The increasingly urbanized world needs a solution to solve one of the most difficult problems – traffic congestion and safety. Researchers, consultants, and local officials are all attempting to solve these problems with different methods. However, it is apparent that understanding the driving behaviors on the roadway network and implementing roadway configurations accordingly is one of the great solutions. Therefore, the modeling of driving behavior would be the focus of this two-part thesis. Chapter two of this thesis will elaborate on the modeling of various driving behavior types in the microsimulation software by providing an easier-to-calibrate alternative for the driver behavior model in the microsimulation. The calibration method would leverage VISSIM, its highly customizable External driver model (EDM) API, JMP Pro's experiment design and sensitivity analysis, and SSAM's trajectory analysis. Then a set of driver model parameters are produced through sensitivity analysis, which is effective in producing a set of traffic conflicts that matches a preset target. Chapter three of this thesis focuses on simulating aggressive driving behaviors in a microsimulation and driving simulator co-simulation environment. Two co-simulation platforms are demonstrated, and the data collection are done in the VISSIM-Unity platform to collect microscopic driving data and trajectory data from the aggressive driver. Data analysis are performed on both datasets and determine the aggressive driver's safety impact. / Master of Science / The increasingly urbanized world needs a solution to solve one of the most difficult problems – traffic jams and safety. Researchers, engineers, and local officials are all attempting to solve these problems with different methods. However, it is apparent that understanding people's driving behavior on the road and designing the roads and policies to cater to these driving behaviors is one of the great solutions. Therefore, the modeling of driving behavior would be the focus of this two-part thesis. Chapter two of this thesis will experiment with a traffic simulator (which is a tool used for designing and simulating different road configurations like roundabouts and numbers of lanes) and provide an easier and more accurate way to represent various driving styles in the traffic simulator. The calibration method would leverage a driving simulator called VISSIM, an adjustable driver behavior model, a vehicle route tracker, and a vehicle route conflict analysis tool. Then a set of driving behavior parameters would be produced to match the possible traffic accident count in the traffic simulator. Chapter three of this thesis focuses on simulating aggressive driving behaviors in a traffic simulator and driving simulator (like that of those with a steering). Two driving simulator platforms are tested, and the data collection are done in one of the platforms to collect driving data and vehicle route tracker data from the aggressive driver. Data analysis are performed on both types of data and determine the aggressive driver's safety impact.

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.