Abstract Manager

Shared micro-mobility services such as shared e-bike sand e-scooters are increasingly becoming popular mode of transportation in urban areas, largely due to their low-cost, convenience, fuel savings, environmental benefits and so on. Many cities and transit agencies are investing in deploying micro-mobility services as a way to combat climate change. In fact, transportation planning is no longer limited to mobility and accessibility; rather the paradigm of sustainability is equally valued. Although these micro-mobility modes are growing in popularity, their inclusion in travel demand models has not occurred to any significant extent. For effective transport planning, it is quintessential to integrate micro-mobility options into transport simulation models. The study integrates micro-mobility service options as travel modes within a travel demand forecasting model and use the model to test alternative scenarios and their potential benefits on the environment. A multimodal travel forecasting model has been developed for the Central Okanagan region of British Columbia, Canada. The existing model includes the following travel modes: car, transit, walk, and bike, which has been updated in this study to include shared micro-mobility options as travel modes. In this region, shared e-bikes and e-scooters are operational. This updating procedure includes the use of shared mobility users survey data as well as usage data from the service providers. Demand model has been utilized to predict the spatio-temporal distribution of trip origin and destination for the currently operational micro-mobility services. Following the updating of the travel mode, alternative scenarios such as increased use of micro-mobility services for work travel and transit access will be tested and understanding on congestion and emissions reductions will be developed. Findings of this study will provide insights to policy makers on how shared mobility service deployment can assist in achieving emissions reduction target.