We investigate the impacts of spatial pricing for ride-sourcing services in a Stackelberg framework considering traffic congestion. In the lower level, we use combined distribution and assignment approaches to explicitly capture the interactions between drivers' relocation, riders' mode choice, and all travelers' routing decisions. In the upper level, a monopolistic transportation network company (TNC) determines spatial pricing strategies to minimize imbalance in a twosided markets. We show the existence of the optimal pricing strategies for locational imbalance minimization, and propose effective algorithms with reliable convergence properties. Furthermore, the optimal pricing is unique, and can be solved in a convex reformulation when matching time can be ignored. We conduct numerical experiments on different scales of transportation networks with different TNC objectives to generate policy insights on how spatial pricing could impact transportation systems.
In Dhaka, which is the capital city of Bangladesh, significant percentages of commuters walk to meet their daily commuting demand. However, there is scarcity of research in Dhaka for walkability assessment. This research tried to overcome that scarcity by developing a measurement tool to assess the walking environment. Methodological approach adopted by this research is the combination of subjective and objective method. Assessment results were converted into 1-point scale. Results showed that Dhaka is seriously lack of good quality footpath and disable facilities. Excessive noise pollution is also one of the significant issues for pedestrians in Dhaka. Any other similar cities walking environment can be assessed by this approach.
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