Automated Analysis of Wildlife-Vehicle Conflict Hotspots Using Carcass and Collision Data


Fraser Shilling, Co-Director, UC Davis Road Ecology Center

Fraser Shilling is co-director of the Road Ecology Center at UC Davis, where is also faculty in the Graduate Group in Ecology and Transportation Technology and Policy graduate group. Among other things, he studies and provides training in the interaction between transportation and natural systems. He is also the lead organizer for the International Conference on Ecology and Transportation.


February 13, 2019 , 10:00am - 11:30am


This presentation is sponsored by ITS-Davis’ partnership with the Pacific Southwest Region University Transportation Center

Wildlife-vehicle conflict (WVC) refers to any interaction between wildlife and vehicles/traffic that can have negative impacts for drivers and/or wildlife. This includes animals fleeing from traffic noise/light, to drivers swerving around animals on the road surface, to vehicle collisions with animals. When drivers swerve because of animals on the road and crash, or when vehicles collide with larger animals, this can result in damage to the vehicle, and injury and sometimes death for drivers and passengers. Although there are always some aspects of WVC that are difficult to predict (e.g., when an animal might decide to cross a road), there is also some predictability to WVC that can be highlighted by studying past WVC events. Most states and countries use past WVC occurrences as a source of information for planning mitigation to improve driver safety and to protect animals.

The webinar will cover:

  1. critical elements of data collection needed to inform hotspots analysis;
  2. overview of an automated online tool that provides any US-state user a way to map densities and statistically-significant clusters of WVC (; and
  3. next steps in automating data collection, management, reporting, and use in decision-making.

The presenter will also demonstrate a novel real-time WVC reporting system for California, which could be used to inform driver-assist programs in conventional and automated vehicles. The automated analysis tool was developed in partnership with several state DOTs to ensure utility for state agencies. The tool uses state and interstate highway maps divided into 1 –mile segments and requires some attention to data formatting prior to upload and returns to the user analysis outputs in several forms. The approaches used here are identical to those used in the scientific and technical literature, providing the user assurance that the results can be used in planning.

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