Cities worldwide adopted lockdown policies in response to the outbreak of coronavirus disease 2019 (COVID-19), significantly influencing people's travel behavior. In particular, micro-mobility, an emerging mode of urban transport, is profoundly shaped by this crisis. However, there is limited research devoted to understanding the rapidly evolving trip patterns of micro-mobility in response to COVID-19. To fill this gap, we analyze the changes in micro-mobility usage before and during the lockdown period exploiting high-resolution micro-mobility trip data collected in Zurich, Switzerland. Specifically, docked bike, docked e-bike, and dockless e-bike are evaluated and compared from the perspective of space, time and semantics. First, the spatial and temporal analysis results uncover that the number of trips decreased remarkably during the lockdown period. The striking difference between the normal and lockdown period is the decline in the peak hours of workdays. Second, the origin-destination flows are used to construct spatially embedded networks. The results suggest that the origin-destination pairs remain similar during the lockdown period, while the numbers of trips between each origin-destination pair is reduced due to COVID-19 pandemic. Finally, the semantic analysis is conducted to uncover the changes in trip purpose. It is revealed that the proportions of Home, Park, and Grocery activities increase, while the proportions of Leisure and Shopping activities decrease during the lockdown period. The above results can help planners and policymakers better make evidence-based policies regarding micro-mobility in the post-pandemic society.

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In urban areas, where road space is limited, it is important to provide efficient public and private transportation systems to maximize person throughput, for example from a signalized intersection. To this end, this research looks at providing bus priority using a dedicated bus lane which is terminated upstream of the intersection, and placing an additional signal at this location, called a pre-signal. Although pre-signals are already implemented in some countries (e.g. UK, Denmark, and Switzerland), an adaptive control algorithm which responds to varying traffic demands has not yet been proposed and analyzed in the literature. This research aims to fill that gap by developing an adaptive control algorithm for pre-signals tailored to real-time private and public transportation demands. The necessary infrastructure to operate an adaptive pre-signal is established, and guidelines for implementation are provided. The relevant parameters regarding the boundary conditions for the adaptive algorithm are first determined, and then quantified for a typical case using a micro-simulation model. It is demonstrated with case studies that, under all considered scenarios, implementing a pre-signal with the proposed adaptive control algorithm will result in the least average person delay at the intersection. The algorithm is expected to function well with a wide range of car demands, bus frequencies, and bus passenger occupancies. Moreover, the algorithm is robust to errors in these input values, so exact information is not required.

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Bimodal urban networks are complex systems operating within multiple constraints. This paper develops an integrated and systematic framework for the optimization of bimodal urban networks using 3D-MFDs, considering the complexities of bimodality. With the proposed framework, effective strategies can be designed for the planning, management, and control of bimodal networks. In particular, strategies to provide public transport priority on the network level can be holistically evaluated. We apply this methodological framework to propose, model, and analyze one such strategy to provide public transport priority in the perimeter of urban networks. The proposed strategy addresses a pressing problem of the existing perimeter control (i.e. gating) schemes: public transport vehicles will be queuing with the cars in the perimeter and hence blocked from entering the network. This impairs the service quality of public transport. Adopting our proposed strategy, the inflows of public transport and cars can be regulated independently (i.e. both inflows are controllable), the network traffic can be managed more efficiently, and public transport priority can be provided. The performance of the proposed strategy is evaluated both analytically and with simulations. Results show that the proposed strategy always performs better than existing perimeter control schemes in terms of passenger mobility. Most importantly, it differentiates the public transport mode and the car mode, with much smaller queueing time outside the network for public transport. This can shift the transportation system to a more sustainable state in the long run. Policy recommendations are provided for a large range of traffic scenarios.