Browsing by Author "Baek, Kwangho"

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    MnDOT's Mobility-as-a-Service Platform: Assessing User Behavior and Measuring System's Benefits
    (Center for Transportation Studies, University of Minnesota, 2024-06) Baek, Kwangho; DeBruin, Hannah; Khani, Alireza; McFadden, Elliott
    A Mobility-as-a-Service (MaaS) platform was implemented in Southern Minnesota to streamline transit use and promote rural transit use, incorporating features like interactive trip planning and mobile payment. The project commenced with an area analysis, followed by a literature review highlighting MaaS's potential benefits for rural regions. Pre-deployment ridership data analysis revealed the impact of COVID-19 and seasonal variations on mid- and long-term ridership trends. Analysis of reservation and ride data provided insights into transit use patterns and user/operator experiences, informing areas for improvement through MaaS deployment. The post-deployment analysis employed a time series model to estimate MaaS's impact on ridership, showing a notable average monthly increase of 4.2% for demand-responsive transit (DRT) and paratransit services over nine months, compared to a marginal 0.2% rise in the control group. In addition, a before-and-after study of trip location data demonstrated MaaS's efficacy in boosting transit service rates in areas with socioeconomically disadvantaged populations, underscoring its equity-driven effectiveness.
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    Southern Minnesota Rural Transit Origin, Destination, and Reservation Data (The ODR Data)
    (2024-06-27) Khani, Alireza; Baek, Kwangho; baek0040@umn.edu; Baek, Kwangho; University of Minnesota Transit Lab
    The ODR data provides detailed observations of six Southern Minnesota Transit Agencies' trip reservations and actual trips over two one-week periods, spanning both pre- and post-MaaS deployment phases. The collected features for the reservation-based services — demand-responsive transits, some ADA paratransits, and route deviations — included the following: date and time of phone call (ride requests) received or reservation reception time (RRT or call-in time), the request’s intended trip date, preferred departure time (PDT), scheduled departure time (SDT), actual pick-up time (APT), actual drop-off time (ADT), origin & destination (OD), fare type (cash, token, etc.), service type (paratransit, student, etc.), and some information on trip cancellations. On the other hand, the collected features for the fixed route buses include the number of boarding and alighting activities for each bus stop and the inferred timestamps. Some measures were taken to mask sensitive information.
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    Transfer Behavior and Off-Peak Commutes
    (Center for Transportation Studies, University of Minnesota, 2024-10) Baek, Kwangho; Khani, Alireza
    To improve transit service for off-peak travelers, an essential yet often underrepresented group, and promote social equity, this study examines off-peak transit commutes and transfers, with a focus on the transitway system in the Twin Cities. The research contrasts off-peak and peak travel behaviors using an onboard survey (OBS) from 2016 and automatic fare collection (AFC) data from 2018 to 2023. The initial analysis involved clustering trips from OBS into 16 regional zones and creating origin-destination matrices to explore spatial travel patterns. Key findings include longer peak-time trips (8.51 miles) compared to off-peak trips (5.74 miles) and a higher concentration of non-work trips during off-peak times. The study also reveals that off-peak trips are more dispersed geographically. In the second phase, path choice sets were generated for each respondent from OBS, and logistic regression models were used to analyze preferences for transitway versus bus-only routes. The results indicated a strong preference for transitways, with 60% of passengers opting for them over buses when travel times were equal. Finally, AFC data was integrated with OBS using machine learning techniques to examine long-term trends, including the impact of the COVID-19 pandemic. Post-pandemic data show an increase in off-peak commutes and transit trips with transfers despite an overall decline in transfers. This study provides insights into evolving transit usage behaviors and highlights the importance of the transitway system in facilitating efficient travel.