Post on 28-Jul-2015
Texxi GlobalRed Herring European Top 100 Startups
Conference
Amsterdam, NetherlandsApril 13th - 15th 2015
A New Beginning For Earth's Cities
US20080015923(patent pending since 2006)
Go West Young Man...
An overview of a Largescale Transport Operating System
by Eric MasabaTexxi Global
Crane Dragon
At the time of invention, Texxi and Crane Dragon had no affiliation to any institution. Academic or Corporate.
Texxi was invented by Eric M.W. Masaba in 2004 as a solution to the predicted trifecta of a credit crisis, high oil prices and congestion based on global growth of numbers of both automobiles and human beings.
It was largely a fluke.
The Six PillarsSpatio Temporal Order Matching and Fulfillment
TopologySocial Networks / Credit Contagion
Conformal Mapping
Complex Analysis / Simplex Method
Electricity Markets
Constraints
Genetic Algorithms
NP Hard Problems
Futures Exchanges
Market Makers / Price Discovery
Integrated Battlespaces
ADS-B + Link 16
Texxi GlobalThe New Transport Economy
MissionReform global transport by optimising roadspacetime use in a real-time dynamic fashion
Vision
Apply concepts from the internet and free markets / futures exchanges to transport
Who are our competitors?
Bus monopoliesLarge oligopolistic intercity coach operatorsThe taxi incumbentsMerchant services companies for taxi paymentsCorrupt government officialsSome car manufacturersThe global banks
What problems do we solve?
Congestion Budgetary shortfalls for municipalitiesLow average vehicle occupancyIncreasing urbanisationFuel UseSocial ExclusionHigh Taxi PricesLack of availability of transportDearth of choice
So just how ripe is this opportunity? What do the numbers say ?
$500 billion p.a.
In the USA alone
€223 billion p.a. in both the EU5 and China
Yes, you got it right
$1 TRILLION
That the per annum market for largescale ridesharing in the EU5 alone is worth at least €223 billion and $500bn in the USA alone*
*Assuming $0.05 per mile cost of a seat, that each car travels 16,550 miles p.a. and that each car has 2 seats free. Taxis cost $3.00 / mile.
That a shift to to an occupancy rate of 3.6 or more could take as many as 75% of vehicles
off the road at times of peak congestion
It does turn out that trying to describe a solution to a combinatorial optimisation
problem using genetic algorithms and
heuristics to overcome an apparent bottleneck
in computational complexity theory is really quite a mouthful
TRANSIT EXCHANGE FOR THE XXI CENTURY
Combinatorial Optimisation
Travelling Salesman Problem
Although initially demonstrated in 2005 - 2006 as an exclusively SMS-
based system, the overall concept is to allow any suitable messaging
mechanism communion with the exchange
Did you know that shared travel is the default mode of mechanised transport for most of human history
Did you also know that it is still the norm in most countries of the world even today
Myanmar
Matatu - Nairobi, Kenya
Kampala, Uganda
Dolmus, Turkey
Did you also know that the average car is used for less than one hour a day and carries only one passenger for 90% of trips
Source: Susan Shaheen and Daniel Sperling
Did you also know that the taxi business is the only sector of the transport industry in which customers still regularly post pay for their rides?
Post-Pay: that means you ride first then you pay
Exposing the operator to credit risk
Can you imagine an airline in which that was normal practice?
$1,300 please
And speaking of airlines, did you know that it costs more to
travel per mile in a Hackney cab in London than it did flying to New York
on Concorde ?
And back
2002 Concorde Ticket PricesReturn trip: London - New YorkCost £6,800 (FY2002)Miles: 6,000
Cost per mile: £1.13Heathrow to Central London Cab FareOne Way (1 - 5 people)Miles: 24Cost: £42 - £80Cost per mile: £1.75 - £3.33
Best cost (avg 2 ppl): £1.24
That the cab-ride from central London to Gatwick airport costs more
Than it does to fly to Munich
Yes
Munich!
One way taxi from SE23 to Gatwick Airport: £72.00
The taxi fare one-way can cost more than the return flight + beer
Why is that ?
Could things be any different in the transport business ?
Could things be done any better?
So what's the
big idea?
Enabling strangers to share rides in vehicles on a large-scale
Dynamically - as in "On the fly"
by pre-summoning their ride in a vehicle type of their choosing
with stated preferences for their co-riders and situational ambience
What are you smoking?
Population 73mCars - 28m
Average Occupancy(all modes) - 1.6 Average annual car mileage - 8,430
Average annual # trips per person -960Average distance of trip - 7 miles
Average distance travelled - 6,726 miles
Most of the decline in overall trips rates between 1995/97 and 2010 can be accounted for by a fall in
shopping and visiting friends
Trips by car (as a driver or passenger) accounted for 64% of all trips made and 78% of distance travelled http://assets.dft.gov.uk/statistics/releases/national-travel-survey-2010/nts2010-01.pdf
in 2010
UK National Travel Survey 2010
We have not only proved that dynamic, real-time ridesharing is not only theoretically possible
but have achieved it in practice in real life situations with real paying customers
People used their mobile devices to hail a vehicle for a shared ride and travelled to a common set of destinations together
with wait times (headways) of as
little as 5 minutes
We are thus proposing a whole new way to look at transport systems in urban areas
in order to make use of the "river of empty seats" available in most city vehicle fleets
Liverpool 2006: March - September
Fridays and Saturdays 22:00 - 03:00
135 trips
Ryde, Isle of Wight 2008: July - December
Fridays 22:00 - 03:00
Ryde Taxis 01943 811 111Fleet Size: 200Licence Type: Private Hire:Proprietor: Andrew YounieFinder: Matthew Burden
700 trips
As in on 700 occasions strangers summoned a shared ride in a taxi by mobile phone message
Imagine
Instead of owning a car, could the average person make each of those 960 trips per year by shared vehicle - whether taxi, shared car from a car club, rented car or carpool
UK National Travel Survey (2010)
Cars: 28mAvg Occupancy: 1.6Avg Trip Length: 7 miles# Trips p.a. 960Total Mileage: 6,726
Highest Mode Occupancy: 2.1 (shopping)Lowest Mode Occupancy: 1.2 (commuting)
Could we now have a transport system which behaves more like a
nervous system?
We showed it was possible as far back as 2006
And that the market for this in the USA + EU5 alone
is at least $3,000 billion per annum
Taxi Hailing startups
Carshare / Car rental companies
How it all came about
RAF(1993 - 1995)
RAEng / National Grid(1992 - 2001)
Aeronautical Engineering (Imperial College,UK & ECL,France)(1993 - 1998)
IMDB / Social Networks
Computers / Networking
Investment Banking / Hedge Funds
UK Royal Air Force
While at university I was lucky enough to indulge my passion for aircraft by
flying in an RAF University Air Squadron
University of London Air Squadron
I had some idea of the general operation of integrated air defence
systems and the way that modern battlespaces are set up.
The key thing that separates grouping applications on a transit exchange from all other ride-sharing initiatives before it is the
integration of certain operational concepts
As with joint operations in a modern battlespace, the marketing of the scheme cannot be separated from the messaging and grouping
technology, the futures exchange ideas, the use of a databases of transit intentions, the effect of social networks (which Texxi was
designed from the outset to take into account) nor the ability to represent rideshare matches as nodes in a “searchable battlespace”
Year in Industry Programme Industrial Placement 1992 - 1993
Project to use day-ahead and week ahead weather
predictions to schedule more power loading on
transmission lines
"Central Electricity Research Labs started life as a series of huts
in Surrey
My project was to create a database of overhead lines conductors and their thermal characteristics to link in with the statistical modelling
Using those weather predictions in making line loading decisions
(a type of demand response balancing)
Strict thermal constraints were required to prevent the plastic creep of the power lines over time resulting in electrical discharges to ground
As was proved in that project, rethinking and challenging commonly held assumptions sometimes results in great solutions
An RAEng project in 1995 called
"The Role of Computers in Transportation Technology"
NASA Space Shuttle Trainer at
Marshall Space Flight Centre,
Alabama
During an internship at Swiss Bank Corporation, in 3 weeks, I travelled to;
New York - Atlanta - Huntsville Miami - San Francisco - Los Angeles
To see;Automated highway technology (thanks Kate Bellingham)
ACM SIGGRAPH '95 (thanks Paul Brown, Len Breen and Daniel Brown)
NASA bases (organised by the RAF, MoD and paid for by the Royal Aeronautical Society and the Royal Academy of Engineering)
Structural Matrices (a type of social network for forces)
Genetic Algorithms(a way to "cheat" hard problems by borrowing from Biology )
Wing Design(How solving for a wIng shape is like figuring out the best route)
Complex Analysis / Conformal Mapping(Once you map a problem to another domain, it may no longer look like a problem)
Engineering Mathematics Concepts
Applied mathematics from aeronautics + biology(wing design, complex analysis, genetic algorithms)
This idea is to map a hard problem that seems intractable into a form that you (or someone else) *can* solve
752
975 x 98916 x 17
e.g. | a 2nd Order Linear Differential Equations with constant coefficients
Become simple algebraic expressions once transformed by a Laplace Transform
e.g. | Forced harmonic motion equations with damping
Used to require months and dozens of prototype wings
e.g. | Finding the separation point of airflow over complex wing shapes
then use a Kutta-Joukowksi transform to map the cylinder into the actual shape you want
Start with a 2D cylinder and pretend the flow is inviscid
ERASMUS Scheme for year abroad in Europe
A ridesharing project at Ecole Centrale de Lyon using groupware
The Internet Movie Database(database / social network of actors and films)
Sometime in 1990, an intrepid group of enthusiasts decided to make a comprehensive database of every
film with all its actors and crew listed
What's this got to do with ridesharing?
which was eventually bought by Amazon in 1998
Ever played "6 degrees of Kevin Bacon" ?
To begin with, we had to structure a lot of raw, historical volatility data into a "DataMart" of sorts, which allowed us to find patterns within a dataset
Connectedness + Contagion
Book'em Danno
it occurred to me that some companies would be more connected than others and thus would be like critical nodes in
the case of a bankruptcy
In times of economic stress, where either many companies face similarly challenging conditions or a few very large and well connected companies are at
risk of failing, fatter tails in loss distributions of large loan portfolios are observed.
Recent papers (since 2010) on credit contagion have now empirically confirmed the presence of fat tails in observed loss distributions due to credit defaults from the correlative aspect
of companies in a trading space
The corollary in ridesharing is situations in which a lot of people want transport at the same certain times (rush
hour, concert or sports events, school start and end times, industrial action and inclement weather)
The correlations increase dramatically making finding matches that much easier than would be apparent at first glance
Later in 2004 - 2006, applying further ideas from commerce (the Long Tail by Chris Anderson)
and some subjects from aeronautical engineering (wing design, structural matrices and genetic algorithms), RAF (battlespaces
and integrated air defence)
I became confident that this problem was indeed resolvable in a real, largescale live environment.
The issue at hand is identical to the same problems that agricultural producers experienced in commerce before the adoption of “futures exchanges”
The attitude to ridesharing is one of risk aversion (much like how farmers sought to minimise risk trades with buyers)
Trading will not happen if people cannot have some sort of good knowledge or guarantee of their counterparties
The same is true ridesharing: outside certain special conditions, the matching in both space and time seems
to be unlikely if not impossible
People always say "what is the likelihood of someone doing the exact same trip as me at the same time as me?"
It is actually quite a lot higher than many imagine. However, using a market-maker, we don't need to worry
about that to begin with
The market-maker effectively buys the empty seats from "producers" and holds them until it finds a buyer
Name: Ms Ying LuiWorks: Investment BankStatus: SingleRoute: Woolton - James St.Leaves Home: 6:45amSpare Seats: 3Would share with: Professional Women.
To give the sellers a guarantee that someone will buy at some price and to give customers confidence that they
can always get a ride at an advertised price
3 spare seats (rides) for sale in a convertible for professional women only
This actually happens anyway with buses which drive around empty
It is just that the person paying for those empty seats is a
taxpayer
Whether that taxpayer ever uses the bus or not
We thought this was unfair - a bit like bailing out bankers for bets that went wrong
Why not let a private entity take the risk (and reward) instead?
Ironically, the bandwidth industry also uses “transit exchanges” to link fibre carriers in locales called “peering
points” - think of these as bus stations for data packets
Mode: CommuterA subscription service to enable people to have the same transport options as a private car
Taking customers from lamp-post stops or transit hubs to their homes or offices
Transport solutions for large scale festivals and events, particularly where parking is limited
Mode: Big EventChanging the charging model for destinations
Big EventThe stadium becomes an appliance / app on the road system
Costs such as policing would now be borne by anyone travelling to the stadium
http://www.flickr.com/photos/beggs
CorporateCan become an equaliser
Virtual Private Travel, enabling staff members, executives and their clients to make use of a luxury fleet of coaches to get to work
Corporate
Now even smaller start-up businesses could set-up at business parks and offer their employees the kind of travel perks usually reserved only for corporate behemoths.
Mode: School RunA subscription service to enable people to have their children transported in shared services to schools
School-age children could now share direct transport to and from school in appropriate vehicles
Mode: Evening Economy
Restaurant patrons and restaurant businesses could benefit from cheaper travel, especially where alcohol is involved
Mode: TouristA city as a cruise destination becomes an "app".
Tourists on visits to a city could visit relatively remote destinations; the revenue shared between the broker and the mode licence buyer (the cruise company)
A better, cheaper and faster way to get tourists from the airports into the city centre
Tourist
Shopping
on-the-fly, door-to-mall travel to and from supermarkets. A version of a supermarket bus on-demand.
Soccer Mom Taxi Service (SMOTAS)
Other AppsOnce a system is in place, bespoke creations will be encouraged
A Transit Exchange exists to links all forms of vehicular travel into a free market auction mechanism so that transport can be executed with respect to its true costs
A transit exchange does for vehicle operators and passengers what an
agricultural exchange did for farmers and produce buyers
In the market for dynamic transport it serves, it links supply and demand
The true costs of congestion are rarely factored into the prices of various modes
of transport
Subsidies for certain other travel modes further distort the picture
Why Now?
People + Cars + Resources
Transport accounts for about one quarter of global energy use and energy-related CO2 emissions.
International Energy Agencyhttp://www.iea.org/journalists/fastfacts.asp
In the car crazed USA, the proportion is even higher 75% of oil use and 50% of CO2 emissions.
Transport, Energy and CO2: Moving Towards Sustainability
In the absence of new policies, transport energy use and related CO2 emissions are projected to increase by nearly 50% by 2030 and by more
than 80% by 2050.
76% of commuters in America go to work alone in a private car.
The world’s car fleet is expected to triple by 2050 with 80% of this growth occurring in developing economies.
See "50by50" report from the Global Fuel Economy Initiative (GFEI) for more details. See also the IEA press release.
See "50by50" report from the Global Fuel Economy Initiative (GFEI) for more details. See also the IEA press release.
Increasing urbanisation is rapidly presenting a new and diverse set of
challenges for many cities across the world, most notably the BRICS economies
According to the UN, almost
180,000 people move into cities every day
[UN DESA Report, March 2012 - World Urbanization Prospects The 2011 Revision]Source: http://esa.un.org/unup/pdf/WUP2011_Highlights.pdf
That is 2 people every second
[UN DESA Report, March 2012 - World Urbanization Prospects The 2011 Revision]Source: http://esa.un.org/unup/pdf/WUP2011_Highlights.pdf
There are predicted to be an extra 2.1 billion people living in cities by 2040
[UN DESA Report, March 2012 - World Urbanization Prospects The 2011 Revision]Source: http://esa.un.org/unup/pdf/WUP2011_Highlights.pdf
There are currently 23 megacities in the world with populations over 10 million
[UN DESA Report, March 2012 - World Urbanization Prospects The 2011 Revision]Source: http://esa.un.org/unup/pdf/WUP2011_Highlights.pdf
There will be 36
By
2025
http://www.flickr.com/photos/makalux/4960210708/
[UN DESA Report, March 2012 - World Urbanization Prospects The 2011 Revision]Preparing for China's Urban Billion | McKinsey 2009
Source: [ McKinsey & Co. report, "Preparing for China's urban billion" March 2009 ]
China will have an estimated 8 “mega-cities” (populations of > 10 million) by 2025.
Two of those will have populations of over
20 million.Source: [McKinsey & Co. report, "Preparing for China's urban billion" March 2009 ]
2025
235m
China2025
221 28
1m10m
20m
India2025
There are predicted to be a total of 1.7 billion cars and commercial vehicles on the planet by [2]
2025
Sources: 1. Ward's Auto Report 2009 | World Vehicle Population Tops 1 Billion Units2. International Transportation Forum Transport Outlook 20113. UCDavies ITS | 2 Billion Cars - Transforming Transportation
Taking the total to over 2 billion(but 4bn cars, buses and trucks by 2050)
Building demand in
the "ramp up" perio
d
It takes a certain amount of time to go
from "the ground floor" to a well patronised system
This is the dawn of a new transport paradigm
We are ready to take the plunge in a number of cities
For more details
ops@texxi.com
+44 (0)7986 594 137
https://bit.ly/TexxiGlobal2015