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Possible Bike S haring P rograms in UCLA Given the Arriving Purple Line Subway

Possible Bike S haring P rograms in UCLA Given the Arriving Purple Line Subway. Tsai- wei Wen Department of Public Policy. Introduction. The future purple line extension subway could increase the public transit usage

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Possible Bike S haring P rograms in UCLA Given the Arriving Purple Line Subway

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  1. Possible Bike Sharing Programs in UCLAGiven the Arriving Purple Line Subway Tsai-weiWen Department of Public Policy

  2. Introduction • The future purple line extension subway could increase the public transit usage • However, there exists the “Last mile problem”, people don’t have incentive to work more than 10 minutes(0.5 mile) to catch the subway • If find a solution to solve the “Last mile problem”, more people will have higher willingness to use public transit rather than driving. • How to solve? BICYCLEs

  3. The Bike Sharing System The public rental bike system • Rent a bike for short one-way trip • How it works? • Register with your smart card transit pass at the bike station • Swipe the smart card on the lock • Ride the bike and return it at any bike station • Program in Paris, London, Barcelona, Washington, D.C. • Purpose- • Intermodal transportation • Solve the last-mile problem • Easy way to transit in the city center

  4. Case Study---- The UCLA Station • The possible station location: Wilshire/Gayley, • 14,300 people are expected to board each day • Riders from: UCLA, UCLA Medical Center, High-rise offices around, Federal Building

  5. From UCLA station to campus • 3/4 mile walk to Ackerman Plaza • 1 mile to Royce Hall • More than 1 mile to Northern campus. For example: School of Public Affair • By bus: BBB1,2,8,12, Metro761 • Bus frequency: every 2-5 minutes • 5 Minutes on bus • By Bruin Bus • Bus frequency: every 8-10 minutes • 5 Minutes on bus • Biking: 1.5 miles, 6-10 minutes (15mph) • Walking: 1.5 miles, 30 minutes (3mph)

  6. The UCLA Subway Station--- • Future Potential User: People who work and live there • 0.5 mile: • 5 minswalking • 1.5 miles: • 30 mins walking VS. • 8-10 mins Biking • (Walk: 3mph; Bike:15mph) The bike sharing system could attract people who live 2 mile away from the station, and increase the usage of the public transit

  7. If

  8. The Hot spot Analysis • Distances from Station • Score increases in the 2 miles buffer and decrease outside the 2 miles buffer, locations which is 2 miles away from the station have the highest score • Population in the study area • Number of workers in the study area • Number of public transit users • Darker color indicates better place to set a bike station

  9. The Service Area Analysis • Walk Distances From UCLA Station • Less than Half UCLA building can be reached in 15 Minutes Walking Distances • Serious last mile problem

  10. The Service Area Analysis • Biking Distances From UCLA Station • Bicycle could be a good way to solve the “Last Mile Problem” • The Whole UCLA campus could be reached in 10 minutes biking distances (assume biking speed is 15 mph)

  11. Find the Routes for Bicycle

  12. Where to set the Bike Stations on Campus? • Need space to set the stations • Possible Space area on Campus: The Parking Structure and Bus Terminal • Walking Distance to the Main Buildings

  13. Where to set the Bike Stations on Campus? • Short Biking Distance between Stations---3 minutes • Almost every main buildings could be reached in 3 minutes by bike

  14. No Service Area • No bike friendly road (e.g. Ladders) • Data not available---no data for small path

  15. Conclusion • Bicycle population should increase if there is a UCLA subway station on Wilshire • The bike facility/bike path still not enough in UCLA (especially in north campus) • Space for bike stations: the existing parking structure could be solutions • The concerns about public bike sharing system: • Where to find money to build? • Need bike paths through the UCLA campus

  16. GIS Skills • Modeling: Create the different distances buffer • Original data: The UCLA building locate The Future UCLA station locate • Analysis: Buffer Analysis • Extracting information from a buffer • Charts (extract data and create the table) • Hotspot Analysis • Network Analysis (find the bike route and bike station service area)

  17. Appendix----Model and Metadata Metadata Screen Shot Model Screen Shot

  18. Thank You Q &A?

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