Completed

Transportation agencies are familiar with traditional traffic data (e.g., speed, volume) produced from traditional data collection methods (e.g., tube counts) and the traditional methods to analyze the data to produce origin-destination tables, segment speed delay etc. However, there are new and emerging traffic data sets (e.g., ubiquitous speed, vehicle specific data) collected from new and emerging data sets (e.g., third-party probe data, sensors) and corresponding alternate methods to analyze the data to understand, for example harsh braking, delays, or level of service/return to normal. The new and emerging traffic data collection methods produce a lot of data (often referred to as Big Data), and some transportation agencies have hired data scientists and artificial intelligence (AI) specialists to conduct data analysis. The analyses and processing of these large sets of data often require additional skills and tools beyond traditional data analysis methods. This is not only due to the large volumes of data, but also because of additional factors such as the conflation of multiple data sets together. The objective of this project was to understand and document different transportation agency examples of new and emerging alternate methods of traffic data analysis through a literature review, interviews, and related webinars.

Roadway Digital Infrastructure (RDI) is a term that has been increasingly used in the context of roadway operations to describe the non-physical aspects that supplement the physical infrastructure in the support of operations. The collection, movement, and use of data is the most widespread example of digital infrastructure. This project describes collaborative and coordinated national-level RDI activities being conducted. In addition to researching and documenting national RDI activities, this ENTERPRISE project conducted engagement and discussions among members around conceptual or actual examples of RDI deployments in their agencies. Key takeaway and themes from these discussion include: transportation agency procurement of RDI systems and support is still evolving, transportation agency integration of RDI into existing systems is challenging, the Department of Transportation (DOT) role in RDI is still evolving with unanswered questions, there is some confusion about the term RDI and the justification for investments in it, and RDI data presents new opportunities and challenges for DOTs.  

A significant increase in traffic-related pedestrian fatalities has occurred in the United States since 2010. Of particular concern are uncontrolled pedestrian crossings at mid-blocks and other uncontrolled approaches, as the majority of pedestrian fatalities occur at non-intersection locations. The objective of this research was to review existing guidance for selecting intelligent transportation system (ITS) countermeasures at uncontrolled pedestrian crossings and uncontrolled approaches, and to identify associate gaps and needs. The project completed a review of existing guidance for selecting ITS pedestrian safety treatments, conducted an interactive meeting with state department of transportation (DOT) traffic safety professionals, and identified potential gaps and needs. The guidance reviewed commonly includes ITS treatments such as blinker signs, flashing beacons, rectangular rapid flashing beacons (RRFBs), and pedestrian hybrid beacons (PHBs). However, the interactive meeting with state DOT traffic safety professionals revealed limited deployment of ITS pedestrian treatments, inconsistency in application of these ITS treatments, and hesitancy with the use of some ITS technologies because drivers and pedestrians may not be familiar with these treatments. Overall, there appears to be a lack of on-road ITS pedestrian treatments for uncontrolled approaches. There may be an opportunity to further develop infrastructure-based pedestrian detection approaches such as cameras, radar, and LiDAR, especially at locations with known safety issues.