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 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

Thr hree ee autho uthors; ; two wo orga gani niza zati tions ns

The he need need fo for inno nnovati tion in n 1. 1. ur urba ban publ public tr trans nspo port

Gr Growth th of of cit citie ies; W ; Wor orldwi 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

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

Myth: My : Sel Self drivin riving cars cars wi will ma make e 2. 2. public tr publ trans nspo port t redunda edundant

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

Cha hallenges enges of of 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?

3. Driv riverle rless publ public tr trans nspo port

Driv riverle rless Publ ublic T Trans nspo port “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

Stat ate of of the the Ar Art (1 (1/2) Train ( Tr (capac apacity driven): ): • Implementation of ERTMS • First pilots are taking place Metr Me 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 of the the Art ( (2/2) 2) 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

Poten enti tial of P PT T to to embr embrace aut utoma mati tion The he main in chal allenge ge of of driverless ss ro road vehic icle les is is the he com omplex 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 otential 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)

Degr egree ee of of opennes penness vs. s speed peed

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

Challen enges ges of of the he ci city of of Rot otterdam • 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%

5. 5. Poten enti tial impa mpacts ts

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

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)

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

6. 6. Conc nclus usions ns & & Rec ecommenda mmendati tions ns

Conc onclusions ons (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 on 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.

Conc onclusions ons (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 ondit 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 omation 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