Multiple Passenger Ridesharing

Changes the Economics of CommutingProvides both low price and short travel times, along

with greener transport

Jeffrey Funk

Division of Engineering and Technology Management

National University of Singapore

Traditional Approaches to Transport

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

City Percentage Devoted to

Streets

Street Area (square feet) Per

CapitaNew 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 StreetsSource: John R. Meyer and Jose A. Gomez-Ibanez, Autos, Transit, and Cities, Twentieth Century Fund

Report (Cambridge: Harvard University Press, 1981).

Rank City Parking Area* 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 AreasSource: 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

This is the Reality 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?

There is a Better 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

Very Different from Uber 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

Advantages of Multiple Passenger 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

Singapore’s Taxis are Concentrated in a Few Places (bright

red) Throughout a Typical Day (this data is for Sunday)

Midnight3AM 6AM

9AM

Noon 3PM6PM

9PM

How Much Space Does 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

Taxis are Operating on 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

Travel Time

Price

Multiple Passenger Ride Sharing can Change the

Economics of Commuting

Private vehicle

or private taxi

Multiple

passenger

ride sharingPublic

TransportBEST: want

low price,

short time

Design Services that Better 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)

Such Private Bus/Car Mobile 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 algorithmhttp://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/

Fixed Route Services Can 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

Fixed of Fixed Route 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

RidePal

It offers a number 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/#/

Chariot Runs 14 passenger 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

Examples of Possible Services 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

Many other Examples in 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

What About Other Transport 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

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50

100

150

200

250

0 5 10 15 20

Relative Traffic On All Roads, Great Britain, by Time of Day

Ride sharingcars canalso servicehigh off-peak demand

May be lots of potential during non-peak times

Ride sharing cars and vans can be usedfor other transport applications duringmiddle of day,when there is lesscommuting

We need better info onstarting and ending pointsduring non-peak hours

PeakCommutingTimes

Challenge is to Find 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

Other Types of Data? (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

Other Types of Data? (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?

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?

Multiple Passenger

Ride Sharing can

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

Conventional Wisdom About Lower 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

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20

40

60

80

100

0 50 100 150 200 250 300 350

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

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5

10

15

20

25

30

0 5 10 15 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

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

Centralized Cities/Rail Lines

(with multiple centers emerging)

Some cities have multiple centers,

particularly in the U.S. where growth

has occurred in the South-West

(California, Texas, Arizona) and FloridaMultiple Centers

Multiple Passenger Ride Sharing 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

Conclusions

Multiple passenger ride 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

Conclusions (2)

Not just 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

Conclusions (3)

Even Los 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