Pedestrian-vehicle conflict analysis at signalized intersections using micro-simulation
2016 (English)Conference paper (Refereed)
The main goal of this study is to explore whether the VISSIM simulation model and Surrogate Safety Assessment Model (SSAM) can be used to provide the reasonable estimates for pedestrian-vehicle conflicts at signalized intersections. Two types of pedestrian-vehicle conflicts are discussed in this study, including vehicle-yield-pedestrian and pedestrian-yield-vehicle. A total of 42 hours videos were recorded at seven signalized intersections for field data collection. The calibrated and validated VISSIM model was used to generate pedestrian-vehicle conflicts and SSAM software was used to extract these conflicts by processing the vehicle trajectory file from the VISSIM model. The mean absolute percent error (MAPE) was used to determine the maximum TTC and PET thresholds for pedestrian-vehicle conflicts. The results showed that there was a best goodness-of-fit between simulated conflicts and observed conflicts when the maximum TTC threshold was set to be 2.7 and the maximum PET threshold was set to be 8. Moreover, the linear regression was developed to study the relationship between simulated conflicts from the micro-simulation and the observed conflicts from the field. The result indicated that there was a significant statistical relationship between the simulated conflicts and the observed conflicts. However, it was also found that the VISSIM model underestimated the pedestrian-vehicle conflicts. One possible reason was that the VISSIM simulation cannot generate the pedestrian-vehicle conflicts that involved the illegal pedestrian behaviors such as red light violation in the real world.
Place, publisher, year, edition, pages
Linköping: Statens väg- och transportforskningsinstitut, 2016.
Research subject X RSXC
IdentifiersURN: urn:nbn:se:vti:diva-10570OAI: oai:DiVA.org:vti-10570DiVA: diva2:926089
17th International Conference Road Safety On Five Continents (RS5C 2016), Rio de Janeiro, Brazil, 17-19 May 2016.