TU Delft

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to. Driverless. What is automated driving? ... Source: Liang X., Correia G. and van Arem B. 2015. ... of electric automated taxis used for the last mile of train trips. ... automatically driven .... ➢Total distance inside a car=2*6+4+3+3+4+6*2=38 kms.
Driving to Driverless Challenges and opportunities for research on the impacts of vehicle automation on urban mobility

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

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

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Driving to Driverless

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

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What is automated driving?

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SAE International (Society of Automotive Engineers)

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It will take some time …

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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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Impacts of automated driving on urban mobility

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

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Mobility Impacts Questions More trips satisfied by each car?

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Substitution of private conventional vehicles for automated ones?

Fully automated vehicles

Use shared fleets of vehicles?

More willingness to travel by car? Lower Value of Time?

Lower car ownership?

More or less traffic congestion?

More or less parking demand?

Less trips by car? More public transport demand?

Used as public transport? How will these be operated?

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

More or less traffic congestion?

Fully automated vehicles

More or less parking demand? Wepods.nl

More public transport demand?

Used as public transport? How will these be operated?

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D2D100%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 DelftZuid 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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D2D100%EV: Planning (I) 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:

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.

Driving to Driverless

D2D100%EV: Planning (II)

10 Total Fleet Obj. requests size (€/day)

Electric Taxis 5

Conventional Taxis Electric Taxis Conventional Taxis

466 10

Requests Requests Total satisfied satisfied served (Trips) (%) zones

391.9

269

58%

15

452.5

319

68%

24

518.8

422

91%

31

518.8

422

91%

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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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D2D100%EV: Operation

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Source: Arthur Scheltes ongoing master thesis

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D2D100%EV: Value of Travel Time • 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.

Willingness-to-pay for different modes per 10 minutes

Trip

segment

Mode

Willingness-to-pay

10 minutes

What?!

Main

Private car

€1.80 - €1.90

Egress

Bus/tram/metro

€0.55 - €0.65

Egress

Bicycle

€1.45 - €1.55

Egress

Automatic

vehicle: €0.85 - €0.95

manually driven

Egress

Automatic

vehicle: €2.25 - €2.35

automatically driven

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.

per

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WEpods project

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9 km

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WEpods project: Challenge

14 Easymile

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WEpods 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 demandresponsive transport system: fleet size and performance analysis for the case of a campus-train station service. Submitted to the Transportation Research Board meeting.

Driving to Driverless

WEpods project

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Riender Happee, 3ME, TU Delft

Jan Willem van der Wiel, Springer

More willing to travel by car?

Fully automated vehicles

Use shared fleets of vehicles?

More or less traffic congestion?

Lower Value of Time?

Lower car ownership?

More or less parking demand?

Less trips by car? More public transport demand?

Use shared fleets of vehicles for all trips?

Car2Go

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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.

Source: Luis Martinez, analyst at the ITF

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International Transport Forum Model

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

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International Transport Forum Model • 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.

More research in needed!

More trips satisfied by each car? Substitution of private conventional vehicles for automated ones?

More willing to travel by car?

Lower Value of Time? Fully automated vehicles

More or less traffic congestion? More or less parking demand?

Substitute private conventional vehicles by automated ones?

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Traffic 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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Traffic Assignment + Routing Problem • Example of how automated vehicles could make a difference in our household: 3km

Husband work

Husband lunch

4km 4km Home

Wife work

6km

• Conventional:  Driving distance=6+4+3+3+4+6=26 kms  Total 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 kms  Total distance inside a car=2*4+4+3+3+4+6*2=34kms

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Traffic Assignment + Routing Problem

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Traffic Assignment + Routing Problem

25 Scenario

Generalized 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

47.0%

19.46

With Automation With Automation and lower value of travel time

1,520,000

1,267,430

-

3.41

+ + 143 1.79%

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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Traffic Assignment + Routing Problem

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

Thank you!

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