Wildlife-vehicle collision liability in Europe: A review of existing approaches and their implications.

Summary Vehicle collisions with wild animals are a serious problem that justifies the widespread application of mitigation measures such as road fencing and provision of crossing structures. Models that predict the best location for mitigation measures can improve wildlife survival and road safety. A database of 2067 records of animal–vehicle collisions was used to create two data sets at different spatial scales. The first comprised records of road sections of 1 km length with high rates of collision in combination with road sections with a low number of collisions. The second comprised records of collision and no collision incidence at points on the road system at a 0·1‐km scale. Logistic regression was used to investigate the relationship between incidence of collision and measured habitat features in each data set. The models were validated with a subset of the original data not used in developing the models. Road sections with high collision rates were associated with areas having high forest cover, low crop cover, low numbers of buildings and high habitat diversity. The fitted model achieved a significant predictive success during validation (χ2 = 4·82, 1 d.f., P= 0·028), with more than 70% correct classification of cases. Specific collision points typically had no guard‐rails or lateral embankments, were not near underpasses, crossroads or buildings, and featured hedges or woodland near the road. The fitted model also showed a significant predictive power in validation (64% correct classification, χ2 = 9·51, 1 d.f., P= 0·002) and accurately predicted 85·1% of collision points. Synthesis and applications. Predictive models of animal–vehicle collision locations should be used at both a landscape level and a local scale during the process of road design and implementation of mitigation measures. Modelling of collision risk could inform decisions on road alignment and on the exact location of crossing structures for mammals, to improve wildlife survival and road safety. This is the first study integrating both landscape and local scales of analysis for the variables associated with animal–vehicle collisions.

BackgroundAccording to WHO’s Global Status Report on Road Safety 2023, global road traffic crash (RTC) deaths decreased. However, they increased in most of the low-and-middle-income countries (LMICs). Research suggests systemic...

This article explores the challenges of setting up a coherent legal translation quality assessment system at a national – Romanian, and international – European level. It begins by providing an overview of the importance of accurate legal translation and its impact on legal procedures. It then delves into the current state of legal translation quality assessment in Romania and Europe and suggests the establishment of a legal translation control body, insisting on a number of responsibilities that it may have and challenges that it may face.

Human Wildlife Conflict (HWC) is one of the major challenges for wildlife conservation globally. This study assessed the status of HWC and the associated mitigation measures in two villages - Okhreni and Chilaune - of Sundarijal Shivapuri Buffer Zone User Committee at Shivapuri Nagarjun National Park (SNNP). Primary data were collected through household questionnaire surveys; key informant interviews and secondary data were collected from official records of SNNP, relevant journals, books, and reports. The survey was conducted in 115 HHs of both villages. 90 HHs were surveyed out of 300 HHs in Okhreni whereas 25 HHs were surveyed out of 50 HHs in Chilaune. Likert scale was used to identify the most problematic animal species involved in HWC. Wild boar (Sus scrofa), Himalayan Black Bear (Ursus thibetanus), crested porcupine (Hystrix brachyuran), rhesus monkey (Macaca mulatta) and barking deer (Muntiacus muntijak) are the major animal species involved in HWC. 95% respondents from Okhreni and 97% respondents from Chilaune experienced crop damage by wild animals, with those near the forest being more affected. Maize was the most targeted crop followed by millet and wheat. Only a single case of human injury has been registered in the last five years. Crop depredation by wild boar was most prevalent in the study area. People from both villages are not satisfied with the existing compensation measures. However, the lack of incidences of livestock depredation and human injuries and fatalities combined with peoples’ awareness about the significance of wildlife could be the probable reasons for positive attitudes towards wildlife and wildlife conservation in SNNP. People should be encouraged to cultivate less preferable and unpalatable crops and plants that are economically profitable as well. This could provide an alternative source of income and help reduce the incidences of HWC in the study area.

In 2014 more than 4 000 people aged 15–24 died on European roads. On this base an idea to conduct a European project focused on preventing young road users’ accidents...


 
 
 Every year approximately 1.3 million people are killed on roads around the world. Without new and effective actions, deaths in low to middle-income countries are forecasted to rise steeply, as the level of motorization is increasing. The availability of road safety data is fundamental to improving road safety outcomes, tracking progress, and achieving the road safety targets set by each country. With consistent and standardize collection and management, these data will provide beneficial and accurate insights for trends monitoring, future and time series prediction, and ultimately a reliable review of currently implemented programs. However, managing the data is a challenging aspect especially when it involves multiple agencies with different focuses and requirements and countless bureaucracy. By continued adoption of the "3-5-2" concept from football strategies, this paper will review the status-quo conditions of road crash data collection and management in the middle-income tier ASEAN countries. These shall be one of the core values for effective road safety management and improvement stipulated under the Decade of Action for Road Safety.
 
 

A future where autonomous vehicles drive on the European roads is promising in many ways. For example road safety, congestion and our environment could benefit from innovation and the large scale rollout of autonomous vehicles (AVs). However, regulation is often stated to form an obstruction for innovation and societal ... read more acceptance of AVs. That hypothesis plays a key role in this PhD-thesis, in which interrelations are investigated between the regulation of product- and traffic liability and personal data protection on the one hand, and innovation and acceptance of AVs on the other. Firstly, it is investigated which factors can be identified in regulatory frameworks that could influence innovation and acceptance of the results of innovation. Secondly, it is assessed to what extent those factors exist in the harmonised regulatory framework of product liability, traffic liability frameworks in The Netherlands, England and France, and the Unionwide regulation of personal data protection. Thirdly, recommendations are formulated for the EU legislator to improve these factors, in order to both stimulate innovation and the creation of optimal conditions for the societal acceptance of AVs. Three routes are sketched towards factor improvement. The ultimate goal should be to improve the factors within the respective legal frameworks. In order to reach that tenable solution, it is recommended that in parallel a “bottom-up” approach is followed, through the introduction of “bottom-up” binding industry codes of conduct for innovators, and the regulation of mandatory no-fault insurance that should lead to the compensation of damages of victims of AV-related accidents. show less

KNOW-IN Project Outcomes in Support of Training Road Transport Managers

Machine learning currently holds a vital position in predicting collision severity. Identifying factors associated with heightened risks of injury and fatalities aids in enhancing road safety measures and management. Presently, Thailand faces considerable challenges with respect to road traffic accidents. These challenges are particularly acute in industrial zones, where they contribute to a rise in injuries and fatalities. The mixture of heavy traffic, comprising both trucks and non-trucks, significantly amplifies the risk of accidents. This situation, hence, generates profound concerns for road safety in Thailand. Consequently, discerning the factors that influence the severity of injuries and fatalities becomes pivotal for formulating effective road safety policies and measures. This study is specifically aimed at predicting the factors contributing to the severity of accidents involving truck and non-truck collisions in industrial zones. It considers a variety of aspects, including roadway characteristics, underlying assumptions of cause, crash characteristics, and weather conditions. Due to the fact that accident data is big data with specific characteristics and complexity, with the employment of machine learning in tandem with the Multi-variate Adaptive Regression Splines technique, we can make precise predictions to identify the factors influencing the severity of collision outcomes. The analysis demonstrates that various factors augment the severity of accidents involving trucks. These include darting in front of a vehicle, head-on collisions, and pedestrian collisions. Conversely, for non-truck related collisions, the significant factors that heighten severity are tailgating, running signs/signals, angle collisions, head-on collisions, overtaking collisions, pedestrian collisions, obstruction collisions, and collisions during overcast conditions. These findings illuminate the significant factors influencing the severity of accidents involving trucks and non-trucks. Such insights provide invaluable information for developing targeted road safety measures and policies, thereby contributing to the mitigation of injuries and fatalities.

<p>Most commonly, geo-hydrological hazards (i.e., landslide, flood, sinkhole) occur in response to a single trigger like an intense rainfall event, a prolonged rainfall period, a rapid snowmelt event, an earthquake. Multiple damaging processes (phenomena) occurring in response to a single trigger can cause a cumulative socio-economic impact, which is often difficult to quantify and to attribute to each single damaging processes (landslide, or a group of landslides, or a single inundation). As a consequence, after a geo-hydrological disaster occurs, media, insurance companies and international institutions publish numerous assessments of the cost of the disaster based on different methodologies and approaches, often reaching different results. At European level, EC Directives related to natural hazards prove standards for the collection of data focusing their attention mainly on codifying the processes, their attributes and their spatial extent, leaving out the important issue of rigorously classifying the damaged elements and the loss data. Lack of standards contributes negatively to the paucity of damage information and cost data, fundamental for the successive ex-post analysis aimed at quantitatively risk evaluation. In Italy, despite the frequency of the significant socio-economic impacts due to geo-hydrological hazards, few attempts have been made to estimate the economic cost of geo-hydrological hazards. These loss estimations are mainly based on cost components of the public budget for post-event restorations and reimbursements, hampering the possibility to distinguish between the private and public sector losses. The loss estimates do not distinguish the costs (i) by type of processes (landslides, flash floods, floods and other damaging events) responsible for the damage, and (ii) by expenditure items (restoration actions or mitigation activities). LAND-deFeND, a recently developed database structure, represents an effort to manage all the issues that can arise when storing, organizing and analysing information on losses related to geo-hydrological hazards with different levels of accuracy and at different geographical scales, from the national to the local scale.</p>

BackgroundContemporary educational needs require searching for and using more effective and attractive solutions to reach young road users, an example of which is active education AE.ProcessTraditional learning methods are based...

Exposure and vulnerability are the main contributing factors of growing impact from climate-related disasters globally. Understanding the spatiotemporal dynamic patterns of vulnerability is important for designing effective disaster risk mitigation and adaptation measures. At national scale, most cross-country studies have suggested that economic vulnerability to disasters decreases as income increases, especially for developing countries. Research covering sub-national climate-related natural disasters is indispensable to obtaining a comprehensive understanding of the effect of regional economic growth on vulnerability reduction. Taking China as a case, this subnational scale study shows that economic development is correlated with the significant reduction in human fatalities but increase in direct economic losses (DELs) from climate-related disasters since 1949. The long-term trend in climate-related disaster vulnerability, reflected by mortality (1978–2015) and DELs (1990–2015) as a share of the total population and Gross Domestic Product, has seen significant decline among all economic regions in China. While notable differences remain among its West, Central and East economic regions, the temporal vulnerability change has been converging. The study further demonstrated that economic development level is correlated with human and economic vulnerability to climate-related disasters, and this vulnerability decreased with the increase of per-capita income. This study suggested that economic development can have nuanced effects on overall human and economic vulnerability to climate-related disasters. We argue that climate change science needs to acknowledge and examine the different pathways of vulnerability effects related to economic development.

Growth of vegetation in curbside cracks causes deterioration of asphalt and curbs, reducing road longevity and safety capabilities. Road managers spend a considerable amount of time and money on roadside vegetation management every year. The vegetation in curbside cracks in these study regions is managed approximately once a year by mowing and road sweeping using street-sweeper trucks. Nevertheless, ideal management practices of roadside vegetation have not yet been established partly due to insufficient knowledge of the ecological strategies of plants invading roadsides, especially curbside cracks. Although establishment of plants in the cracks might be restricted due to severe anthropogenic road disturbances, the cracks could be habitats for species with specific ecological traits. The objective of this study was to clarify the floristic and functional characteristics of roadside weeds, particularly species invading curbside cracks, to provide information for effective road management. The species composition of plants invading the cracks was surveyed along Route 3 (southern Japan) and Route 4 (eastern Japan) in different climatic zones, based on 108 floristic inventories. We compared species occurrence and composition to characterize the dominant ecomorphological traits of the species. In total, 163 species occurred in curbside cracks along both routes. Species composition of vegetation in curbside cracks was more variable between the routes than between land-use types. Of the 54 species, more than 5% occurred in all plots, and only three had differences in occurrence among land-use types. Ecomorphological trait composition patterns of the species were similar across land-use types. From these results, we found that regardless of differences in species composition among regions, climatic conditions, and surrounding land-use type, there were some dominant ecomorphological traits of roadside vegetation with plants in curbside cracks, such as ephemeral monophytes that are barochorous or anemochorous. By contrast, rhizomatous perennials, which cause greater deterioration of asphalt than ephemeral monophytes, were rare along the cracks. Although vegetation composition and structure generally depend on land-use types and disturbance regimes, linear landscape elements such as curbsides might be habitats for plants adapted to road disturbances. Roadside vegetation management, such as mowing and road sweeping once a year, seems sufficient to restrict establishment of rhizomatous perennials around Japan.

BackgroundEvidence-based road safety interventions require robust local data. In Bangladesh, road traffic injuries (RTI) are severely underreported in police records, and sub-national jurisdictions like the city of Chattogram never had...

In recent decades, increased attention has been focused on the impact of disabilities and medicinal drug use on road safety. The aim of our study was to investigate the association between prescription medicines and the risk of road traffic crashes, and estimate the attributable fraction. We extracted and matched data from three French nationwide databases: the national health care insurance database, police reports, and the national police database of injurious crashes. Drivers identified by their national health care number involved in an injurious crash in France, between July 2005 and May 2008, were included in the study. Medicines were grouped according to the four risk levels of the French classification system (from 0 [no risk] to 3 [high risk]). We included 72,685 drivers involved in injurious crashes. Users of level 2 (odds ratio [OR] = 1.31 [1.24-1.40]) and level 3 (OR = 1.25 [1.12-1.40]) prescription medicines were at higher risk of being responsible for a crash. The association remained after adjustment for the presence of a long-term chronic disease. The fraction of road traffic crashes attributable to levels 2 and 3 medications was 3.3% [2.7%-3.9%]. A within-person case-crossover analysis showed that drivers were more likely to be exposed to level 3 medications on the crash day than on a control day, 30 days earlier (OR = 1.15 [1.05-1.27]). The use of prescription medicines is associated with a substantial number of road traffic crashes in France. In light of the results, warning messages appear to be relevant for level 2 and 3 medications and questionable for level 1 medications. A follow-up study is needed to evaluate the impact of the warning labeling system on road traffic crash prevention.