transport thursday driving to driverless

Driving to Driverless

Dr. ir. Gonçalo Homem de Almeida Rodriguez Correia(Department of Transport & Planning, TU Delft)[email protected]

Facebook group: Transportation Planning and Analysis (>1250 members)

Challenges and opportunities for research on the impacts of vehicle automation on urban mobility

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Driverless Driving to Driverless

Objective: Understand the research challenges on automated driving regarding its impacts on urban mobility

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DriverlessWhat is automated driving?

SAE International (Society of Automotive Engineers)

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DriverlessIt will take some time …

Source: Diffusion of Automated Vehicles: A quantitative method to model the diffusion of automated vehicles with system dynamics. TIL Master thesis of Jurgen Nieuwenhuijsen. 2015.

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Source: Milakis, D., van Arem, B., van Wee, B. 2015 (work in progress). Implications of automated driving. Delft Infrastructures and Mobility Initiative.

Impacts of automated driving on urban mobility

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DriverlessMobility Impacts Questions

Fully automated

vehicles

More willingness to

travel by car?

Lower car ownership

?

Less trips by car?

More public transport demand?

More or less traffic congestion?

More or less parking demand?

Substitution of private

conventional vehicles for

automated ones?

Used as public transport?

How will these be operated?

Lower Value of Time?

More trips satisfied by each car?

Use shared fleets of vehicles?

Used as public transport?How will these systems be operated?

Wepods.nlFully automated

vehicles




Used as public transport?How will these be operated?

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DriverlessD2D100%EV• The D2D100%EV project

has as its main objective to study how to operate a fleet of autonomous electric vehicles as a feeder to train stations.

• The case study of Delft-Zuid to TUDelft is our reference

• Twizy vehicles are used as an example for that fleet.

• Planning and operational studies are being done.

• A Twizy will be automated.

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DriverlessD2D100%EV: Planning (I)

Source: Liang X., Correia G. and van Arem B. 2015. Optimizing the service area and trip selection of electric automated taxis used for the last mile of train trips. Submitted to the Transportation Research Board meeting.

Mathematical model for the operational area definition and trip selection in an automated taxi system (bookings known in advance)

For a fleet of 5 taxis 15 zones are selected:

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Total requests

Fleet size

Obj.(€/day)

Requests satisfied (Trips)

Requests satisfied

(%)

Total served zones

Electric Taxis

466

5

391.9 269 58% 15

Conventional Taxis 452.5 319 68% 24

Electric Taxis

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518.8 422 91% 31

Conventional Taxis 518.8 422 91% 31

D2D100%EV: Planning (II)

Source: Liang X., Correia G. and van Arem B. 2015. Optimizing the service area and trip selection of electric automated taxis used for the last mile of train trips. Submitted to the Transportation Research Board meeting.

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Source: Arthur Scheltes ongoing master thesis

D2D100%EV: Operation

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Driverless• It is argued that ridding in an

AV will be more pleasurable than a normal car and a normal bus. You will be able to work or just enjoy your time.

D2D100%EV: Value of Travel Time

Trip

segment

Mode Willingness-to-pay per

10 minutes

Main Private car €1.80 - €1.90

Egress Bus/tram/metro €0.55 - €0.65

Egress Bicycle €1.45 - €1.55

Egress Automatic vehicle:

manually driven

€0.85 - €0.95

Egress Automatic vehicle:

automatically driven

€2.25 - €2.35

Willingness-to-pay for different modes per 10 minutes

What?!

Source: Yap M., Correia G. and van Arem B. 2015. Preferences of travellers for using automated vehicles as last mile Public Transport of Multimodal train trips. Under review.

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DriverlessWEpods project

9 km

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DriverlessWEpods project: Challenge

Easymile

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DriverlessWEpods project: Scale up

• Results of an optimization for simulation study (MatLab):

Source: Winter K., Cats O., Correia G. and van Arem B. 2015. Designing an automated demand-responsive transport system: fleet size and performance analysis for the case of a campus-train station service. Submitted to the Transportation Research Board meeting.

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DriverlessWEpods project

Riender Happee, 3ME, TU Delft

Jan Willem van der Wiel, Springer

Use shared fleets of vehicles for all trips?

Car2Go

Fully automated

vehicles

More willing to travel by

car?

Lower car ownership

?

Less trips by car?




Lower Value of Time?

Use shared fleets of vehicles?

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Source: Luis Martinez, analyst at the ITF

International Transport Forum Model• Scale up the concept of public transport with automatic

vehicles:

Taxibots (Shared taxis): till 6 pax and 5 min waiting; or Autovots (Individual carsharing): 5 min waiting as well.

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DriverlessInternational Transport Forum Model

International Transport Forum. 2015. Urban Mobility System Upgrade How shared self-driving cars could change a city. Available online.

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• Simulation takes some hours for representing what happens in a medium scale city like Lisbon, which is not much, however:

These simulation methods do not change travel times as flows change in the network (static travel times).

Moreover TaxiBots routing is not optimized: demand is served using some heuristic that searches for the closest cars.

International Transport Forum Model

More research in needed!

Substitute private conventional vehicles by automated ones?

Fully automated

vehicles

More willing to travel by

car?More or less traffic

congestion?


Substitution of private

conventional vehicles for

automated ones?Lower

Value of Time?

More trips satisfied by each car?

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DriverlessTraffic Assignment + Routing Problem

• A model that assigns family owned automated vehicles to the trips of the household.

• As vehicles are routed in the network traffic congestion is formed, travel times increase.

• Trips not satisfied by the cars are done by Public Transport.

Source: Correia G. and van Arem B. 2015. The Privately Owned Autonomous Vehicles Assignment Problem: a model to assess the impacts of private vehicular automation in urban mobility. Submitted for publication.

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Driverless• Example of how automated vehicles could make a difference

in our household:

Traffic Assignment + Routing Problem

Home

Husband work

Wife work

Husband lunch

6km

4km3km

4km

• Conventional:Driving distance=6+4+3+3+4+6=26 kmsTotal distance inside a car=2*6+4+3+3+4+6*2=38

kms• With the Automated Driving another routing option may

happen:Driving distance=4+4+4+3+3+4+6=28 kmsTotal distance inside a

car=2*4+4+3+3+4+6*2=34kms

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ScenarioGeneralized Cost (euros)

(O.F.)

Trips per vehicle

Absolute delay

(hours)

Delay (% of total driving time)

Car modal

share (%)

Average time inside a car per

trip (min)

Conventional 1,539,100 2.97 110 1.65% 43.6% 19.51

With Automation 1,520,000 3.41 143 1.79% 47.0% 19.46

With Automation and lower

value of travel time

1,267,430 3.70 110 1.08% 53.4% 22.15

++- -+-

+

Source: Correia G. and van Arem B. 2015. The Privately Owned Autonomous Vehicles Assignment Problem: a model to assess the impacts of private vehicular automation in urban mobility. Submitted for publication.

-+

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• Positive: • This approach considers the variations of travel times as

vehicles are routed in the network. • Choice is done in a utility maximizing perspective.

• Negative:• The traffic assignment + Routing problem takes one day

for the city of Delft in order to converge to equilibrium! this is quite slow!

More research in needed!

Driving to DriverlessDr. ir. Gonçalo Homem de Almeida Rodriguez Correia(Department of Transport & Planning, TU Delft)[email protected]

Facebook group: Transportation Planning and Analysis (>1250 members)

Thank you!

transport thursday driving to driverless

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