Traffic safety is a priority for State, regional and local transportation agencies. Understanding proximate causes of accidents depends on analyzing past incidents, which in turn depends on having accurate information about these incidents. Transportation agencies also have a responsibility to limit impacts to the environment, including to wildlife. These two priorities, safety and wildlife interactions, coincide in the problem of wildlife-vehicle conflict (WVC). Over the last decade, the Road Ecology Center (REC) has developed several useful tools for reporting wildlife carcasses on roadways (https://wildlifecrossing.net/california), real-time traffic and WVC incident-reporting, and automated WVC analysis system (https://roadecology.ucdavis.edu/hotspots). These systems are based on standardized data-models, data formats, programming workflows, and database management systems. They serve as examples for similarly treating all traffic incidents on state highways, or for all WVC incidents in other states.
Current approaches for recording WVC varies widely among states, and often within states, which reduces opportunities for sharing tools and software and creates barriers to effective analysis and mitigation planning. To record WVC, state DOTs and their partners variously use paper forms, spreadsheets, online forms, and in a few instances smartphones. There has been no effort to standardize these approaches, though the types of data collected and the uses of the data in planning are similar. In conversations with the Road Ecology Center, state DOT staff have expressed the need for new, or updated approaches and tools for collecting, managing, and querying WVC data. The lack of standard specifications for data and metadata is a serious barrier to providing affordable and easy-to-use software approaches for collecting data. It may be the most significant barrier to cost-effective mitigation that also improves driver safety and is ecologically-effective.
I will present software-development approaches based on international standards that can be used to standardize WVC data collection, management, sharing, querying, and quality control. I will describe the types of specifications needed to bring WVC data collection and management systems into line with conventional standards for similar "Big Data" systems. Types of specifications for WVC reporting systems include: data formats, data tracking and verification, data management, security and sharing, image management, long-term archiving (decades), and data transfers among evolving platforms. I will discuss the importance of these specifications for analyzing WVC datasets and to support mitigation decisions, from the level of analysis to combining with other types of data and supporting specific mitigation decisions.