In order to achieve sustainable long-term transport infrastructure development, there is a growing need for fast, reliable and effective methods to evaluate and predict the impact of traffic safety measures. Recognising this need, and the need for an active traffic safety approach, this thesis focuses on traffic safety assessment and prediction based on the use of safety indicators that measure the spatial and/or temporal proximity of safety critical events. The main advantage of such measures is that they occur more frequently than accidents, and therefore require relatively short periods of study to establish values that can later be used for comparison, or for accident prediction purposes. There are a number of more generally accepted safety indicators including: Time-to-Accident, Time-to-Collision, and Post-Encroachment Time. These are based on different underlying principles and measurement techniques, including both on-site subjective estimation, and objective photometric measures. A major part of the work presented in this thesis, concerns identifying the potential and limitations of the different safety indicators with regard to their validity and reliability, and practical use for safety assessment and prediction purposes. This is done in conjunction with field studies in the urban and suburban environment, at both signalised and unsignalised intersections. Results from these studies indicate that on-site observation methods provide useful quantitative and qualitative information relatively quickly and efficiently, provided that they are used correctly. On the other hand, the methods based on photometric measurement (video-analysis) proved arduous and time-consuming. Furthermore, there are questions regarding the abilities of the Time-to-Collision and Post-Encroachment Time safety indicators to adequately represent interaction severity, suggesting possible flaws in fundamental concepts related to construct validity. Importantly, results showed that the relationship between safety indicators and traffic accidents is complex and equivocal, where many different factors and processes can impose a significant influence on safety. This makes generalised predictive modelling a particularly difficult task for safety analysts. The potential of micro-simulation for traffic safety and performance estimation based on the use of safety indicators was investigated in the second part of this thesis. Microscopic traffic simulation has become increasingly popular among transport planners, due to the fact that it serves as a safe and flexible off-line test environment for the estimation of dynamic and complex traffic system effects. It is useful and cost-effective in relation to the evaluation of issues concerning roadway design, and technological systems that influence road-user behaviour and vehicle performance. For reasons related to modelling fidelity and data quality, simulation has seldom been used for traffic safety estimation. Simulation model development is however, undergoing rapid development and the area of ‘safety-simulation’ and is recognised as having a high potential in the field of transport planning and traffic engineering. As part of the work in this thesis, practical simulation experiments were carried out to investigate this potential, and identify limitations. Based on the data from one of the earlier studies, and knowledge regarding important safety-influencing factors and behavioural processes, one of the simulation experiments showed evidence to suggest that realistic safety critical events could be generated and measured using safety indicators in a simulation environment, without making unnecessary and unrealistic behavioural assumptions. Furthermore, a second application of this methodology revealed the safety potential of a rear-end incident-reduction function used in standard vehicle actuated signalling. While both of these simulation studies highlighted the potential of this type of approach, the need for more flexible and realistic models of interactive behavioural processes could be identified in addition to the general need for greater active research into the field of safety simulation. / QC 20100830

Traffic models based on micro-simulation are becoming increasingly important as traffic analysistools. Due to the detailed traffic description, different micro-simulation models are needed tosimulate different traffic environments. The Rural Traffic Simulator, RuTSim, is a unique microtrafficsimulation model for traffic on rural roads. RuTSim is developed at VTI with support fromthe Swedish Transport Administration. Currently, a new version of the RuTSim model has beenimplemented based on the earlier one but with some enhancements. Due to these enhancements,the new implementation of RuTSim should be verified before being used to analyze real worldproblems. In this master’s thesis, a verification of the new implementation of the RuTSim model, RuTSim 2,has been carried out. This paper includes a description of traffic micro-simulation models forrural roads in general and a description of RuTSim model in particular. Common verificationtechniques of the simulation models are also discussed in this study. Based on the theoretical assessments, a model-to-model comparison verification scheme isselected to verify the RuTSim 2 model. That is, the model verification is performed by comparingthe simulation outputs from RuTSim 2 to the old version of RuTSim (RuTSim 1), since RuTSim1 is well verified and calibrated. Statistical hypothesis tests are used to check whether the meanand standard deviation differences of the simulation outputs between the two simulators aresignificant or not. Based on the verification results, the new version of the RuTSim model has comparable modelingof vehicle-vehicle and vehicle-infrastructure interactions as the old version. Furthermore, thehypothesis test results show that the differences of the mean simulation results of the twosimulators are not significant. Therefore, the new implementation of RuTSim model, RuTSim 2,has been proven to be equivalent model as the old version.

No description available.

Transport networks have to provide carriers with time-efficient alternative routes in case of disruptions. It is, therefore, essential for transport network planners and operators to identify sections within the network which, if broken, have a considerable negative impact on the networks performance. Research on transport network analysis provides lots of different approaches and models in order to identify such critical sections. Most of them, however, are only applicable to mono-modal transport networks and calculate indices which represent the criticality of sections by using aggregated data. The model presented, in contrast, focuses on the analysis of intermodal transport networks by using a traffic micro simulation. Based on available, real-life data, our approach models a transport network as well as its actual traffic participants and their individual decisions in case of a disruption. The resulting transport delay time due to a specific disruption helps to identify critical sections and critical networks, as a whole. Therefore, the results are a valuable decision support for transport network planners and operators in order to make the infrastructure less vulnerable, more attractive for carriers and thus more economically sustainable. In order to show the applicability of the model we analyse the Austrian intermodal transport network and show how critical sections can be evaluated by this approach. (authors' abstract)

Microsimulation is becoming more popular in transportation research. The purpose of this research is to explore the potential of microsimulation by integrating an existing activity-based travel demand model with an agent-based traffic simulation model. Differences in model precisions from the two models are resolved through a series of data conversions, and the models are able to form an iterative process similar to previous modelling frameworks. The resulting model is then used for emission modelling where the traditional average-speed model is improved by exploiting agent-based traffic simulation results. Results from emission modelling have demonstrated the advantages of the microsimulation approach over conventional methodologies that rely heavily on temporal or spatial aggregation.

Microsimulation is becoming more popular in transportation research. The purpose of this research is to explore the potential of microsimulation by integrating an existing activity-based travel demand model with an agent-based traffic simulation model. Differences in model precisions from the two models are resolved through a series of data conversions, and the models are able to form an iterative process similar to previous modelling frameworks. The resulting model is then used for emission modelling where the traditional average-speed model is improved by exploiting agent-based traffic simulation results. Results from emission modelling have demonstrated the advantages of the microsimulation approach over conventional methodologies that rely heavily on temporal or spatial aggregation.

Dans une perspective de meilleure évaluation des pratiques de mobilité quotidienne, il convient de recentrer les méthodes et les outils d’aide à la décision autour des acteurs des déplacements : les usagers. Dans cette logique le modèle MICROBILIS a été développé afin d’évaluer l’adaptation des stratégies des usagers par rapport à leur environnement des transports. Trois champs sont mobilisés : les modèles de micro-simulation d’affectation, la théorie des graphes et les systèmes multi-agents. L’environnement est modélisé à partir d’un modèle microscopique des déplacements et d’un graphe cellulaire, définissant la capacité du réseau. Les simulations permettent de retrouver les relations empiriques de la dynamique de trafic sur les sections et mettent en évidence des contraintes supérieures de capacité au niveau des carrefours. Le passage à la simulation d’un réseau de grande taille induit la complexification de l’environnement et la multiplication des cas particuliers. Il n’a pas été possible de réaliser ce passage sans réduire les hypothèses initiales, devenant ainsi non représentatives de la réalité. / From the perspective of best practice assessment of daily mobility, it should refocus the methods and tools for decision aid around the actors in travel: users. In this logic MICROBILIS model was developed to evaluate the adaptation strategies of users relative to their environmental transport. Three streams have been mobilized: the micro-simulation of assignment models, graph theory and multi-agent systems. The environment is modeled from a microscopic simulator of movements and a cellular graph, defining the network capacity. The simulations allow to find the empirical relationships of the dynamics of traffic on the sections and highlight upper capacity constraints at intersections. The transition to the simulation of a large network induces the complexity of the environment and the multiplication of particular cases. It was not possible to make this transition without reducing the initial assumptions, making it unrepresentative of reality.

Due to plans of reconstructing the local public transport stop in front of the railway station in Norrköping, southern Sweden, a simulation model was created to compare the current stop design with an alternative design. The micro simulation model was created with the simulation software Aimsun and includes scenarios based on the current traffic situation as well as future scenarios including assumptions for the future demand growth. While creating the alternative design, which provides a second lane for overtaking, several limitations in Aimsun were recognized and modifications were required to create simulation behaviour as close to reality as possible. Due to the software limitations the simulation results for the alternative design showed slightly higher results and made it difficult to make explicit comparisons of the output values. Nevertheless the output data indicated that both design layouts include remaining capacity of the public transport stop.

With many advances in transportation technology, micro-simulation models have proven to be a useful tool in transportation engineering alternative analyses. Micro-simulation software packages can be used to quickly and efficiently design new transportation infrastructure and strategies, while helping transportation planners and traffic engineers identify possible problems that might arise in a particular design alternative. Over the years these simulation packages have become more advanced, and their capabilities in terms of modeling complex, intricate intersections and producing useful outputs for analysis have increased. Today’s simulations can reproduce many facets of transportation design alternatives while generating outputs that help increase efficiency, reduce cost, optimize financing, and improve safety. Recently micro-simulation models have been employed in the analysis and design of alternative transit signal priority (TSP) strategies. This research reviews the similarities, differences and functional capabilities of two micro-simulation software packages: 1) VISSIM, and 2) S-Paramics. A special effort is made to discuss the usefulness of each package when used to analyze TSP alternatives for small and medium sized urban areas, where data and staff availability are typically limited. The paper includes a case study of Burlington, Vermont in which each software package is employed to evaluate several alternative TSP strategies. Each package is evaluated in terms of ease of use, usefulness of outputs, and consistency of results. The results of the evaluation are intended to guide planners and traffic engineers in small and medium urban areas in the selection of an appropriate simulation package for TSP analysis and design.

Past political regimes and socio-economic imbalances have led to the formation of a transport system in the Republic of South Africa (RSA) that is unique to the developing world. Affluent communities in metropolitan cities are situated close to economic activity, whereas the people in need of public transport are situated on the periphery of the cities. This demographic structure is opposite to that of developed countries and complicates both the provision of transport services and the planning process thereof. Multi-Agent Transport Simulation (MATSim) has been identified as an Agent-Based Simulation (ABS) approach that models individual travellers as autonomous entities to create large scale traffic simulations. The initial implementation of MATSim in the RSA successfully simulated private vehicle trips between home and work in the province of Gauteng, proving that there is enough data available to create a realistic multi-agent transport model. The initial implementation can be expanded to further enhance the simulation accuracy, but this requires the incorporation of additional primary and secondary activities into the initial transport demand. This study created a methodology to expand the initial implementation in the midst of limited data, and implemented this process for Gauteng. The first phase constructed a 10% synthetic population that represents the demographic structure of the actual population and identified various socio-demographic attributes that can influence an individual's travel behaviour. These attributes were assigned to the synthetic agents by following an approach that combines probabilistic sampling and rule-based models. The second phase used agents' individual attributes, and census, National Household Travel Survey (NHTS) and geospatial data to transform the synthetic population into a set of daily activity plans - one for every agent. All the agents' daily plans were combined into a plans.xml file that was used as input to MATSim, where the individuals' activity plans were executed simultaneously to model the transport decisions and behaviour of agents. Data deficiencies were overcome by contemplating various scenarios and comparing the macroscopic transport demand patterns thereof to the results of the initial implementation and to actual counting station statistics. This study successfully expanded the initial home-work-home implementation of MATSim by including additional non-work activities in the transport demand. The addition of non-work activities improved the simulation accuracy during both peak and off-peak periods, and the initial demand therefore provides an improved representation of the travel behaviour of individuals in Gauteng. / Dissertation (MEng)--University of Pretoria, 2011. / Industrial and Systems Engineering / unrestricted