A Novel Collision Avoidance System for a Bicycle

This project focuses on development of a sensing and estimation system for a bicycle to accurately detect and track vehicles for two types of car-bicycle collisions. The two types of collisions considered are collisions from rear vehicles and collisions from right-turning vehicles at a traffic intersection. The collision detection system on a bicycle is required to be inexpensive, small and lightweight. Sensors that meet these constraints are utilized.To monitor side vehicles and detect danger from a right-turning car, a custom sonar sensor is developed. It consists of one ultrasonic transmitter and two receivers from which both the lateral distance and the orientation of the car can be obtained. A Kalman Filter-based vehicle tracking system that utilizes this custom sonar sensor is developed and implemented. Experimental results show that it can reliably differentiate between straight driving and turning cars. A warning can be provided in time to prevent a collision. For tracking rear vehicles, an inexpensive single-beam laser sensor is mounted on a rotationally controlled platform. The rotational orientation of the laser sensor needs to be actively controlled in real-time in order to continue to focus on a rear vehicle, as the vehicle’s lateral and longitudinal distances change. This tracking problem requires controlling the real-time angular position of the laser sensor without knowing the future trajectory of the vehicle. The challenge is addressed using a novel receding horizon framework for active control and an interacting multiple model framework for estimation. The features and benefits of this active sensing system are illustrated first using simulation results. Then, extensive experimental results are presented using an instrumented bicycle to show the performance of the system in detecting and tracking rear vehicles during both straight and turning maneuvers

ASSESSING THE IMPACT OF BICYCLE TREATMENTS ON BICYCLE SAFETY: A MULTI-METHODS APPROACH

Compared to other modes, bicyclists are disproportionally affected by crashes considering their low mode share. There is evidence that crashes between bicyclists and motorized vehicle take place at road segments and signalized intersections where bicycle treatments (e.g., bike lanes) are present, urging for in-dept analysis of the safety impact of the various bicycle treatment types. Additionally, it is important to identify sensor types that have the potential to advance field data collection and traffic monitoring in multi-modal road environments. In this dissertation, three approaches, namely crash analysis, traffic conflict analysis, and analysis of driver speeding and glancing behavior, were implemented to investigate the safety impact of bicycle treatments at the segment- and the intersection-levels on bicycle safety. Prediction models were developed to predict bicycle-motorized vehicle crashes at road segments and signalized intersections, and traffic conflicts between straight-going bicyclists and right-turning vehicles at signalized intersections. Driver speeding and glancing behavior was analysed for the segment and the intersection levels. A mode classification framework to classify trajectories recorded using a radar-based sensor was developed to test the feasibility of using radar-based sensors in field studies. The findings of this dissertation contribute to bicycle safety research in terms of quantifying the safety impact of various bicycle treatment types and how to assess and also, by showing how to assess bicycle safety. The findings of this research have the potential to stand as a valuable tool for transportation policymakers and officials in charge of establishing safe bicycle networks

Crowdsourcing Data-driven Development of Bicycle Safety Performance Functions (SPFs) : Microscopic and Macroscopic Scales

While riding bicycles has been promoted for its health, economic, and environmental benefits, it also complements other modes to complete a safe, efficient, and reliable transportation system. However, the dramatic increase of bicycle usage in the U.S. is accompanied by a growth of bicycle crashes. The U.S. Department of Transportation, therefore, is focusing on providing safer riding environments. Providing a more bicycle friendly environment means more investment in (but not limited to) bicycle infrastructure. A correct prediction of bicycle crashes can increase the return on this investment. One useful tool to understand the causality and predict crashes is Safety Performance Functions (SPFs), but no sophisticated SPFs have been established for bicycles. Therefore, the objective of this thesis is to establish SPFs for microscopic (intersection) and macroscopic (corridor) scales in medium and large size cities using crowdsourced bicycle data, with a case study in the Portland and Eugene-Springfield metropolitan, which overcomes the challenge of insufficient bicycle volume data and crash data. Specifically, in this research 1) bicycle SPFs are created for intersections and corridors that have not been sufficiently studied; 2) bicycle crash severity distributions are used the first time to predict the number of bicycle crashes with different crash severity levels; 3) affordable crowdsourced bicycle volume data – STRAVA® is chosen to solve the problem of limited data; 4) STRAVA® data was verified to be able to represent general bicyclists by comparison with automatic bike count station data; 5) a general framework for building SPFs was developed for jurisdictions.Keywords: SPFs, Crowdsourced Data, Bicycle Safety, STRAV

14-02 Developing Public Health Performance Measures to Capture the Effects of Transportation Facilities on Multiple Public Health Outcomes

Increasingly, federal transportation and public health agencies are working together to identify transportation investments that improve public health. Investments in transportation infrastructure represent one method to utilize transportation to improve public health outcomes. The ideal transportation investment is one that not only provides safe access for pedestrians, bicyclists, motorists and transit riders, but it also promotes more utilitarian or recreational trips for walking and biking in an environment of safe air quality. However, public health objectives can be at conflict when designing transportation infrastructure to support active commuting. For example, infrastructure investments may be made that promote physical activity through utilitarian commuting, yet at the same time, the investment may be made in an area that is characterized by poor air quality or creates an unsafe condition. The purpose of the research is to identify potential performance measures that can foster improved decision making around these investments. The key research contribution is the development of performance measures that can be used in the field to evaluate multiple public health concerns and improve decision making. Secondly, it advances strategies to effectively capture the dimension of safety and physical activity in a manner that considers the conditions under which pedestrian and bicycling activity is likely to increase. The objectives of the project are accomplished through the use and integration of multiple methods, including student-based project learning, expert surveys, content analysis and quantitative statistical techniques

Cycling network discontinuities and their effects on cyclist behaviour and safety

RÉSUMÉ: Le cyclisme est généralement considéré comme le mode de transport le plus dangereux, car les collisions avec des véhicules sont plus susceptibles de provoquer des blessures graves et même la mort que les autres usagers de la route à l’exception des piétons. Compte tenu de ses nombreux avantages environnementaux et sociaux, les villes encouragent le cyclisme en tant que mode de transport abordable et développent leur infrastructure cyclable.----------ABSTRACT: Cycling is widely considered to be the riskiest mode of transport since collisions with vehicles are more likely to result in serious injuries or even death than other road users except pedestrians. Given its many environmental and social benefits, cities are encouraging cycling as an affordable mode of transport and are expanding their cycling infrastructure. While cities are aiming to increase cycling mode share, their alarming safety statistics have compelled transportation researchers and planners as well as city officials and decision makers to invest resources in designing, implementing and improving the cycling network to safely accommodate cyclists

Impacte da interação entre veículos motorizados e bicicletas na escolha de rota, desempenho de tráfego, emissões e segurança

Mobility in urban areas is highly complex because of the variety of possible facilities and routes, the multitude of origins and destinations, the increase of population and traffic. Increased use of active modes, such as cycling, presents economic and environmental benefits, and contributes to health improvement. However, it can lead to safety concerns such as bicycles sudden or unexpected movements mainly when circulating together with motor vehicles (MVs) or when there is an overtaking situation between MVs and bicycles. The main goal of this doctoral thesis is to quantify and assess the impact of the interaction motor vehicle-bicycle on traffic performance, road safety and emissions to define a multi-objective analysis model of the impacts regarding the use of motor vehicle and/or bicycle. The thesis was focused on three main topics developed based on the evaluation of traffic performance, safety and emissions at urban areas : (i) to perform a multi-objective analysis in an integrated manner of the traffic performance, pollutant emissions and road conflicts between bicycles and MVs at a signalized intersection; (ii) to assess the driving volatility in MV-bicycle interactions at two-lane roundabouts and its impacts on safety, pollutant emissions and traffic performance; and (iii) to analyze the impacts of the overtaking lateral distance between a bicycle and a MV on road safety and energy consumption at two-lane urban roads. Second-by-second bicycle and vehicle dynamic data were collected using GPS travel recorders. The methodology developed in this thesis was applied based on real world case studies at different urban road types in the city of Aveiro, Portugal. The present work uses a microscopic simulation platform of traffic (VISSIM), road safety (Surrogate Safety Assessment Methodology – SSAM) and emissions (Vehicle Specific Power – VSP) to analyze traffic operations, road safety concerns and to estimate carbon dioxide (CO2), nitrogen oxide (NOX), carbon monoxide (CO), and hydrocarbons (HC) pollutant emissions. Furthermore, the Fast Non-Dominated Sorting Genetic Algorithm (NSGA-II) was used in order to address the multi-objective analysis of traffic performance, road conflicts between MVs and bicycles, and emissions. Bicycle Specific Power (BSP) and VSP concepts were used in order to analyze the impacts on cyclist and vehicle energy consumption as well. The findings showed that roundabouts present, in general, better traffic performance (number of stops and travel time reduced in 78% and 14%, respectively) and less emissions (CO2, NOX, and HC decreased 9%, 7%, and 12%, respectively) than other intersections, even with high demand of cyclists (270 bicycles per hour). Regarding safety, roundabout layout lead to more severe conflicts and potential crashes while the number of total conflicts can be reduced significantly (-49%). It was also found that the impact of MVs and bicycles speeds, as well as roundabout design, were more important factors than bicycle volumes at roundabouts. Considering the MV-bicycle interaction at two-lane roundabout, the results of emissions dictated good relationships (R2 > 70%) between acceleration and VSP modes distributions. Finally, the findings showed 50% of overtaking lateral distance (between bicycle and MV) lower than 0.5m in both morning and afternoon peak hours. Moreover, it was found that there was a good fit between overtaking lateral distance and traffic volumes in morning (R2 = 72%) and afternoon (R2 = 67%) peak hours. The findings of this research can be useful for policy makers of the mobility and road safety fields, municipalities, road designers, and traffic engineers.A complexidade inerente à mobilidade em áreas urbanas está associada ao excesso de tráfego e à multiplicidade de origem-destinos, rotas e motivos de viagem. O incremento do uso dos modos suaves, nomeadamente da bicicleta, apresenta benefícios económicos e ambientais, contribuindo para a melhoria da saúde. No entanto, a presença de bicicletas acarreta preocupações ao nível da segurança dos ciclistas. As questões de segurança podem estar relacionadas com movimentos súbitos ou inesperados dos ciclistas, principalmente quando circulam em conjunto com veículos motorizados (VMs), ou quando há uma situação de ultrapassagem entre VMs e bicicletas. O principal objetivo da Tese de Doutoramento consistiu em quantificar e avaliar o impacto da interação entre veículos motorizados e bicicletas ao nível do desempenho de tráfego, segurança rodoviária e emissões para definir um modelo de análise multiobjetivo. A tese foi focada em três tópicos principais, desenvolvidos com base na avaliação do desempenho do tráfego, segurança e emissões em áreas urbanas: (i) análise multiobjetivo de forma integrada do desempenho do tráfego, emissões poluentes e conflitos rodoviários entre bicicletas e VMs em intersecções sinalizadas; (ii) avaliação da volatilidade de condução em interações VM-bicicleta em rotundas de duas vias e seus impactos na segurança, emissões de poluentes e desempenho de tráfego; e (iii) análise dos impactos ao nível de segurança rodoviária e consumo de energia em vias urbanas, com a avaliaçao da distância lateral de ultrapassagem entre uma bicicleta e um VM. Os dados da dinâmica do velocípede e do VM foram recolhidos e gravados segundo a segundo com um GPS. A metodologia desenvolvida nesta tese foi aplicada tendo por base os estudos de caso associados a diferentes tipos de vias urbanas na cidade de Aveiro, Portugal. O presente trabalho utiliza uma plataforma de simulação microscópica de tráfego (VISSIM), segurança rodoviária (SSAM) e emissões (Potência Específica do Veículo - VSP) para analisar as operações relacionadas com tráfego, questões com segurança rodoviária e estimar o dióxido de carbono (CO2), emissões de poluentes como o óxido de azoto (NOX), monóxido de carbono (CO) e hidrocarbonetos (HC). Além disso, para a análise multiobjetivo do desempenho do tráfego, conflitos rodoviários entre VMs e bicicletas, e emissões, o algoritmo genético NSGA-II (Nondominated sorted genetic algorithm II) foi utilizado. As metodologias de Potência Específica de Bicicleta (BSP) e VSP foram usados para analisar os impactos no consumo de energia do ciclista e do veículo, respetivamente. Os resultados mostraram que, em geral, as rotundas apresentam melhor desempenho de tráfego (número de paragens e tempo de viagem reduzidos em 78% e 14%, respetivamente) e menores emissões (CO2, NOX e HC diminuíram 9%, 7% e 12%, respetivamente) quando comparadas a outras interseções, mesmo com elevados níveis de ciclistas (270 bicicletas por hora). Em relação à segurança, o design da rotunda tende a favorecer a ocorrência de conflitos mais graves e potenciais acidentes, apesar do número total de conflitos poder diminuir significativamente (menos 49%). Descobriu-se também que o impacto das velocidades de circulação dos VMs e das bicicletas, bem como o design da rotunda constituem fatores mais importantes do que o volume de ciclistas nas rotundas. Considerando a interação VM-bicicleta numa rotunda de duas vias, os resultados das emissões sugerem boas relações (R2> 70%) entre as distribuições dos modos de aceleração e VSP. Por fim, os resultados mostraram que em 50% das ultrapassagens a distância lateral entre o velocípede e o VM foi menor que 0,5m, tanto na hora de ponta da manhã como da tarde. Além disso, verificou-se um bom ajuste entre a distância lateral de ultrapassagem e os volumes de tráfego nas horas de ponta da manhã (R2 = 72%) e da tarde (R2 = 67%). A metodologia e resultados desta investigação poderão ser utilizados por decisores políticos na área da mobilidade e da segurança rodoviária, câmaras, gestores e engenheiros de tráfego.Programa Doutoral em Engenharia Mecânic

2014 Year in Review

The Mountain-Plains Consortium (MPC) theme is "Transportation Infrastructure and Operations to Support Sustainable Energy Development and the Safe Movement of People and Goods". MPC is a competitively selected University Transportation Center sponsored by the U.S. Department of Transportation through its Research and Innovative Technology Administration

Real-world impacts of drone implementation in data collection of fatal accidents

The objective of this study was to analyze the use of drones and data collected in fatal accident investigations in accident scenes in Austin, Texas. The study compares data pre and post drones being used by the police officers of the Austin Police Department. The study presents a new way to collect evidence for fatal vehicle accidents and the attempts to apply the technology in the real world setting of vehicle investigations. The research findings are intended to be used by other municipalities before they implement the technology for their traffic accident investigations.The datasets used in this study came directly from the Computer Aided Dispatch (CAD) reports filed by officers in the Austin Police Department. The size of data files came from additional data sources in the records of fatal accident scenes. Time sequences and data file sizes worked to identify how much time was needed for a police officer to establish a full investigation with a drone while working a fatality and helps municipalities understand the data storage requirements for this type of data collection technique.The study found that when drones are introduced to fatal accident investigations, they increase the duration of the time needed to investigate a scene. The use of drones also increases the use of data for the storage of imaging taken by the drone in this type of case files. Depending on the priorities of a municipality, time and data storage increases, could impact the decision to implement drones as a means to collect data in the field for fatal vehicle accidents.Small sample size from a single municipality limits inference that could be drawn from results to other cities of the same size and demographic make-up. The study, does however, lead to providing beneficial information on potential impacts of drones in police investigation settings. The data can be used by policy makers to balance the value that drones bring with the burden of their implementation

International overview on the legal framework for highly automated vehicles

The evolution of Autonomous and automated technologies during the last decades has been constant and maintained. All of us can remember an old film, in which they shown us a driverless car, and we thought it was just an unreal object born of filmmakers imagination. However, nowadays Highly Automated Vehicles are a reality, even not in our daily lives. Hardly a day we don’t have news about Tesla launching a new model or Google showing the new features of their autonomous car. But don’t have to travel far away from our borders. Here in Europe we also can find different companies trying, with more or less success depending on with, not to be lagged behind in this race. But today their biggest problem is not only the liability of their innovative technology, but also the legal framework for Highly Automated Vehicles. As a quick summary, in only a few countries they have testing licenses, which not allow them to freely drive, and to the contrary most nearly ban their use. The next milestone in autonomous driving is to build and homogeneous, safe and global legal framework. With this in mind, this paper presents an international overview on the legal framework for Highly Automated Vehicles. We also present de different issues that such technologies have to face to and which they have to overcome in the next years to be a real and daily technology

Identification of infrastructure related risk factors, Deliverable 5.1 of the H2020 project SafetyCube

The present Deliverable (D5.1) describes the identification and evaluation of infrastructure related risk factors. It outlines the results of Task 5.1 of WP5 of SafetyCube, which aimed to identify and evaluate infrastructure related risk factors and related road safety problems by (i) presenting a taxonomy of infrastructure related risks, (ii) identifying “hot topics” of concern for relevant stakeholders and (iii) evaluating the relative importance for road safety outcomes (crash risk, crash frequency and severity etc.) within the scientific literature for each identified risk factor. To help achieve this, Task 5.1 has initially exploited current knowledge (e.g. existing studies) and, where possible, existing accident data (macroscopic and in-depth) in order to identify and rank risk factors related to the road infrastructure. This information will help further on in WP5 to identify countermeasures for addressing these risk factors and finally to undertake an assessment of the effects of these countermeasures. In order to develop a comprehensive taxonomy of road infrastructure-related risks, an overview of infrastructure safety across Europe was undertaken to identify the main types of road infrastructure-related risks, using key resources and publications such as the European Road Safety Observatory (ERSO), The Handbook of Road Safety Measures (Elvik et al., 2009), the iRAP toolkit and the SWOV factsheets, to name a few. The taxonomy developed contained 59 specific risk factors within 16 general risk factors, all within 10 infrastructure elements. In addition to this, stakeholder consultations in the form of a series of workshops were undertaken to prioritise risk factors (‘hot topics’) based on the feedback from the stakeholders on which risk factors they considered to be the most important or most relevant in terms of road infrastructure safety. The stakeholders who attended the workshops had a wide range of backgrounds (e.g. government, industry, research, relevant consumer organisations etc.) and a wide range of interests and knowledge. The identified ‘hot topics’ were ranked in terms of importance (i.e. which would have the greatest effect on road safety). SafetyCube analysis will put the greatest emphasis on these topics (e.g. pedestrian/cyclist safety, crossings, visibility, removing obstacles). To evaluate the scientific literature, a methodology was developed in Work Package 3 of the SafetyCube project. WP5 has applied this methodology to road infrastructure risk factors. This uniformed approach facilitated systematic searching of the scientific literature and consistent evaluation of the evidence for each risk factor. The method included a literature search strategy, a ‘coding template’ to record key data and metadata from individual studies, and guidelines for summarising the findings (Martensen et al, 2016b). The main databases used in the WP5 literature search were Scopus and TRID, with some risk factors utilising additional database searches (e.g. Google Scholar, Science Direct). Studies using crash data were considered highest priority. Where a high number of studies were found, further selection criteria were applied to ensure the best quality studies were included in the analysis (e.g. key meta-analyses, recent studies, country origin, importance). Once the most relevant studies were identified for a risk factor, each study was coded within a template developed in WP3. Information coded for each study included road system element, basic study information, road user group information, study design, measures of exposure, measures of outcomes and types of effects. The information in the coded templates will be included in the relational database developed to serve as the main source (‘back end’) of the Decision Support System (DSS) being developed for SafetyCube. Each risk factor was assigned a secondary coding partner who would carry out the control procedure and would discuss with the primary coding partner any coding issues they had found. Once all studies were coded for a risk factor, a synopsis was created, synthesising the coded studies and outlining the main findings in the form of meta-analyses (where possible) or another type of comprehensive synthesis (e.g. vote-count analysis). Each synopsis consists of three sections: a 2 page summary (including abstract, overview of effects and analysis methods); a scientific overview (short literature synthesis, overview of studies, analysis methods and analysis of the effects) and finally supporting documents (e.g. details of literature search and comparison of available studies in detail, if relevant). To enrich the background information in the synopses, in-depth accident investigation data from a number of sources across Europe (i.e. GIDAS, CARE/CADaS) was sourced. Not all risk factors could be enhanced with this data, but where it was possible, the aim was to provide further information on the type of crash scenarios typically found in collisions where specific infrastructure-related risk factors are present. If present, this data was included in the synopsis for the specific risk factor. After undertaking the literature search and coding of the studies, it was found that for some risk factors, not enough detailed studies could be found to allow a synopsis to be written. Therefore, the revised number of specific risk factors that did have a synopsis written was 37, within 7 infrastructure elements. Nevertheless, the coded studies on the remaining risk factors will be included in the database to be accessible by the interested DSS users. At the start of each synopsis, the risk factor is assigned a colour code, which indicates how important this risk factor is in terms of the amount of evidence demonstrating its impact on road safety in terms of increasing crash risk or severity. The code can either be Red (very clear increased risk), Yellow (probably risky), Grey (unclear results) or Green (probably not risky). In total, eight risk factors were given a Red code (e.g. traffic volume, traffic composition, road surface deficiencies, shoulder deficiencies, workzone length, low curve radius), twenty were given a Yellow code (e.g. secondary crashes, risks associated with road type, narrow lane or median, roadside deficiencies, type of junction, design and visibility at junctions) seven were given a Grey code (e.g. congestion, frost and snow, densely spaced junctions etc.). The specific risk factors given the red code were found to be distributed across a range of infrastructure elements, demonstrating that the greatest risk is spread across several aspects of infrastructure design and traffic control. However, four ‘hot topics’ were rated as being risky, which were ‘small work-zone length’, ‘low curve radius’, ‘absence of shoulder’ and ‘narrow shoulder’. Some limitations were identified. Firstly, because of the method used to attribute colour code, it is in theory possible for a risk factor with a Yellow colour code to have a greater overall magnitude of impact on road safety than a risk factor coded Red. This would occur if studies reported a large impact of a risk factor but without sufficient consistency to allocate a red colour code. Road safety benefits should be expected from implementing measures to mitigate Yellow as well as Red coded infrastructure risks. Secondly, findings may have been limited by both the implemented literature search strategy and the quality of the studies identified, but this was to ensure the studies included were of sufficiently high quality to inform understanding of the risk factor. Finally, due to difficulties of finding relevant studies, it was not possible to evaluate the effects on road safety of all topics listed in the taxonomy. The next task of WP5 is to begin identifying measures that will counter the identified risk factors. Priority will be placed on investigating measures aimed to mitigate the risk factors identified as Red. The priority of risk factors in the Yellow category will depend on why they were assigned to this category and whether or not they are a hot topic