Auto tomatio tion in in urban ban pub ublic tr transp sport - - PowerPoint PPT Presentation

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Auto tomatio tion in in urban ban pub ublic tr transp sport - - PowerPoint PPT Presentation

Auto tomatio tion in in urban ban pub ublic tr transp sport sys t system ems; s; The way forward to create better and more liveable cities; A Rotterdam case study ETC 2 201 018 8 - Dub Dublin lin Cont ntent nts The need


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Auto tomatio tion in in urban ban pub ublic tr transp sport sys t system ems; s;

The way forward to create better and more liveable cities; A Rotterdam case study

ETC 2 201 018 8 - Dub Dublin lin

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SLIDE 2

Cont ntent nts

  • The need

eed fo for inno nnovati tion in urban public transport systems

  • Myth: sel

self driv rivin ing ca cars rs will make urban public transport redundant

  • The concept of driv

riverle rless pu publ blic tr trans nspo port

  • State of the art
  • The potential of PT to embrace automation
  • A Rott

tterda dam case study

  • Pote

tent ntial impa mpacts ts on cities; policy goals

  • Driverless metro
  • Driverless shuttles
  • Conclusions & recommendations
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Thr hree ee autho uthors; ; two wo orga gani niza zati tions ns

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The he need need fo for inno nnovati tion in n ur urba ban publ public tr trans nspo port

1. 1.

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Gr Growth th of

  • f cit

citie ies; W ; Wor

  • rldwi

wide

  • Cities are expected to keep growing the next 30 years
  • Currently 55% of world population in cities
  • 68% of the world population in cities by 2050 (UN)
  • Increasing demand for mobility
  • Cha

halle leng nges: s:

  • Capacity
  • Sustainability
  • Accesibility
  • Liveability
  • Scarcity of resources
  • Driverless vehicles
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SLIDE 6
  • Innovation by leaps; often related to duration of the public concession
  • Typically occurs once every 10-20 years
  • Let’s see innovation as a way to counterpart the urban challenges:
  • Becoming CO2 neutral before 2025 (emi

emissionl nles ess)

  • Reducing (the costs of) assets (wirel

eles ess)

  • Increasing capacity and efficiency by automation (driv

driverle rless)

  • Providing personalized journeys in order to become more attractive (seaml

amles ess)

Inno nnovati tion n in ( n (ur urba ban) publ public tr trans nspo port

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My Myth: : Sel Self drivin riving cars cars wi will ma make e publ public tr trans nspo port t redunda edundant

2. 2.

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Devel elopmen pment o t of the the sel elf drivin riving car car

  • 5 levels of automation
  • New business models arise
  • Often seen as the most disrupting innovation in a long while
  • Private vs. shared
  • Pilots/applications (mainly) technology driven
  • Foreseen advantages:
  • Mobility for all (anywhere, anytime)
  • Increase of Value of time
  • Solving congestion
  • Increasing capacity on highways
  • Increasing urban sprawl

?

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Cha hallenges enges of

  • f driv

riverle rless cars cars fo for a a cit city

Main in cha halle leng nges:

  • Complex inner cities (interaction and infrastructure)
  • Ethical dillema’s (responsibility)
  • Safety dilemma (separated vs. mixed)
  • (When) Will we ever get to level 5 automation?
  • Competition with healty modes (walking / cycling / PT)
  • Large spatial footprint compared to PT
  • Extra inner city movements

So So, is is this his what at yo you wan ant as as a a cit ity?

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Driv riverle rless publ public tr trans nspo port

3.

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“Driverless PT is a form of PT which can be operated without the required presence of a driver or attendant in the vehicle.”

  • Sounds like future music but part of it is already there!
  • New routing/service options (e.g. dynamic in stead of fixed)
  • A higher capacity
  • Supply and demand coordination (e.g. platooning)
  • Reduction of operational costs
  • Improved financial viability
  • Efficient operation and fleet management
  • Passenger oriented services

Driv riverle rless Publ ublic T Trans nspo port

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Tr Train ( (capac apacity driven): ):

  • Implementation of ERTMS
  • First pilots are taking place

Me Metr tro ( (capac apacity driven): ):

  • Already driverless for a long time
  • Nearly all new metro’s are driverless

Tram am ( (fi finan ancial al effec ecti tivi vity driven): ):

  • Driver assistance systems already exist
  • First full driverless tram pilot @ InnoTrans 2018

Stat ate of

  • f the

the Ar Art (1 (1/2)

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Bus us ( (fina inanc ncia ially ly drive ven): ):

  • No fully automated bus is available yet
  • First pilots took place, e.g. Amsterdam
  • Production is announced by vehicle manufacturers

Dri Driverl rless shu shuttle les ( s (accessib sibilit ility drive ven): ):

  • Lots of pilots (>35 in NL)
  • First applications in mixed traffic
  • Some already operational as part of the PT-system

Stat ate of

  • f the

the Art ( (2/2) 2)

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The he main in chal allenge ge of

  • f driverless

ss ro road vehic icle les is is the he com

  • mplex

x inne nner cit ity in inte teractio tion an and the he infrastr truc uctur ture chal allenge ges. The physical domain in which operations takes place is called the Operational Design Domain (ODD): Pub ublic tr transp sport h t has s the he pot

  • tential

al to to embr brac ace auto tomatio tion:

  • Mostly controlled ODD (e.g. separated infrastructure or prioritised intersections)
  • Constant ODD (e.g. fixed lines or operation areas)

In cont ntra rast st to to priv ivate te car ars: :

  • Uncontrolled ODD (e.g. mixed infrastructure)
  • Variable ODD (e.g. variations in route choice behavior due to congestion)

Poten enti tial of P PT T to to embr embrace aut utoma mati tion

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Degr egree ee of

  • f opennes

penness vs. s speed peed

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The R he Rott tter erda dam m Case e Study tudy

4. 4.

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Challen enges ges of

  • f the

he ci city of

  • f Rot
  • tterdam
  • 50.000 new dwellings
  • Social challenges for the south of Rotterdam
  • High unemployment rates in the South of Rotterdam
  • Lack of vitality and accesibility
  • Capacity problems in the current network
  • Financial effectiveness of bus and tram lines
  • Inner city space is scarce
  • Rotterdam was originally designed as a car oriented city; transition to sustainable modes:

No Nowada days (201 018): : Amb mbition (2040) 0): Bike ke 37% 43% Public c Tran ansport 31% 35% Car ar 32% 22%

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Poten enti tial impa mpacts ts

5. 5.

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Dr Driv iverle less metro ro

  • Vitality & Social cohesion
  • Increased accesibility of jobs and people
  • Worthy competitor of inner city car usage
  • Capacity
  • >50% capacity increase possible on same physical infrastructure (in Rotterdam)
  • Possibility to match demand and supply during off peak hours
  • Cost effectiveness
  • Reduction of operational costs by -40%
  • Increase of investment costs by +12%
  • ROI of ca. 10 years
  • Operator POV
  • Opportunity to automate control & maintenance procedures
  • Disruption control
  • Passenger POV
  • High user acceptance
  • Increase in robustness, reliability
  • Reduction of waiting times
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Dr Driv iverle less sh shut uttles ( es (1/2)

  • Vitality & Social cohesion
  • Improving accessibility, feedering to Metro
  • Mobility for elderly, disabled
  • Capacity
  • Capacity lower compared to a regular bus, however:
  • Much more efficient operation of diffuse demand patterns (in space and time)
  • Cost effectiveness
  • Only operational when there is demand
  • Vehicle cost dillema
  • Willingness to pay increases in flexibel on demand operation
  • Operator POV
  • Often seen as a competitor, but AV’s have the potential to strengthen the competitive

position of PT

  • Driverless shuttles can have a very high reliability (ODD-related)
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Dr Driv iverle less sh shut uttles ( es (2/2)

  • Passenger POV
  • Real acceptance is still uncertain (stated vs. revealed preference)
  • Social security
  • Imago effect
  • When putting passengers central; spatial implications seem huge
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Conc nclus usions ns & & Rec ecommenda mmendati tions ns

6. 6.

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Conc

  • nclusions
  • ns (1/

1/2)

  • Cities are growing; need

eed fo for mobilit ility increases ses; number of challenges increase

  • Innovation within public transport occurs on 4 main themes
  • Wireless
  • Dri

riverl erles ess

  • Emissionless
  • Seamless
  • Strong development of driverless vehicles; futur

uture is is un unsur sure

  • Self driving vehicles fa

face huge ge chal allenge ges in inner city implementation

  • Self driving vehicles could have a neg

egati tive effect o

  • n polic

licy goals ls:

  • Competition with cycling, walking and public transport usage
  • Increasing number of trips in case of privately owned vehicles
  • Increase in spatial footprint is huge
  • Space is scarce in cities, th

thus us ef efficient tr transp sport i t is s need eeded ed.

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Conc

  • nclusions
  • ns (2/2)

2)

  • Design of the current pu

publ blic c tr transpo port t syste tem has the potential to embrace automation given its bene nefic icia ial bo bounda dary cond

  • ndit

itions ions (e.g. ODD)

  • Driverless metros and driverless shuttles are able to positively contribute

to policy goals such as capacity, accesibility, financial effectiveness and sustainability

  • Au

Autom

  • mation

ion is is al alread ady taking ing place ce in all public transport modalities and should not longer be seen as a futuristic vision

  • Automation of PT is a means to use infrastructure much more efficiently

without adding new infrastructure

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Recomme

  • mmend

ndations

  • ns
  • Take automation of public transport into account in tactical and strategic

planning; Do Do not

  • t thi

hink nk that at sel self-driv ivin ing vehic icle les wil ill solve al all your pr probl blems!

  • Match innovation to policy goal; prev

event tech chnol

  • log
  • gy driven dev

evelopment

  • Sync

nchr hroni nize implementation of automation with large scale asset management replacement (e.g. fleet replacements)

  • Match policy goals to the development of autonomous vehicles
  • Put

ut pas passenge gers cent ntra ral within the implementation process of driverless public transport

  • Learn from each other, try

ry not

  • t to

to be be the he first st! “Embrace automation in public transport, otherwhise automation will embrace public transport”

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