Highlights Measuring crowding through archived and real-time data using object detection tools. Object detection tools with surveillance video to quantify transit performance. Logistic regression models with automatic passenger counts and train operations data. Estimation of left-behind passengers at stations with farecard use only at entrance. Estimation and evaluation of waiting time as a transit service reliability measure.

Large urban special events significantly contribute to a city's vibrancy and economic growth but concurrently impose challenges on transportation systems due to alterations in mobility patterns. This study aims to shed light on mobility patterns by utilizing a unique, comprehensive dataset collected from the Helsinki public transport mobile application and Bluetooth beacons. Earlier methods, relying on mobile phone records or focusing on single traffic modes, do not fully grasp the intricacies of travel behavior during such events. We focus on the Vappu festivities (May 1st) in the Helsinki Metropolitan Area, a national holiday characterized by mass gatherings and outdoor activities. We examine and compare multi-modal mobility patterns during the event with those during typical non-working days in May 2022. Through this case study, we find that people tend to favor public transport over private cars and are prepared to walk longer distances to participate in the event.The study underscores the value of using comprehensive multimodal data to better understand and manage transportation during large-scale events.

Flexible transit systems are a way to address challenges associated with conventional fixed route and fully demand responsive systems. Existing studies indicate that such systems are often planned and designed without established guidelines, and optimization techniques are rarely implemented on actual flexible systems. This study presents a hybrid transit system where the degree of flexibility can vary from a fixed route service (with no flexibility) to a fully flexible transit system. Such a system is expected to be beneficial in areas where the best transit solution lies between the fixed route and fully flexible systems. Continuous approximation techniques are implemented to model and optimize the stop spacing on a fixed route corridor, as well as the boundaries of the flexible region in a corridor. Both user and agency costs are considered in the optimization process. A numerical analysis compares various service areas and demand densities using input variables with magnitudes similar to those of real-world case studies. Sensitivity analysis is performed for service headway, percent of demand served curb-to-curb, and user and agency cost weights in the optimization process. The analytical models are evaluated through simulations. The hybrid system proposed here achieves estimated user benefits of up to 35% when compared with fixed route systems, under different case scenarios. Flexible systems are particularly beneficial for serving corridors with low or uncertain demand. This provides value for corridors with low demand density as well as communities in which transit ridership has dropped significantly because of the COVID-19 pandemic.