| Summary: | Developing a solid understanding of pedestrian behavior is important for promoting walking as an active mode of transportation and enhancing pedestrian safety. Computer simulation of pedestrian dynamics has gained recent interest as an important tool in analyzing pedestrian behavior in many applications. As such, this thesis presents the details of the development of a microscopic simulation model that is capable of modeling detailed pedestrian interactions. The model was developed based on the agent-based modeling approach, which outperforms other existing modeling approaches in accounting for the heterogeneity of the pedestrian population and considering the pedestrian intelligence. Key rules that control pedestrian interactions in the model were extracted from a detailed pedestrian behavior study that was conducted using an automated computer vision platform, developed at UBC. The model addressed both uni-directional and bi-directional pedestrian interactions. A comprehensive methodology for calibrating model parameters and validating its results was proposed in the thesis. Model parameters that could be measured from the data were directly calibrated from actual pedestrian trajectories, acquired by means of computer vision. Other parameters were indirectly calibrated using a Genetic Algorithm that aimed at minimizing the error between actual and simulated trajectories. The validation showed that the average error between actual and simulated trajectories was 0.35 meters. Detailed validation of the accuracy of simulating pedestrian behavior during different interactions showed that the model successfully reproduced the actual behavior taken by pedestrians in the actual data in 95% of the cases. The simulation model was then applied to analyze pedestrian behavior in two case studies in Vancouver and Oakland. The two case studies addressed different pedestrian flow conditions and different walking environments. The average errors between actual and simulated trajectories for the two studies were found to be 0.28 m and 0.49 m, respectively. The average speed errors were 0.06 m/s and 0.04 m/s in the two studies, correspondingly. The accuracy of reproducing the actual behavior of pedestrians exceeded 87% for most of interactions considered in the two studies. The accuracy of simulating group behavior during different interactions was found to be 96% and 92% in the two studies, respectively. === Applied Science, Faculty of === Civil Engineering, Department of === Graduate
|
|---|
