Analyzing the impacts of built environment factors on vehicle-bicycle crashes in Dutch cities

Cycling safety policy and research have mostly focused on cycling infrastructure, cyclists' behavior, and safety equipment in the past decades. However, the role ofbuilt environment characteristics (BECs) in the safety of cyclists has not yet been fully examined. For the Netherlands, this is rather surprising given the significant modal share of bicycles in daily trips, the importance attributed to urban spatial planning, and it being one of the most planned countries in the world. Despite the considerable improvements that have ta1cen place in traffic safety over the decades, the ( actual) number of cyclist deaths between 2011 and 2020 increased by on average 2% per year; the cyclists bad a major portion oftraffic death (followed by passenger cars); also, almost onethird of traffic death happened in built-up a.reas (about 25% of fatalities occurred on 50km/h roads in urban areas) in this period. Considering the aim of construction of on average 75,000 new homes per year until 2025, as weil as promoting bicycle use in as a healthy and sustainable mode of transport in the N etherlands, underst.anding the relationships between the BECs and cycling safety is invaluable for improving the safety of cyclists

Safe cycling routes:Road safety indicators for cycling routes

To ensure that the cycling network remains safe after an increase in cycling, a well-developed, safe cycling network is needed. Studies investigating safe cycling often focus on design choices at road level, whereas route and network levels are also relevant. This study deals with cycling safety at route level. Firstly, it aims to define indicators to compare the safety levels of different routes between each origin-destination (OD) pair. Secondly, it aims to discuss how these indicators can be applied by road authorities in order to assess and improve the safety of cycling routes. Finally, it also aims to discuss the function of different types of infrastructure in the cycling network, as elements in cycling routes. The study focuses on cyclist routes within urban areas (built-up areas)

The future decision support system, deliverable 8.5 of the H2020 project SafetyCube

The European Road Safety Decision Support System (DSS) is a comprehensive “one stop shop” designed to inform evidence based policy by providing state of the art scientific knowledge on road safety. A short promotion video is available here: www.youtube.com/watch?v=Y-mVUde3knU. The DSS (www.roadsafety-dss.eu) has a user friendly web-based interface allowing users access to compressive information about a large range of road safety risk (problems) and measures (solutions), and links between the two. In addition, users are presented with information about serious road injuries, accident scenario fact sheets and an Economic Efficiency Evaluation (E3) tool. The E3 tool allows users to evaluate the cost effectiveness of road safety measures as well as providing a selection of worked examples. The European Road Safety DSS was developed by the European Commission supported Horizon 2020 project Safety CaUsation, Benefits and Efficiency (SafetyCube). The object of SafetyCube was to develop an innovative road safety Decision Support System (DSS) that will enable policy-makers and stakeholders to select and implement the most appropriate strategies, measures and cost-effective approaches to reduce casualties of all road user types and all severities. Detailed information about the development and DSS status at the end of the SafetyCube project are available in Yannis & Papadimitriou (2018). An overview of the DSS scientific content and a summary of the methodology used to develop the DSS can be found in the SafetyCube Final Project Report (Thomas & Talbot, 2018). The present Deliverable (8.5) gives a brief overview of the current state of the art DSS, describes the future enhanced version of the DSS and provides information for potential funder(s). Opportunity is available for new funders to support the European road safety DSS as it is developed and enhanced for future users. Through supporting the DSS, the future funder(s) will be contributing the Global UN Sustainable Development Goals on road safety by taking a leading position to actively promote effective solutions to road safety’s most pressing challenges. Aspirations for the future DSS will make the scientific content more accessible through translation of content in to local languages and filtering information into the manner most appropriate for low and middle income countries. The content will be expanded to include more topics and more detail about existing topics. Expansion of knowledge will include knowledge about implementing measures and a focus on the interdependences of road safety measures considering the impacts of implementing measures in combination. In addition to the future visions for content there are also aspirations for the future web based interface. A key enhancement will be to give users the ability to customise the display and select the information they would like to see for each individual coded study. The best case future for DSS operation is that of extended growth supported by considerable external funding. The exact structure, legal entity and governance of the future enhanced DSS will be decided in collaboration between the SafetyCube consortia and the future funder(s). In this cooperative way funding partners will have the chance to influence the development process in the manner most appropriate to meet their stakeholder needs. It is envisaged that the future DSS will be financed by several Organisations, therefore, the governance, time schedule and strategy for extended growth will be mutually decided. Within the SafetyCube project activities have been undertaken to advertise the DSS and provide information for potential funders. The European road safety DSS is the first integrated road safety support system developed in Europe. It aims to be the “go to tool”for road safety knowledge. The next funder(s) of the DSS have the exciting opportunity to take the DSS to the next level in facilitating the future of evidence based road safety policy making, ensuring safe roads for all

Burden of injury of serious road injuries in six EU countries

BACKGROUND: Information about the burden of (non-fatal) road traffic injury is very useful to further improve road safety policy. Previous studies calculated the burden of injury in individual countries. This paper estimates and compares the burden of non-fatal serious road traffic injuries in six EU countries/regions: Austria, Belgium, England, The Netherlands, the Rhône region in France and Spain. METHODS: It is a cross-sectional study based on hospital discharge databases. POPULATION: of study are patients hospitalized with MAIS3+ due to road traffic injuries. The burden of injury (expressed in years lived with disability (YLD)) is calculated applying a method that is developed within the INTEGRIS study. The method assigns estimated disability information to the casualties using the EUROCOST injury classification. RESULTS: The average burden per MAIS3+ casualty varies between 2.4 YLD and 3.2 YLD per casualty. About 90% of the total burden of injury of MAIS3+ casualties is due to lifelong consequences that are experienced by 19% to 33% of the MAIS3+ casualties. Head injuries, spinal cord injuries and injuries to the lower extremities are responsible for more than 90% of the total burden of MAIS3+ road traffic injuries. Results per transport mode differ between the countries. Differences between countries are mainly due to differences in age distribution and in the distribution over EUROCOST injury groups of the casualties. CONCLUSION: The analyses presented in this paper can support further improvement of road safety policy. Countermeasures could for example be focused at reducing skull and brain injuries, spinal cord injuries and injuries to the lower extremities, as these injuries are responsible for more than 90% of the total burden of injury of MAIS3+ casualties

Reporting road traffic serious injuries in Europe. Guidelines from the SafetyCube project (H2020)

Reporting road traffic serious injuries in Europe. Guidelines from the SafetyCube project (H2020

A systematic cost-benefit analysis of 29 road safety measures

Economic evaluations of road safety measures are only rarely published in the scholarly literature. We collected and (re-)analyzed evidence in order to conduct cost-benefit analyses (CBAs) for 29 road safety measures. The information on crash costs was based on data from a survey in European countries. We applied a systematic procedure including corrections for inflation and Purchasing Power Parity in order to express all the monetary information in the same units (EUR, 2015). Cost-benefit analyses were done for measures with favorable estimated effects on road safety and for which relevant information on costs could be found. Results were assessed in terms of benefit-to-cost ratios and net present value. In order to account for some uncertainties, we carried out sensitivity analyses based on varying assumptions for costs of measures and measure effectiveness. Moreover we defined some combinations used as best case and worst case scenarios. In the best estimate scenario, 25 measures turn out to be cost-effective. 4 measures (road lighting, automatic barriers installation, area wide traffic calming and mandatory eyesight tests) are not cost-effective according to this scenario. In total, 14 measures remain cost-effective throughout all scenarios, whereas 10 other measures switch from cost-effective in the best case scenario to not cost-effective in the worst case scenario. For three measures insufficient information is available to calculate all scenarios. Two measures (automatic barriers installation and area wide traffic calming) even in the best case do not become cost-effective. Inherent uncertainties tend to be present in the underlying data on costs of measures, effects and target groups. Results of CBAs are not necessarily generally valid or directly transferable to other settings.acceptedVersio

Network-wide safety impacts of dedicated lanes for connected and Autonomous Vehicles

Cooperative, Connected and Automated Mobility (CCAM) enabled by Connected and Autonomous Vehicles (CAVs) has potential to change future transport systems. The findings from previous studies suggest that these technologies will improve traffic flow, reduce travel time and delays. Furthermore, these CAVs will be safer compared to existing vehicles. As these vehicles may have the ability to travel at a higher speed and with shorter headways, it has been argued that infrastructure-based measures are required to optimise traffic flow and road user comfort. One of these measures is the use of a dedicated lane for CAVs on urban highways and arterials and constitutes the focus of this research. As the potential impact on safety is unclear, the present study aims to evaluate the safety impacts of dedicated lanes for CAVs. A calibrated and validated microsimulation model developed in AIMSUN was used to simulate and produce safety results. These results were analysed with the help of the Surrogate Safety Assessment Model (SSAM). The model includes human-driven vehicles (HDVs), 1st generation and 2nd generation autonomous vehicles (AVs) with different sets of parameters leading to different movement behaviour. The model uses a variety of cases in which a dedicated lane is provided at different type of lanes (inner and outer) of highways to understand the safety effects. The model also tries to understand the minimum required market penetration rate (MPR) of CAVs for a better movement of traffic on dedicated lanes. It was observed in the models that although at low penetration rates of CAVs (around 20%) dedicated lanes might not be advantageous, a reduction of 53% to 58% in traffic conflicts is achieved with the introduction of dedicated lanes in high CAV MPRs. In addition, traffic crashes estimated from traffic conflicts are reduced up to 48% with the CAVs. The simulation results revealed that with dedicated lane, the combination of 40-40-20 (i.e., 40% human-driven – 40% 1st generation AVs– 20% 2nd generation AVs) could be the optimum MPR for CAVs to achieve the best safety benefits. The findings in this study provide useful insight into the safety impacts of dedicated lanes for CAVs and could be used to develop a policy support tool for local authorities and practitioners