Preventing Animal-Vehicle Crashes using a Smart Detection Technology and Warning System

Abstract

Animal-vehicle collisions (AVCs), and deer-vehicle collisions (DVCs) in particular, are a major safety problem on roads in Virginia, United States. Mitigation measures such as improved fencing and location-specific driver alerts are being implemented and evaluated in Virginia and elsewhere. One of the most promising mitigation methods uses a buried cable animal detection system (BCADS) to provide roadside or in-vehicle warnings to approaching drivers based on the active presence of an animal on or near the roadway. In this study, the Virginia Department of Transportation (VDOT) in collaboration with the Virginia Tech Transportation Institute (VTTI) implemented and monitored the performance of a BCADS on a public road to provide a real-world assessment of system capabilities and possible operation issues. Concurrently, a flashing light “Deer Crossing” warning sign was installed at the site and linked with the BCADS to alert approaching drivers when an animal crossing was detected. Continuous video surveillance data were collected for a year to monitor animal movement, vehicle traffic, and system performance. Study findings indicate that the BCADS is capable of detecting larger animals such as deer, and sometimes smaller animals such as coyotes, with almost 99% reliability. The system also performed well when covered by approximately 0.6 m (2 ft) of snow. Vehicle speed and brake light application data collected during warning sign activation showed that approximately 80% of drivers either braked or slowed in response, indicating that the sign was effective. A 75% reduction in deer-vehicle crashes was observed in the first year after system deployment.

Developing a situation and threat assessment framework for a next generation roadside animal detection system

“…A review of research into collisions that involved an animal found that the indicators used to trigger the warning messages of conventional RADS systems [12–17] were limited to the presence/absence of an animal within a detection area. As safety indicators are usually designed to analyse vehicle‐to‐vehicle collisions [20] rather than animal‐vehicle collisions, additional indicators were required.…”

Intelligent Systems Using Sensors and/or Machine Learning to Mitigate Wildlife–Vehicle Collisions: A Review, Challenges, and New Perspectives

“…Because of these limitations, other solutions such as wildlife–vehicle detection systems have received much attention. These include systems such as break-the-beam [ 17 , 18 , 19 , 20 , 21 ], area cover [ 17 , 18 , 22 , 23 , 24 , 25 , 26 , 27 ], buried cable [ 28 , 29 , 30 ], driver assistance [ 31 ], autonomous vehicles [ 32 ], and mobile mapping animal detection systems (ADSs) [ 33 , 34 ], as well as roadkill detection [ 35 ]. These ADSs are combined with traditional methods to enhance the prediction and detection of animals on the road.…”

Potential Benefits of Animal-Detecting Automatic Emergency Braking Systems Based on U.S. Driving Data

“…Several previous studies have been conducted to characterize different vehicle-animal crash types and hotspots, improve roadways, and design new warning systems to help mitigate vehicle-animal crashes (3)(4)(5)(6)(7). A study in 2005 by Williams and Wells (3) found that many fatal crashes occurred at night and on rural roads, and recommended that additional vehicle-animal countermeasures be deployed to help avoid crashes.…”

“…Sullivan ( 6 ) analyzed the characteristics of vehicle-animal crashes over a two decade period to identify road factors that could mitigate these crashes in the future, finding that forward visibility was critical to avoiding vehicle-animal crashes. A recent study by Druta and Alden ( 7 ) found that deer-vehicle collisions could largely be mitigated by adding a buried cable animal detection system, leading to a 75% reduction in this type of crash in the first year after the system was deployed.…”