E-bikes\u2019 Effect on Mode and Route Choice: A Case Study of Richmond, VA Bike Share

University Transportation Centers Program2021PDFTech ReportChavis, CelesteMartinez, Vanessa FriasUrban Mobility & Equity CenterMorgan State University. Dept. of Transportation and Urban Infrastructure StudiesUnited States. Department of Transportation. University Transportation Centers (UTC) ProgramUnited States. Department of Transportation. Office of the Assistant Secretary for Research and TechnologyUrban Mobility & Equity CenterVirginiaUnited StatesBicyclesCase studiesCluster analysisElectric vehiclesGlobal Positioning SystemMembership organizationsModal shiftOrigin and destinationRoute choiceVehicle sharinge-BikeBike sharePedal electric cyclesPedelecElectronically power assisted cyclesEPACUMEC-02469A43551747123FinalThe bicycle has become a legitimate transportation option in many cities due to its different benefits. Lower transportation costs, health improvement, and lower emission rates are some critical benefits of a bicycle ride. A large body of research exists on bicycle route choice and travel behavior. There is currently a lack of research on mode shift and route choice changes with the introduction of e-bikes. This study has presented a comprehensive analysis of the similarities and differences between a pedelec and regular bicycle use in Richmond City, Virginia, as well as an evaluation of how membership type and other user characteristics might influence bike share use. This study utilized global positioning system (GPS) data for a docked bike-share system in Richmond, Virginia, from March 2019, when RVA Bike Share began converting the traditional bikes to e-bikes. To retrieve the data this study used Mapbox\u2019s Map Matching API, which snaps fuzzy, inaccurate GPS traces to actual segments in the road network, breaks the snapped roads into segments and queries each segment in Open Street Maps (OSM) to identify the type of road. This study did a comprehensive descriptive analysis, origin-destination trip analysis, and user cluster analysis with the retrieved data. The results have shown that pedelecs are generally associated with longer trip distances, shorter trip times, higher speeds and lower elevations. In April, about 25% of the fleet was pedelec bikes and by December, approximately 65%. The t-tests results showed that the mean number of trips made per bike available was significantly more (~3.2x) for pedelecs compared to bikes (p-value=0.004). The origin-destination analysis considered the business, mixed use, residential and other uses and observed that the plots show extremely similar trends with a large number of trips staying within either business or residential locations or mixed use. The roadway use analysis and mapping showed that pedelecs were used farther outside of the city than bikes. Additionally, pedelecs were frequently used in the downtown core where most RVA bike share stations are located. In terms of memberships, longer-term memberships (annual, monthly) were found to be associated with significantly higher use of pedelecs than shorter-term memberships, potentially pointing to a lack of knowledge on the part of those who use the system less frequently or to a preference for normal bicycles. Finally, the user cluster analysis identified six diverse types of behaviors that varied by geographical region (e.g., central Richmond vs. recreational areas), as well as by trip distance, trip duration, and bike type.125