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Multiple Passenger Ride Sharing Changes Economics of Commuting
Multiple passenger ridesharing offers a solution to the economic challenges of commuting by providing lower costs and shorter travel times, while also reducing congestion and environmental impact. By leveraging information technology and big data, ridesharing can optimize routes based on actual demand, potentially revolutionizing urban transport beyond high-density cities. Successful implementation of such services could lead to reduced car ownership, lower transportation costs for families, and decreased energy consumption.
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Multiple Passenger Ride Sharing Changes Economics of Commuting
- 1. Multiple Passenger Ridesharing Changesthe Economics of Commuting Provides both low price and short travel times, along with greener transport Jeffrey Funk Division of Engineering and Technology Management National University of Singapore
- 2. Traditional Approaches toTransport Private Cars Advantage: Lots of freedom! Usually fast speeds and short travel times Disadvantages: cars are expensive, cities are filled with roads and parking lots, much lost time in traffic during many parts of day Public transportation Advantage: Inexpensive Disadvantages: travel times are usually much longer than for private cars or taxis almost double those of private cars and taxis in Singapore
- 3. City Percentage Devotedto Streets Street Area (square feet) Per Capita New York 30% 345 Newark 16% 257 San Francisco 26% 441 Chicago 24% 424 Philadelphia 19% 365 St. Louis 25% 609 Pittsburgh 18% 455 Cleveland 17% 416 Miami 24% 778 Milwaukee 20% 724 Cincinnati 13% 573 Los Angeles 14% 741 Atlanta 15% 1,120 Houston 13% 1.585 Dallas 13% 1,575 Portion of Land Devoted to Streets Source: John R. Meyer and Jose A. Gomez-Ibanez, Autos, Transit, and Cities, Twentieth Century Fund Report (Cambridge: Harvard University Press, 1981).
- 4. Rank City ParkingArea* Divided by Land Area 1 Los Angeles 81% 2 Melbourne 76% 3 Adelaide 73% 4 Houston 57% 5 Detroit 56% 6 Washington, D.C. 54% 7 Brisbane 52% 8 Calgary 47% 9 Portland 46% 10 Brussels 45% Land for Parking in Urban Areas Source: Michael Manville and Donald Shoup, “People, Parking, and Cities,” Journal of Urban Planning and Development, Vol. 131, No. 4, December 2005, pp. 233-245 * Includes all levels of all parking garages
- 5. This is theReality of Many Cities Cars, cars, and more cars Private cars are primary mode of transportation in most developed countries Particularly in U.S. But also in Japan and Europe They are parked 95% of the time When they are driven, they usually have a single driver and are stuck in traffic Waste of time! And also energy Isn’t there a better way?
- 6. There is aBetter Way: Multiple Passenger Ride Sharing It combines the best of Short travel times (similar to private vehicles) Low cost, fewer private cars less congestion (similar to public transport) How can it do this? Many people have same starting and ending points, and times Entrepreneurs can offer services for high-density routes and times Information Technology enables us to do this Big data provides better data on common routes and times Smart phones enable interactions between riders and services GPS and fast computers enable vehicles to have very complex routes
- 7. Very Different fromUber Pool or Crowdsourcing Entrepreneurs must take the risks They must guarantee short travel times and low prices Uber Pool has twice the travel times as Uber’s single passenger services People want short travel times! Demand won’t emerge in the short run for Uber Pool! Entrepreneurs must offer services for specific times and routes Even if there is initially low demand
- 8. Advantages of MultiplePassenger Ride Sharing Provides another choice for users Depends more on entrepreneurs than on governments If successful, Reduces cost of transport, with only small increase in travel time Increases income for drivers, good for them and economy Reduces congestion and thus travel times for everyone Reduces petroleum usage and air pollution, without expensive subsidies for electric vehicles, solar cells, or wind turbines Can reduce need for car ownership, which represent second highest cost for most low and mid-income families after homes Less car ownership means less need for parking lots and roads
- 9. Singapore’s Taxis areConcentrated in a Few Places (bright red) Throughout a Typical Day (this data is for Sunday) Midnight 3AM 6AM 9AM Noon 3PM 6PM 9PM
- 10. How Much SpaceDoes Bright Red Occupy? 1% of Space? Two Major Areas/Routes for Most of the Day (Green Boxes) Midnight 3AM 6AM 9AM Noon 3PM 6PM 9PM
- 11. Taxis are Operatingon Same Routes at the Same Time These taxis can be shared with little increase in travel time One main route along east coast A second route from south central to central Simple calculation for Singapore 28,000 taxis or 39 taxis per km2 (total area of 710 km2 ) If taxis are operating in 1% of area: 3,900 taxis per km2 So many chances for shared taxis Singapore is not unique! Similar situations probably exist in many cities
- 12. Travel Time Price Multiple PassengerRide Sharing can Change the Economics of Commuting Private vehicle or private taxi Multiple passenger ride sharing Public TransportBEST: want low price, short time
- 13. Design Services thatBetter Match Real Demand Use big data to understand People’s actual starting and ending points by time of day Provide direct services for high density routes and times Fewer stops reduce travel times, thus increasing user value Increase number of vehicles if demand emerges Vehicles follow multiple routes during day, facilitated by GPS Real densities and demand should determine fixed routes Vans and cars follow demand as it changes from commuting to shopping during middle of day and back to commuting in evening During non-peak commuting times, vehicles can also be used for other transport needs, such as deliveries (see below)
- 14. Such Private Bus/CarMobile Apps are Emerging Many transportation apps are emerging Mostly private taxis Uber, Didi Dache-Kuaidi Dache, Ola Cabs, Lyft, Grabtaxi All are valued at >$1Billion, Uber >$50 Billion Some transport multiple passengers in same vehicle Uber Pool, LyftLine, Via (in NY) and Split Driver receives requests via real-time routing algorithm, which maps pickups and drop-offs into most efficient route Problems is most services have long travel times, because there aren’t enough people using the services Most people want to plan their routes, not depend on dynamic algorithm http://bits.blogs.nytimes.com/category/special-section/?_r=1 http://districtsource.com/2015/05/split-a-new-ridesharing-app-is-out-to-shake-up-d-c-s-on-demand-transportation-scene/
- 15. Fixed Route ServicesCan Have Bigger Effect Fixed route services transfer risk from passenger to service Services must provide short travel times (and low prices) through small number of stops, perhaps one or two at each end Dynamic services will not provide short travel times until the number of users is high Fixed route services can provide shorter travel times Initially number of passengers may be small and thus service might lose money Depends on choice of routes Services must target routes with high densities of users
- 16. Fixed of FixedRoute Services are Emerging Examples San Francisco area: RidePal, Chariot, Split, Potrero, Richmond, Loup, Sunset Bridj in Boston and Washington Services make multiple stops only at beginning and end of route Since no need to access car from parking garage, travel times almost as fast as private vehicles, but can be much cheaper The challenge is to find starting and ending points with lots of demand; Big Data analysis will help Most current services based on crude observations, not real data Better data on starting and ending points will lead to better services http://bits.blogs.nytimes.com/category/special-section/?_r=1; http://www.bridj.com/welcome/#how http://www.theverge.com/2015/3/23/8279715/san-francisco-bus-leap-loup-chariot
- 17. RidePal It offers anumber of fixed route services that connect starting and ending points with high demand Picture shows SF and Sunnyvale Also provides services for specific companies (they know addresses of their employees) https://www.ridepal.com/#/
- 18. Chariot Runs 14passenger vans across San Francisco on five set routes during morning and afternoon rush Rides cost between $3 and $5 Passengers book from smartphones and use mobile phone apps to monitor van location Free WiFi also available Total of 5,000 rides provided each week Introduced tool to determine new routes, “Roll your Route” Users can submit their optimum bus route and commute times Can then recruit friends and neighbors to vote for the route If route meets certain threshold, the service starts within a week http://www.bloomberg.com/news/articles/2015-04-22/silicon-valley-private-bus-service-chariot-gets-more-vc-funding
- 19. Examples of PossibleServices in Singapore Consider NUS (National University of Singapore) night classes 500 to 1000 students attend classes on weeknights (6-9PM) in Faculty of Engineering Probably similar numbers in other faculties and universities Some of these students are coming from the same place about 6PM going to the same place at about 9PM Can we offer cars, vans or mini-buses for them? Thus reducing use of single passenger private vehicles travel time for students who typically use public transportation The more we know about starting and ending points by time of day, better services can be offered
- 20. Many other Examplesin Singapore and Other Places Any location with many low- and mid-income people is one end point Low price retail outlets Popular shopping malls Popular weekend destinations: beaches, parks, theme parks Schools, universities, and government offices Entrepreneurs can connect these end points with residential locations that are close and are densely populated Learn from results, expanding successful routes and reducing unsuccessful routes Data base will improve over time
- 21. What About OtherTransport Demands Ride sharing vehicles/vans are wasted when they are parked Are there transportation demands during non-peak hours, such as 10AM to 4PM? Can vehicles and vans be used for other types of transport services? Use them for deliveries and other applications? Uber wants to do other applications, why can’t others? Many store-owned vehicles sit 90% of the time The following slide suggests there is large demand for transport in non-peak hours Understanding the demand through big data is essential
- 22. 0 50 100 150 200 250 0 5 1015 20 Relative Traffic On All Roads, Great Britain, by Time of Day Ride sharing cars can also service high off-peak demand May be lots of potential during non-peak times Ride sharing cars and vans can be used for other transport applications during middle of day, when there is less commuting We need better info on starting and ending points during non-peak hours Peak Commuting Times
- 23. Challenge is toFind High Density Routes Taxi companies have good data, because pick-up and drop-off points are often close to user starting and ending points Same with Waze, a community-based traffic and navigation app (acquired by Google) Train and bus companies also have data on boarding and alighting points but, these points may be far from actual user starting and ending points Ride sharing companies are collecting data and will likely guard it closely Employers and governments also have data for specific people on residential employment locations
- 24. Other Types ofData? (1) Residential Retail Total Densities Employment Employment http://simulacra.blogs.casa.ucl.ac.uk/2011/04/running-spatial-interaction-models-in-java/ Employment, residential, and shopping densities are known in many cities Can this data can be used to build a rough map of high density routes and times? Many trips are between: Employment centers Retail centers Residential centers Entertainment centers
- 25. Other Types ofData? (2) Can this rough map be used to devise a travel model for a city? Can we assume travel times for work and shopping activities? Would time-of day road, train, bus, and taxi usage data or retail data provide a better model? Can this model help us devise ride sharing routes and schedules? Can simulations help us identify the best combinations of routes and best schedules? Where should vehicles stop and at which times?
- 26. Can Employers Help? For example, should employers provide anonymous data on home addresses to help design transport services for them? Well designed services could dramatically cut travel times for users increase employee satisfaction reduce traffic on trains during peak demand Should governments require employers to provide data, in order to reduce peak demand traffic on trains?
- 27. Multiple Passenger Ride Sharingcan Change Conventional Wisdom about Energy Usage: High urban densities (and centralized cities) are needed for low energy consumption in transport Newman P, Kenworthy J 1989. Cities and automobile dependence : a sourcebook. Aldershot Hants England: Gower Technica
- 28. Conventional Wisdom AboutLower Energy Usage High urban densities are necessary for low energy usage Shorter distances to travel More walking and bicycling in dense than in less dense cities Vehicle, bus, and train trips are shorter More public transportation partly because better economics of public transportation Both lead to lower energy usage in transportation Examples of extremes Long car commutes in Los Angeles Short bus or train commutes in Hong Kong
- 29. 0 20 40 60 80 100 0 50 100150 200 250 300 350 Asia Canada Australia US Public Transport (%) Density (per hectare) Public Transport Usage (%) is Higher in Dense Cities (Asia, Canada, Australia, US) Newman P, Kenworthy J 1989. Cities and automobile dependence : a sourcebook. Aldershot Hants England: Gower Technica
- 30. 0 5 10 15 20 25 30 0 5 1015 20 25 30 A More Detailed Look at Canada, Australia, and US New US Cities Decentralized Designed for Cars Old US Cities Australia Canada Density (per hectare) Public Transport
- 31. Why the Differences? Public Transportation tends to be more economic when Population is large, population density is high Cities are designed around walking (and not cars) Cities are centralized and commuting is one direction (e.g., Tokyo) Public Transportation is often designed for centralized one direction commuting during peak hours Easy to design; just bring people downtown for work and then back home Train and bus routes are fixed, repeat same routes Routes are repeated with only changes in frequency of service by time of day
- 32. Centralized Cities/Rail Lines (withmultiple centers emerging)
- 33. Some cities havemultiple centers, particularly in the U.S. where growth has occurred in the South-West (California, Texas, Arizona) and Florida Multiple Centers
- 34. Multiple Passenger RideSharing Will Overturn this Conventional Wisdom Can increase the number of passengers per vehicle and thus reduce energy usage Even lightly congested cities can do multiple passenger ride sharing First find high density routes and times and offer services Then work towards lower density routes and times and offer services The end result can be lower energy usage along with Lower cost and time of transport Less congestion and thus travel times for everyone Lower car ownership, which represent second highest expenditure for most low and mid-income families after homes Less car ownership means less need for parking lots and roads
- 35. Conclusions Multiple passengerride sharing can change the economics of transport How can it do this? Many people have same starting and ending points, and same times We just need to identify those routes and times Information Technology enables us to do this Big data provides better data on common routes and times Smart phones enable interactions between riders and services GPS and fast computers enable vehicles to have very complex routes
- 36. Conclusions (2) Notjust Singapore and other high density populated cities! Smaller and less dense cities can also do this Cities should provide more data, to help services identify common routes Cities have data, so they can help Much cheaper than building train lines and buying buses
- 37. Conclusions (3) EvenLos Angeles can do this Cars, mini-buses and vans are used for high demand routes Big data can find these routes and times This will cause users to depend more on ride sharing, reducing private vehicle usage and ownership Can we reduce number of vehicles on roads by more than half during peak hours? Can we reduce the number of cars per family from two to one? Can Los Angeles have lower energy usage than Tokyo currently does? Perhaps, because no empty trains and buses running in opposite directions And fewer empty trains and buses during off-peak hours Instead, many full ride sharing vans and mini-buses