Regional-based mitigation to reduce wildlife-vehicle collisions

A spatiotemporal risk prediction of wildlife-vehicle collisions using machine learning for dynamic warnings

INTRODUCTION

The technology in the automotive industry is becoming increasingly safer in the age of automated driving, but the number of accidents is still high, especially in wildlife-vehicle collisions (WVCs). To better avoid these accidents, patterns involved in these accidents must be detected.

METHOD

This paper presents a spatiotemporal risk prediction of WVCs, including various road and environmental characteristics. A process of data preparation using GIS automated by Python scripts was developed to enable a spatiotemporal link of diverse features for the subsequent predictive data analysis. Different machine learning (ML) approaches were applied- random forest (RF), feedforward neural networks (FNN), and support vector machine classifier (SVM) - including automated ML to predict the risk of WVCs. Therefore, a dataset of approximately 731,000 accidents reported to the police in Bavaria over a period of 10 years (2010-2019) was used. In addition, non-accidents were randomly generated in Python over time and space for the supervised ML processes. As the actual risk probability for WVCs and non-WVCs is not entirely known, the impact of different training ratios between accidents and non-accidents was tested on the risk prediction quality (RPQ) (25%, 50%, 75%, 90% WVCs) of the double-weighted sensitivity and single-weighted specificity rate.

RESULTS

The test yielded high mean values of RPQ as an indicator for a suitable WVC prediction. Both RF (86.6%) and FNN (86.7%) were identified as suitable choices for WVC risk prediction in terms of RPQ. The SVM yielded a lower prediction quality, even though acceptable results could be achieved within a shorter runtime.

PRACTICAL APPLICATIONS

Spatial transferability was verified since the algorithm was trained on the dataset of Bavaria (excluding Upper Bavaria) and successfully tested in Upper Bavaria. WVC forecasts were also proven through training with datasets from 2010-2017 and in prediction for 2018 and 2019.

How Engineers and Roadside Vegetation Managers Maintain Roadside Vegetation in Iowa, USA

Recently the value of roadside vegetation as habitat for pollinators has gained increased attention, particularly in areas dominated by agriculture where there is little native vegetation available. However, many factors, including safety, cost, public perception, erosion control, and weedy plants must be considered when managing roadside vegetation. Although their decisions influence thousands of hectares of public rights-of-way, how engineers and roadside managers maintain roadside vegetation has been the subject of little research. In this study, we surveyed county engineers and roadside managers who manage vegetation along secondary roads in Iowa, USA to assess how they maintain roadside vegetation. Some counties employ roadside managers, who often have an environmental sciences background, to implement the on-the-ground management of roadside vegetation, while some counties use other staff. Compared to engineers, roadside managers more strongly agreed that using the ecological principles of integrated roadside vegetation management (IRVM) provided environmental benefits. Engineers in counties with a roadside manager more strongly agreed that IRVM practices reduce the spread of invasive species and provide attractive roadsides. Both engineers and roadside managers mentioned challenges to managing roadside vegetation, including interference with some native plantings by adjacent landowners, and ranked safety and soil erosion concerns as the highest priorities when making decisions. Four in ten roadside managers said their counties had protected native plant community remnants on secondary roadsides. Our findings can inform conservation outreach efforts to those responsible for managing roadside vegetation, and emphasize the importance of addressing safety and soil erosion concerns in roadside research and communications.

Spatiotemporal Analysis of Road Crashes with Animals in Poland

This article describes the issue of the influences of the time factor and wildlife populations on road animal–vehicle crashes. The article presents problems associated with animal–vehicle crashes in Poland. They are the subject of many court disputes. For the purposes of the study, data on animal–vehicle road crashes were obtained from the SEWiK database, as well as data on the numbers of animals in hunting districts from 2016–2020. The relationship between the number of road crashes and time was analysed, and the relationships between the numbers of road crashes and the animal populations, as well as the locations, types, and categories of the hunting districts, were analysed as well. The factors related to changes in the wildlife populations, road crashes in previous years, and the lengths of the road networks were also analysed. The research shows no relationship between the abundance of a particular species and the number of road crashes. Instead, there is a correlation between the number of crashes in previous years and the road network length.

Local Decision-makers' Perspectives on Roadside Revegetation and Management in Iowa, USA

Environmental practitioners must understand those they collaborate with to implement programs that are both socially and ecologically effective. Practitioners who understand decision-makers' perspectives are better able to collaborate to lower political, financial, and cultural obstacles. In this study, we surveyed decision-makers involved with a voluntary environmental program in Iowa, USA. Iowa counties can choose to manage their roadside vegetation using an ecological approach, called integrated roadside vegetation management. Key decision-makers who decide whether a county has a roadside program are the county board of supervisors and the county conservation board. We used a mixed-mode design to survey the conservation board directors and chairs of the board of supervisors in each county. Our main goals were to understand the decision-makers' perceived benefits and barriers to having a roadside program in their counties, as well as the key factors influencing their decisions about roadside vegetation management. Safety, maintenance cost savings, and erosion control were the main factors that influenced decision-making, while pollinators and other wildlife received the least consideration. However, decision-makers in counties with a roadside vegetation manager were more influenced by pollinators and other wildlife compared to their counterparts in counties without a roadside vegetation manager. The main barriers to having a program include a lack of resources or other concerns being a higher priority. Emphasizing safety, cost savings, and erosion control benefits of roadside programs, and identifying ways to lower startup costs may increase buy-in with county decision-makers.