Orientador: Jorge Luiz Alves Trabanco / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo / Made available in DSpace on 2018-08-14T15:09:12Z (GMT). No. of bitstreams: 1 Silva_AndersonPereirada_M.pdf: 4388966 bytes, checksum: 8a2adb482cff8945f6f6f3728bf42042 (MD5) Previous issue date: 2009 / Resumo: Administradores públicos e privados necessitam de informações que os auxiliem no gerenciamento e tomada de decisões quanto à prevenção de acidentes. Acidentes de trabalho e de trânsito são grandes problemas de serem administrados, pois os métodos existentes muitas vezes não conseguem trazer resultados com rapidez para auxiliar na tomada de decisão. Este trabalho propõe uma metodologia baseada em geotecnologias e softwares livres para o desenvolvimento de um Sistema de Informação Geográfica (SIG) para gestão e prevenção de acidentes de trabalho e trânsito no campus da Universidade Estadual de Campinas - UNICAMP. As parcerias com Comissão Interna de Prevenção de Acidentes (CIPA), Prefeitura e Setor de Vigilância do campus, e Laboratório de Topografia e Geodésia da Faculdade de Engenharia Civil, Arquitetura e Urbanismo proporcionaram: a atualização da base cartográfica do campus utilizando de equipamentos GNSS (Global Navigation Satellite System); obtenção de plantas baixas; contratação de estagiários; e desenvolvimento de sistemas para georeferenciamento dos riscos em ambiente de trabalho e acidentes de trânsito para gestão e visualização na Internet através de um SIG-WEB. / Abstract: Public and private administrators need information that will help them in managing and making decisions regarding the prevention of accidents. Occupational accidents and traffic are major problems to be administered, because the existing methods often fail to bring results quickly to assist in decision making. This paper proposes a methodology based on geotechnology and free software for the development of a Geographic Information System (GIS) for management and prevention of occupational accidents and traffic on the campuses of Universidade Estadual de Campinas - UNICAMP. Partnerships with the Comissão Interna de Prevenção de Acidentes (CIPA), the Hall and Sector Monitoring of campuses, and Laboratory of Topography and Geodesy of Faculty of Civil Engineering, Architecture and Urbanism provided: the update of the cartographic basemap of the campuses using GNSS equipment (Global Navigation Satellite System), obtaining floor plans, hiring interns, and systems development for georeferencing of risks in the workplace and traffic accidents to management and viewing the Internet by WEB-GIS. / Mestrado / Transportes / Mestre em Engenharia Civil

The topic of this Diploma's thesis is Road safety inspection in the Zlín region. To start off, I was given 14 dangerous locations in the region of Zlín by the Road Services of Kroměříž; 7 of them at crossroads and 7 outside of crossroads. Then I analysed accident risks and compared the locations among each other according to safety features. Based on the outcome of my analysis, then I chose 2 locations at crossroads and 2 outside of crossroads which I personally visited and conducted analysis on how safe they are. I uncovered potential risks which could lead to traffic accidents and suggested solutions that eliminate or minimise that risk.

The thesis focuses on a road safety inspection in South Moravian Region. In the first part, 15 locations with different characteristics were chosen, which were subjected to in-depth accident analysis and then compared by security indicators. On the basis of the results of this analysis, 5 locations were selected, namely the junction on a road II/430 and four sections on the roads II/373, II/384 and II/394. The selected sites were the objects for a road safety inspection, consisting of a personal visit of sections and the subsequent preparation of the potential risks influencing the origins of accidents. For each risk are proposed corrective measures that remove or eliminate the problems on selected section.

Aktuell wird die Erfassung von Biofunktions-Indikatoren durch Fitness-Tracker, Smart Watches und ähnliche Devices massenwirksam. Bewegungen und Körperfunktionen werden detektiert, aufgezeichnet und aufbereitet. Ziel der Nutzer ist es, mit den gewonnenen Erkenntnissen den eigenen Körper und Lebenswandel zu optimieren. Aktuelle Geschäftsmodelle der in diesem Geschäftsfeld tätigen Akteure liegen überwiegend darin, aus dem zur Verfügung stehenden Datenmaterial Handlungsvorschläge abzuleiten, welche die Kunden in ihrem Optimierungsstreben unterstützen. Anwendungsfelder könnten sich aber auch im Verkehrssektor eröffnen. So erscheint es möglich und sinnvoll, die neu verfügbaren Indikatoren zu nutzen, um die emotionale Verfassung von Beförderten und die Aufmerksamkeit von Fahrern zu überprüfen sowie Möglichkeiten zu schaffen, Verkehrsinfrastrukturen, Verkehrssituationen als auch Umfeldsituationen zu identifizieren, welche Fahrer sehr stark fordern und somit aus Sicht der Verkehrssicherheit kritisch zu werten sind. Um Potentiale, Aufwände und Grenzen abzuschätzen zu können, wurde eine Vorstudie im Kontext des Motorisierten Individualverkehrs durchgeführt. In den Fokus gesetzt wurde dabei die Identifikation von Stresssituationen, hervorgerufen durch die Bewältigung infrastruktureller Herausforderungen aus auch durch die Interaktionen mit anderen motorisierten Verkehrsteilnehmern. Mit einem Equipment aus Biofunktions-Sensorik, Positions-Erfassungseinheit und einem Aufzeichnungsgerät, wurden Daten im Sinn von Extended Floating Car aufgezeichnet. Einflüsse von Infrastrukturen auf Stressindikatoren zeichneten sich bei der Auswertung deutlich ab. Gleiches gilt für Verkehrssituationen, welche eine erhöhte Aufmerksamkeit abverlangten. Um die Thematik umfassend bearbeiten zu können, wurden die zu klärenden Kernfragestellungen ermittelt und strukturiert.

Road freight transportation is subject to several legal requirements having direct impact on the practical applicability of routes and schedules. The vast majority of vehicle routing literature, so far, has largely focused on physical constraints such as capacity limits, or customer requirements such as time windows for pickups and deliveries. This paper studies legal requirements for long-distance haulage in the European Union, identifies some major gaps in the current state-of-the-art in vehicle routing, presents approaches for overcoming this gap, and analyzes the impact of the legal requirements studied.

Trafikverket planerar nya förbifarter längs med E22:an i Söderköping och Karlskrona då säkerheten och kapaciteten på de befintliga vägarna inte är tillräcklig. Syftet med uppsatsen är att undersöka hur Trafikverket tar hänsyn till samhällsnytta och  naturmiljö vid byggandet av nya förbifarter, med exempel från planerade förbifartsprojekt i Karlskrona kommun och Söderköpings kommun. I genomförandet av resultatet gjordes en dokumentstudie samt tre intervjuer. Det som går att se utifrån resultatet och diskussionen är att risken för köer minskar till följd av en ökad kapacitet på vägarna. Påverkan som dessa förbifarter har på miljön uppstår bland annat i och med att förbifarterna ska dras genom skog och jordbruksmark. Resultatet visar på att Trafikverket är medvetna om påverkan på naturmiljön och tillämpar vissa verktyg för att minska negativ påverkan på miljön. Vid större förändringar, som att välja förbifartens placering, verkar dock fokus ligga på samhällsnytta och ekonomisk lönsamhet. / The Swedish Transport Administration (Trafikverket) is planning new bypass roads in Söderköping and Karlskrona, because of congestion and safety issues. The purpose of this thesis is to investigate how Trafikverket takes into account societal benefits and the natural environment when building new bypass roads. For the result analysis of relevant documents and three interviews have been made. The result shows building roads with higher capacity leads to shorter travel times and better safety. Less traffic in the town will lead to better air quality and lower noise in the town. The planned placement of the bypass is going through woods and farmlands. Results also show that Trafikverket is aware of the negative effects the bypass will have on the environment. Larger changes like choosing a placement for the road, more focus is on the societal and economic benefits that the bypass brings.

With the rapid improvement of the Advanced Driver Assistant System (ADAS), autonomous driving has become one of the most common hot topics in recent years. While driving, many technologies related to autonomous driving choose to use the sensors installed on the vehicle to collect the information of road status and the environment outside. This aims to warn the driver to perceive the potential danger in the fastest time, which has become the focus of autonomous driving in recent years. Although autonomous driving brings plenty of conveniences to people, the safety of it is still facing difficulties. During driving, even the experienced driver can not guarantee focus on the status of the road all the time. Thus, lane departure warning system (LDWS) becomes developed. The purpose of LDWS is to determine whether the vehicle is in the safe driving area. If the vehicle is out of this area, LDWS will detect it and alert the driver by the sensors, such as sound and vibration, in order to make the driver back to the safe driving area. This thesis proposes a novel lightweight LDWS model LEHA, which divides the entire LDWS into three stages: image preprocessing, lane detection, and lane departure recognition. Different from the deep learning methods of LDWS, our LDWS model LEHA can achieve high accuracy and efficiency by relying only on simple hardware. The image preprocessing stage aims to process the original road image to remove the noise which is irrelevant to the detection result. In this stage, we apply a novel algorithm of grayscale preprocessing to convert the road image to a grayscale image, which removes the color of it. Then, we design a binarization method to greatly extract the lane lines from the background. A newly-designed image smoothing is added to this stage to reduce most of the noise, which improves the accuracy of the following lane detection stage. After obtaining the processed image, the lane detection stage is applied to detect and mark the lane lines. We use region of interest (ROI) to remove the irrelevant parts of the road image to reduce the detection time. After that, we introduce the Canny edge detection method, which aims to extract the edges of the lane lines. The last step of LDWS in the lane detection stage is a novel Hough transform method, the purpose of it is to detect the position of the lane and mark it. Finally, the lane departure recognition stage is used to calculate the deviation distance between the vehicle and the centerline of the lane to determine whether the warning needs to turn on. In the last part of this paper, we present the experiment results which show the comparison results of different lane conditions. We do the statistic of the proposed LDWS accuracy in terms of detection and departure. The detection rate of our proposed LDWS is 98.2% and the departure rate of it is 99.1%. The average processing time of our proposed LDWS is 20.01 x 10⁻³s per image.

Intersections represents one of the most common accident sites in traffic today. The biggest cause of accidents is obstructed view and subpar communication between vehicles. Since autonomous vehicles rely on sensors that require a direct view intersections are some of the most complex situations. Where the potential for inter vehicular communication exists between modern vehicles, it is absent in the older generation. An overseeing intersection system can fill this function during the transition period to fully autonomous traffic. This project aimed to implement an intersection system to assist autonomous vehicles through a crossroad. The assist system’s objective was to collect and transmit data from cars close to the junction to the autonomous vehicles nearby. The concept was tested in simulations by having models traverse a crossroad to evaluate how it utilised the external information. No persistent conclusion could be made due to insufficient simulation environment and vehicle model control.

Physical inactivity increases the risk of multiple diseases with extensive personal and societal effects [1]. For instance, the annual economic cost of physical inactivity is estimated to be more than 80 billion euros in the European Union (EU) [2]. One measure to increase physical activity is the promotion of active transport modes, such as cycling. Finland is aiming to increase the mode share of active transport modes to 35-38% by 2030 [3]. In tbe most recent national travel survey 8% of daily trips were made by bicycle and 22% of daily trips involved walking [ 4]. A shift from cars to more sustainable transport modes is desirable, however more work is needed to promote cycling safety, with cyclists over-represented in fatal (11%) and serious injuries (32%) when compared to mode share [5]. Amongst cyclist crashes in Finland, single-bicycle crashes (SBCs), where other road users are not collided with, represent more than half of non-fatal injuries [6-7] and 46% of fatal injuries [8--9]. This proportion of non-fatal injuries is similar to findings from other jurisdictions [6]. However, the rate of fatal injuries in SBCs is substantially higher in Finland compared to the average rate in Europe [10], highlighting the importance of understanding SBCs in a Finnish context. Analyses of SBCs are usually more challenging than crashes between bicycles and motor vehicles because SBCs are typically underreported in police-reported crash data [11]. However, in Finland, road crash investigation teams investigate almost all fatal road crashes, including SBCs. This captures high-quality information on SBCs including their contributory and background risk factors, as well as safety recommendations. Identifying the contributory factors that enable the occurrence of crashes and implementing actions to prevent these crashes can help promote cycling safety [ 12]. Such analyses and actions are particularly needed in Finland, where there are targets to increase the mode share of cycling. Given the robust data available through the in-depth investigations undertaken in Finland, this study aims to increase knowledge on SBCs and their safety recommendations by analysing data on fatal cycling crashes in Finland. The study compares the key characteristics, risk factors and safety recommendations regarding SBCs and other cyclist crashes. Although the data for this study is sourced from Finland, the findings are useful in other countries with similar bicycle infrastructure and weather conditions. [From: Introduction]

With the beginning of the COVID-19 outbreak and the restrictions put in place to prevent an uncontrolled spread of the virus, the circumstances for daily activities changed. A remarkable shift in the modal split distribution was observed. Cycling was seen as a reliable and resilient option in pandemic times as it allowed social distancing and poses a low risk of contagion. There are detailed studies on the effect of the pandemic on cycling traffic all over the globe which used different data sources, like app data. counters or surveys [1] [2]. Apart from the citizens' behavioral responses to the corona pandemic, the municipalities also put up interventions that were meant to support a shift to cycling-based movements in cities. The question to discuss is what changes will be permanent and which changed circumstances, e.g. increased subjective safety, lead to a long-term change of mobility patterns. The changes in mobility during the COVID-19 pandemic bad different impacts on road traffic collisions and road deaths in different countries. While there was a reduction of both indicators in 32 out of 36 countries in April 2020 compared to April 2019, there was an increase in the other four countries [3]. Others also found a reduction of traffic fatalities in 23 out of 24 countries in 2020 compared to a baseline of the previous years (2017-2019), the only exception being Switzerland [4]. The subjective well-being has also changed differently for the different transport modes throughout the pandemic. For example, in April 2020, 9% of respondents said they would feel more comfortable or much more comfortable if they used or would use a bicycle compared to pre-pandemic times; in summer and autumn 2020, this figure was 11 %, in spring 2021, it was 13%. In autumn 2021, 15% of respondents said they would feel more comfortable or much more comfortable if they used or would use a bicycle than before the spread of the coronavirus [ 5]. [From: Introduction]