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

Wildlife-vehicle conflict (WVC) occurs when traffic coincides with a place where animals decide to cross the surface of a roadway. State departments of transportation have a consistent need to understand rates and locations of WVC but inconsistent access to tools to measure statistical significance of clusters of WVC which could need mitigation. This research brief summarizes the findings from the associated project, the objective of which was to develop a standard method for analyzing WVC “hotspots” (areas of concern) that any state could use to identify potential locations for WVC mitigation

The Reliability and Effectiveness of a Radar-Based Animal Detection System

This document contains data on the reliability and effectiveness of an animal detection system along U.S. Hwy 95 near Bonners Ferry, Idaho. The system uses a Doppler radar to detect large mammals (e.g., deer and elk) when they approach the highway. The system met most of the suggested minimum norms for reliability. The total time the warning signs were activated was at most 90 seconds per hour, and likely substantially less. Animal detection systems are designed to detect an approaching animal. After an animal has been detected, warning signs are activated which allow drivers to respond. Results showed that 58.1–67.9% of deer were detected sufficiently early for northbound drivers, and 70.4–85% of deer were detected sufficiently early for southbound drivers. The effect of the activated warning signs on vehicle speed was greatest when road conditions were challenging (e.g., freezing temperatures and snow- and ice-covered road surface) and when visibility was low (night). In summer, there was no measurable benefit of activated warning signs, at least not as far as vehicle speed is concerned. Depending on the conditions in autumn and winter, the activated warning signs resulted in a speed reduction of 0.69 to 4.43 miles per hour. The report includes practical recommendations for operation and maintenance of the system and suggestions for potential future research

Computer Vision for a Camel-Vehicle Collision Mitigation System

As the population grows and more land is being used for urbanization, ecosystems are disrupted by our roads and cars. This expansion of infrastructure cuts through wildlife territories, leading to many instances of Wildlife-Vehicle Collision (WVC). These instances of WVC are a global issue that is having a global socio-economic impact, resulting in billions of dollars in property damage and, at times, fatalities for vehicle occupants. In Saudi Arabia, this issue is similar, with instances of Camel-Vehicle Collision (CVC) being particularly deadly due to the large size of camels, which results in a 25% fatality rate [4]. The focus of this work is to test different object detection models on the task of detecting camels on the road. The Deep Learning (DL) object detection models used in the experiments are: CenterNet, EfficientDet, Faster R-CNN, and SSD. Results of the experiments show that CenterNet performed the best in terms of accuracy and was the most efficient in training. In the future, the plan is to expand on this work by developing a system to make countryside roads safer

Road Safety Audit for the Intersection of US 59 and IA 9 in Osceola County, Iowa Final Report, March 2012

The Iowa Department of Transportation (DOT) requested a road safety audit (RSA) of the US 59/IA 9 intersection in northwestern Iowa, just south of the Minnesota border, to assess intersection environmental issues and crash history and recommend appropriate mitigation to address the identified safety issues at the intersection. Although the number of crashes at the location has not been significantly higher than the statewide average for similar intersections, the severity of these crashes has been of concern. This RSA was unique in that it included intersection video observation and recorded traffic conflict data analysis, along with the daylight and nighttime field reviews. This report outlines the findings and recommendations of the RSA team for addressing the safety concerns at this intersection

Requirement analysis for building practical accident warning systems based on vehicular ad-hoc networks

An Accident Warning System (AWS) is a safety application that provides collision avoidance notifications for next generation vehicles whilst Vehicular Ad-hoc Networks (VANETs) provide the communication functionality to exchange these notifi- cations. Despite much previous research, there is little agreement on the requirements for accident warning systems. In order to build a practical warning system, it is important to ascertain the system requirements, information to be exchanged, and protocols needed for communication between vehicles. This paper presents a practical model of an accident warning system by stipulating the requirements in a realistic manner and thoroughly reviewing previous proposals with a view to identify gaps in this area

The Role of Landscape in the Distribution of Deer-Vehicle Collisions in Two Counties in South-Central Mississippi

The number of deer killed by vehicle collisions each year in the United States exceeds the number of deer killed annually through hunting. Deer-vehicle collisions (DVCs) have a vast negative impact on the economy, traffic safety, and general wellbeing of otherwise healthy deer populations. To mitigate DVCs, it is imperative to gain a better understanding of the factors that play a role in their spatial distribution. Much of the existing research has been inconclusive, pointing to a variety of factors that cause DVCs that are specific to study site and region. Very little DVC research has been undertaken in the southern United States, which makes the region particularly important with regard to this issue. Through the use of GIS, remotely sensed imagery, and statistical analysis, this thesis evaluates landscape factors that contribute to the spatial distribution of DVCs within Forrest and Lamar Counties in Mississippi

DEVELOPING A SOUTH CAROLINA TRAFFIC INCIDENT MANAGEMENT PLAN ALONG THE I-26 CORRIDOR BETWEEN COLUMBIA AND CHARLESTON

Traffic Incident Management (TIM) programs are used in many states across the nation to efficiently clear interstate incidents and alleviate congestion in response to incidents. The overarching goal of this research is to maintain safety of the motoring public and incident responders while reducing congestion, secondary collisions, and traffic delays from incidents that occur on South Carolina highways. To reduce incident clearance times along the I-26 corridor between Columbia and Charleston through the implementation of a Traffic Incident Management (TIM) Program, several objectives for this thesis were established to move toward the goal, including; defining gaps between national TIM best-practices and SC TIM practices recommending programmatic changes to address gaps based on best-practices literature, developing training materials to address programmatic changes as needed, and assessing existing performance measurement metrics and suggest improvements to better evaluate changes in program effectiveness. The nationally recommended best practices were compared to the current South Carolina practices. Gaps were observed and SCDOT expressed interest in developing towing, coroner, HAZMAT, and crash investigation procedures. Successful programs involving these groups of responders were evaluated, including implementation costs and challenges. Several successful national programs, as well as those in Florida, Georgia, and numerous other states were included in this step. This specifically included incentive based towing programs, fatality removal programs, HAZMAT training procedures, and crash investigation technologies. It is recommended that these programs be considered and investigated further when implementing a SC TIM plan. It was however noted that while basic HAZMAT training is necessary, a large or full-scale program may not be cost effective. After analyzing the data, areas where data collection could be improved were determined. It is recommended that responders more consistently collect on-scene arrival time for all agencies. Additionally, due to the high number of incidents that seem to be timing out and recording recovery times that are too long, it is recommended that improvements to the data collection process be made

Assessing Vehicle-Related Mortality of Mule Deer in Utah

Roads are essential in modern societies, but as populations grow and traffic volumes rise, roads will continue to be built and expanded. As a result, the effects that roads have on wildlife will likely intensify, making it imperative that managers understand those effects so mitigation can be directed accordingly. In Utah, considerable areas of mule deer (Odocoileus hemionus) habitat have been bisected by roads. Mule deer are commonly involved in vehicle collisions and there is concern that roads and vehicle traffic are impacting populations. This project was conducted to determine the number and demographic effects of deer-vehicle collisions, to examine how movements and survival of deer were impacted by roads, and to develop a smartphone-based reporting system for wildlife-vehicle collisions. Accurate estimates of DVCs are needed to effectively mitigate the effects of roads, but great uncertainty exists with most deer-vehicle collision estimates. I estimated the number of deer-vehicle collisions using carcass surveys, while accounting for several sources of bias to improve accuracy. I estimated that 2-5 % of the statewide deer population was killed in vehicle collisions annually. The effect that vehicle collisions have on deer abundance depended not only on the number of deer killed but also on the demographic groups removed. I found that 65 % of deer killed in vehicle collisions were female and 40 % were adult females. As female deer are the primary drivers of population growth, my data suggest vehicle collisions could significantly affect population abundance. However I was unable to detect a decreasing trend in deer abundance. Deer have distinct movement patterns that affect their distribution in relationship to roads. I analyzed deer movements during two consecutive winters (2010-11 & 2011-12) to determine what effect climate had on deer movements and vehicle collision rates. I observed that as snow depth decreased, the distance that deer occurred from roads increased. As a result road crossing rates declined, as did the number of vehicle collisions. This suggests a causal mechanism by which winter conditions influence vehicle collision rates. Currently there is a need for an efficient wildlife-vehicle collision data collection. I envisioned and, working with colleagues, helped develop a smartphone-based system for reporting wildlife-vehicle collision data. The WVC Reporter system consisted of a mobile web application for data collection, a database for centralized storage of data, and a desktop application for viewing data. The system greatly improved accuracy and increased efficiency of data collection efforts, which will likely result in improved mitigation and ultimately increased safety for motorists and deer