Identifying Changes in Bicycle Accident Trends Using GIS and Time Series Information in the City of Zürich

In order to be effective, road safety officers must have a complete overview of the accidents in their area of responsibility, including information pertaining to the location and severity of the accidents, and how the number of accidents are developing over time. Ideally, this information is stored in a Geographic Information System (GIS) enabled database, which helps to facilitate data processing and analysis, which enables improved understanding of the reasons for the accidents and the proposals of how to improve road safety. This paper presents a case study based on accident reports from the Zurich City Police. Using a joint GIS and time series analysis based on negative binomial regression, the data is analyzed to identify trends in accident development for several accident subgroups (e.g., bicycle accidents, senior citizen accidents, e-bike accidents) and specific locations. The subgroup of bicycle accidents will be discussed in more detail. The time series analysis is corrected for exposure (e.g., the increasing number of e-bikes) and forecasts the number of accidents which are likely to occur in the future. Significantly higher numbers of accidents than those expected serve as an early warning that further investigation, leading to possible interventions, is required. The case study shows that with this information, it is possible to identify both geographical areas and accident subgroups that have deviating patterns in accident numbers, and should be further investigated. For bicycle accidents, 4 out of 12 districts exceed the average accident trend by over 95% and 3 districts have an accident number that is over 10% higher than that district's forecast, with the highest being 33% above the already increasing accident trend. Other accident subgroups are presented in summary form. The results of the analysis allow consistent and automated analysis across all potential areas for improving road safety, helping to focus the efforts of road safety managers on those areas where their efforts are most effective

Wider view over bicycle accidents: Complementing and extending bicycle accident statistics in urban areas using surveys

City traffic planners are striving to adapt their infrastructure to not only increase the number of cyclists but also to ensure that city cycling is both enjoyable and safe. In Switzerland and in many other countries, it is suspected that only one of ten bicycle accidents is reported to the police [ 1-5]. Only knowing about 10% of the accidents, on top of the fact that there are luckily not many accidents from a statistical perspective, casts doubt about where efforts should be made to improve cycling infrastructure, and how effective the actions taken actually are. To deal with this lack of data, this paper proposes to use surveys of cyclists besides police records to obtain a more complete picture of the number and location of cycling accidents, including the ones not reported to police, and the locations that cyclists perceive as dangerous. The combination of survey and police reported data gives a considerably different and more complete impression of where there is potential to improve cycling infrastructure, when compared to that obtained using only police reported accidents. This work expounds how the survey responses about hazard perception and unreported accidents help provide a more complete overview of the accident potential of the existing cycling network and how they form a base of immensely useful inputs for planning improvements. [From: Introduction

Wider view over bicycle crashes: Complementing and extending bicycle crash statistics in urban areas using surveys

ntroduction: In pursuit of sustainability goals, many cities are introducing measures to increase the usage of bicycles as a means of transportation. City planners aim to ensure that this increase does not lead to an increase in crashes, but must make corresponding infrastructure decisions with limited information. Sufficient data to perform a statistical analysis of location-specific crash frequencies is rarely available. For example, only approximately 10% of all bicycle crashes are reported to the police (Shinar et al., 2018). Therefore, urban planners often rely on expert opinion, which may lead to suboptimal prioritization and realization of infrastructure improvements. Method: This paper demonstrates how surveys on bicycle crashes can be used to aid urban planners in making infrastructure decisions. In addition to confirming the location and characteristics of reported crashes, surveys can uncover characteristics of crashes that are not reported to the police, situations in which a crash almost occurred, and locations perceived by cyclists to be dangerous. Surveys also allow urban planners to investigate non-infrastructure related causes of crashes, such as the frequency with which individual cyclists use other modes of transportation. Practical Applications: The usefulness of surveys in the determination of urban cycling safety is demonstrated in this paper through analysis of survey results from the city of Zurich in 2018

A real option approach to determine optimal intervention windows for multi-national rail corridors

In this paper, a real option approach to determine the optimal time to execute interventions on rail infrastructure, when it is not known for certain which intervention is to be executed, is presented (i.e. the optimal intervention window). Such an approach is useful in the management of rail infrastructure that belongs to a multi-national rail corridor where multiple railway organizations, ideally, should coordinate their maintenance interventions, years in advance, to minimize service disruptions. The approach is based on an adaptation of the Black and Scholes differential equation model used to value European call options in financial engineering. It is demonstrated by determining the optimal intervention window for infrastructure in a fictive rail corridor

The effect of restoration on the resilience of transportation infrastructure

Coping with the resilience of infrastructure systems is important in order to be prepared for disruptive events such as natural hazards. It is essential to understand how and in what order damaged infrastructure objects should be restored so that they can provide adequate service again. Infrastructure managers making such decisions must also take into account other constraints such as available funds, personnel, available resources, and any external constraints, e.g. which objects on which roads should have priority. In this work, a mathematical optimization model was used to determine such a restoration program, by minimizing the direct and indirect costs of the event, considering constraints such as budget, resource and traffic flow. With this approach, a restoration programme for a real road network in Switzerland after the occurrence of an extreme flood event is investigated

The effect of management decision processes on the management of bridges

It is necessary to execute interventions on bridges to ensure that they continue to provide an adequate level of service. It is necessary to inspect them to ensure that these interventions are timed appropriately. As there are negative impacts associated with both inspections and interventions, e.g. the impact on the owner due to the hours of labor and amounts of materials required to perform an inspection and execute an intervention, it is desirable to determine inspection and intervention strategies that minimize these negative impacts (i.e. the optimal management strategy). An important, however often overlooked, factor in determining optimal management strategies, is how management processes affect the determination of the optimal management strategy. In this article it is shown that it is not always possible to determine an optimal management strategy without explicitly taking into consideration management processes, how variations in management processes can be evaluated and that the significance of these variations is dependent on the values of the incurred impacts. First published online: 21 Oct 201

Automated Construction Progress and Quality Monitoring for Commercial Buildings with Unmanned Aerial Systems: An Application Study from Switzerland

Unmanned Aerial Systems (UASs), which have become a key tool in remote sensing in recent years, have also rapidly entered the practice of Architecture, Engineering, Construction, and Operations (AECO). This paper presents an application study of a methodology for monitoring construction progress and quality using real-time data from a commercial building during the execution phase and the results of an analysis of the costs and benefits of monitoring construction progress and quality with and without a UAS. The methodology used consists of three parts: (1) automated data collection at the construction site, (2) data processing, in which the collected data are processed to generate the outputs necessary for the data analysis, and (3) data analysis to monitor construction progress and quality. The method is based on the detection of structural elements, combined with four principles: the sectional approach, the calculation of the concrete volume, the height-distance measurement, and the detection of defects by visual comparisons. The cost-benefit analysis considers three cases: monitoring of progress (1) by the construction company using the UAS, (2) by external contractors using the UAS, and (3) by the construction company without using the UAS. We show that the in-house operation of the UAS is associated with medium costs. However, a return on investment can be achieved quickly if the strategy for the operation of the UAS is clearly defined. In summary, the use of a UAS for the automated monitoring of the construction progress and quality of commercial buildings is practicable, which can quickly lead to a return on investment. We also show that there is great potential for further improvements.</p