Abstract

The planning of vehicle-dependent cities across the world with emerging technologies like automated vehicles must be amended to make them pedestrian-friendly. Therefore, there is a need to reorganise the urban streets to create more spaces for pedestrians, even with the presence of automated vehicles (AVs). This research proposes the concept of a superblock model in the presence of automated vehicles to meet this challenge. This research aims to assess the impacts of AVs on pedestrian-friendly streets using a superblock approach. In the superblock model, cut-through traffic demand is restricted, and traffic generated or attracted to a superblock can have access, allowing for more room for public spaces. This study systematically discusses the superblock model implemented in a network with a grid structure using a genetic algorithm. It addresses the dynamic user equilibrium assignment for demand and topology segmentation. Three scenarios are considered due to the longer period of transition from traditional vehicles to fully AVs. The study evaluates the potential and constraints of implementing the superblock model with different penetration rates of AVs in the system by defining variable traffic demand and the variable number of superblocks. Furthermore, a cost-benefit analysis of the proposed methodology is conducted. The proposed model is implemented on a real-time network of Barcelona city, and the findings of this study are summarised by the macroscopic fundamental diagram, which depicts the improvement in the performance of the network with the inclusion of AVs.

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