UNIVERSIDADE DE LISBOA INSTITUTO SUPERIOR TÉCNICO PROBABILISTIC SAFETY ANALYSIS USING TRAFFIC MICROSCOPIC SIMULATION Carlos Miguel Lima de Azevedo Supervisor: Doctor João Paulo Lourenço Cardoso Co-Supervisors: Doctor Moshe E. Ben-Akiva Doctor Filipe Manuel Mercier Vilaça e Moura Thesis approved in public session to obtain the PhD Degree in Transportation Systems Jury final classification: Pass with Merit Jury Chairperson: Chairman of the IST Scientific Board Members of the Committee: Doctor Luís Guilherme de Picado Santos Doctor Carlos Manuel Robalo Lisboa Bento Doctor João Paulo Lourenço Cardoso Doctor José Pedro Maia Pimentel Tavares Doctor João António de Abreu e Silva Doctor Luís Miguel Garrido Martinez 2014 UNIVERSIDADE DE LISBOA INSTITUTO SUPERIOR TÉCNICO PROBABILISTIC SAFETY ANALYSIS USING TRAFFIC MICROSCOPIC SIMULATION Carlos Miguel Lima de Azevedo Supervisor: Doctor João Paulo Lourenço Cardoso Co-Supervisors: Doctor Moshe E. Ben-Akiva Doctor Filipe Manuel Mercier Vilaça e Moura Thesis approved in public session to obtain the PhD Degree in Transportation Systems Jury final classifiction: Pass with Merit Jury Chairperson: Chairman of the IST Scientific Board Members of the Committee: Doctor Luís Guilherme de Picado Santos, Full Professor of the Instituto Superior Técnico, University of Lisbon; Doctor Carlos Manuel Robalo Lisboa Bento, Associate Professor (with Habilitation) of the Faculty of Science and Technology of the University of Coimbra; Doctor João Paulo Lourenço Cardoso, Principal Investigator (Habilitated to Research Coordination) of the National Laboratory of Civil Engineering; Doctor José Pedro Maia Pimentel Tavares, Assistant Professor of the Faculty of Engineering of the University of Porto; Doctor João António de Abreu e Silva, Invited Assistant Professor of the Instituto Superior Técnico, University of Lisbon; Doctor Luís Miguel Garrido Martinez, Invited Assistant Professor of the Instituto Superior Técnico, University of Lisbon. INSTITUIÇÕES FINANCIADORAS 2014 Abstract Traffic microscopic simulation applications are currently a common tool in road system analysis and several application attempts to safety performance assessment have been recently carried out. However, current most common approaches still ignore causal rela- tionships between different levels of vehicle interactions or accident types, lacking for a physical representation of the accident phenomena itself. A new generic probabilistic safety assessment framework for traffic microscopic sim- ulation tools is proposed. The probability of a specific accident occurrence is assumed to be estimable by an accident propensity function, composed by a deterministic safety score component and a random component. The formulation of the safety score compo- nent may be specified depending on the type of occurrence and on the simulation features. The generic model is then specified for the case of urban motorways for no-accident events and three types of accidents: rear-end, lane-changing and run-off-road accidents. To deal with the lack of available trajectory data for different occurrence types, ar- tificial trajectories from a calibrated microscopic simulation tool are used. These trajec- tories are obtained following a comprehensive calibration effort: extracting trajectories for a generic scenario, calibration of the simulation tool using the collected trajectories, and re-calibration of the simulation model using aggregate data for each event selected at replication. An advanced method for automatic extraction of vehicle trajectories using aerial imagery is presented, in order to collect the detailed traffic variables. A global sensitivity analysis based calibration is proposed to deal with uncertainty in the detailed calibration of complex models. The parameters of the safety model are estimated using artificial vehicle trajectory data calibrated for the Portuguese A44 motorway and using the MITSIMLab simulator. With this study it is shown how traffic microsimulation tools may replicate detailed traf- fic statistics that are essential to explain different accident phenomenon and how the quality of this replication is strongly linked to the simulation modelling formulation, the calibration methodology and the available data. Key-words: traffic microscopic simulation; road safety; probabilistic assessment; driving behaviour modeling; surrogate safety measures; discrete choice; global sensitivity analysis; calibration; vehicle tracking; remote sensing. 5 6 Resumo As aplicações de simulação microscópica de tráfego representam, hoje em dia, uma ferra- menta importante na análise de sistemas de transporte. Recentemente, várias tentativas de aplicação destes recursos para a avaliação do desempenho em segurança rodoviária foram concretizadas. No entanto, as abordagens mais comuns ainda carecem da explici- tação de relações causa-efeito, não só relativamente às diferentes interações entre veículos como também na representação física da ocorrência de vários tipos de acidentes. Neste estudo é proposto um novo modelo genérico de avaliação probabilística da segu- rança rodoviária para integração em ferramentas de simulação microscópica de tráfego. A probabilidade de ocorrência de um determinado evento é definida em função de uma com- ponente determinística, designada por grau de segurança, e de uma componente aleatória. O grau de segurança é especificado consoante o tipo de ocorrência, tendo em conta as car- acterísticas específicas do simulador utilizado. Este modelo genérico é pormenorizado para as auto-estradas urbanas considerando os eventos de não-acidente e três tipos de acidentes: colisões traseiras, colisões laterais associadas a mudanças de via e despistes. Visto não existirem ainda dados de trajectórias de veículos para diferentes tipos de ocorrência, na estimação do modelo proposto foram utilizadas trajectórias artificiais ger- adas através de um simulador microscópico de tráfego. Estes dados foram obtidos após um processo de calibração avançada: extracção de trajectórias para um cenário genérico, calibração do simulador com base nestas trajectórias, e nova calibração do modelo para cada um dos eventos a replicar. Para o efeito foram desenvolvidos um algoritmo de ex- tracção automática de trajectórias de veículos registados em imagens aéreas e um método inovador de calibração de modelos complexos baseado em análise de sensibilidade global. Os parâmetros do modelo de segurança são estimados usando dados recolhidos para a auto-estrada A44, em Portugal, e usando o simulador de tráfego MITSIMLab. É demon- strado o potencial da simulação microscópica em replicar estatísticas detalhadas de tráfego, essenciais na modelação de diferentes tipos de acidente, e a sua dependência relativamente à especificação do modelo de simulação, metodologia de calibração e dados disponíveis. Palavras-chave: simulação microscópica de tráfego; segurança rodoviária; análise prob- abilística; modelação do comportamento do condutor; indicadores de segurança; modelos discretos; análise de sensibilidade; calibração; seguimento de veículos; sensor remoto. 7 8 Acknowledgements I would like to express my sincere gratitude to Prof. João Cardoso and Prof. Moshe Ben-Akiva for their continuous guidance, support and friendship. It has been a privilege to work with both of them and have the opportunity to learn from their vast knowledge. I am also thankful to Prof. Filipe Moura whom interest and guidance was a source of inspiration. Dr. Biagio Ciuffo from the Joint Research Center deserves a very special thanks as his helpful guidance for more than a year allowed to acquire a strong knowledge in uncertainty analysis. Some parts of this thesis were joint work with Biagio and under the EU Commission’s Cost Action TU0903 (Multitude). His technical and practical insights for making the complex things tractable were invaluable for the presented and future research. Also, this dissertation could not be completed without the generous help of Prof. João Costeira and Dr. Manuel Marques from the Institute for Systems and Robotics at IST, without whom I would not have discovered the potential and fun of image processing. I am thankful to my colleagues from the National Laboratory of Civil Engineering (LNEC) who helped me in the arduous task of collecting and processing a considerable amount of data: Jośe Gil, Cristina Sousa, Cristina Cabral, Paulo Miranda, Francisco Cavalheiro, José Carmo, Óscar López, Ivan Lopes and Acácio Monteiro. A special thanks to the Portuguese National Grid Initiative and namely to João Martins and Gonçalo Borges for the use of one of the most advanced computational infrastructures for research in Portugal; to Ge Qiao from ETH Zurich for is precious help on the EE design; and to Lu Lu from MIT for providing part of the code used in the WSPSA calibration. I am grateful to LNEC and to the Department of Transportation for hosting me, providing the resources used in this research, and funding my scholarship jointly with the Fundação para a Ciência e Tecnologia through the MIT Portugal Program. I am also thankful to InfoPortugal, S.A. for the precious help in the aerial image collection, 9 especially to Alexandre Gomes for the help in the data processing and for distracting me when I first saw the size of the aircraft we had to fly in; to José Luís Almeida Garret from LNEC for developing the electronic trigger used in the sequential photo shooting; and to Ascendi, S.A. for providing the traffic data used in this thesis. The guidance and motivation from my close friends at LNEC, Sandra Vieira, André Paixão,