT) have been modeled over the years on the bridge inspection process and were recently evaluated. A study was undertaken to further evaluate the current culvert asset management practices. Approximately 700 small culverts and catch basins were visited and evaluated using both the traditional culvert inspection practices and a revised asset management evaluation scale. The paper summarizes the findings of this evaluation and concludes by making recommendations for process improvements. These recommendations include the addition of photos to the culvert database, a revised rating scale, advanced planning of inspection schedules, a formalized process for culvert reassessments, the creation of a separate catch basin inlet inventory, various improvements to the inventory process, and a dedicated staff to complete inspections efficiently. It is also noted that building a reliable database will show historical trends and can eventually lead to a study of small culvert inspections and culvert longevity, which will lead to improved asset management

Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data

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

Impacts to Traffic Behavior from Queue Warning Truck: Current Pilot Project

The Indiana Department of Transportation (INDOT) started deploying queue warning trucks ahead of interstate work zones to alert motorists of queued traffic. Along with visually alerting the motorists, digital alerts were integrated with navigational applications such as Apple Maps, Waze, and the in-vehicle infotainment system of Stellantis vehicles. More than 45,000 hours of alerting was provided to motorists across various interstates in Indiana over a 26-month period. This report evaluated the impact of queue warning trucks on traffic using hard braking events and traffic speeds provided by granular connected trajectory vehicle data. Evaluation of over 370 hours of queuing with the presence of queue trucks and 52 hours of queuing without the queue trucks indicated a decrease in hard braking events by 80% when trucks were present with digital alerts. It was also observed that traffic speeds started to reduce approximately 1,500 to 2,000 ft in advance of deployed queue trucks

Crowdsourcing/Winter Operations Dashboard Upgrade

INDOT has recently completed the deployment of Parsons telematics-based dash-cameras, automatic vehicle locator (AVL) positions, and spreader rate monitoring across their winter operations fleet. The motivation of this study was to develop dashboards that integrate connected vehicle data into the real-time monitoring and after-action review of winter storms. Each month approximately 13 billion connected vehicle records are ingested for the state of Indiana and almost 99 billion weather data records are ingested nationwide in 15-minute intervals. This study developed techniques to utilize this connected vehicle data and weather data to monitor real-time mobility of interstates and post storm after-action assessments to identify improvement opportunities of winter operations activities. In multiple instances, these agile reviews have influenced operational changes in snow removal and maintenance around the state, leading to a marked improvement in observed mobility and safety