DigitalizationPaul  Davidsson    (Professor,  Computer  Science,  Malmö  University)

Jan  Persson    (Associate  Prof.,  Computer  Science,  Malmö  University)

Andreas  Tapani (Research  Director,  Traffic  analysis  and  logistics,  VTI)

Challenge  and  Approach

Major  challenge:  optimize  the  use  of  the  available  resources  to  meet  the  goals  of  society,  including– providing  the  best  possible  service  to  the  potential  travellers– economical,  environmental  and  social  sustainability

Approach:  make  use  of  modern  information  technology  to  collect  and  analyse  information  and  then  make  recommendations  to  – travellers– public  transport  operators– transport  analysts  and  planners

On-­‐going  research  – Digitalization

• K2-­‐funded  research  projects– Agent-­‐based  Simulation  of  Passenger  Transport  in  Urban  Areas– Efficient  Interchange  Stations– Information-­‐based  Disturbance  Management  for  Public  Transport

• Examples  of  affiliated  projects– Sustainable  Traveling  Through  Dynamic  Public  Transportation  

(Vinnova)– Data  Innovation  Arena:  Using  open  data  to  develop  innovative  

services  for  people  in  motion    (Vinnova)– National  Postgraduate  School  for  Intelligent  Transport  Systems  

(Vinnova and  Swedish  Transport  Administration)

Agent-­‐based  Simulation  of  Passenger  Transport  in  Urban  Areas  – Problem

Implementation

Instruments• Different taxes, restrictions on vehicle use,

ticket prices, investments in infrastructure, bus routes and frequency, etc.

Transportation system issues• Congestion, emission, service quality,

coverage, etc.

Impact assessment of changes in policies and infrastructure

investments

Actual tests• Expensive• Time-consuming• Sometimes infeasible

Traditional models• Limited number of factors• Oversimplification • Neglecting interaction effects

Agent-­‐based  Simulation  of  Passenger  Transport  in  Urban  Areas  – Approach

Decision making module

Cost Travel time

Social normsConvenience

Age Gender

Income Work&homeaddresses

Car / bike ownership

An agent-based modelwhere every traveler

is individually modeled

Choice of travel(mode, time, route, etc.)

Traveler’s characteristics

Cost Time

CO2 emission

Number of interchange

Walking/Cycling distance

Available travel options

Skåne-­‐trafikenOpenAPI

Google  maps

Agent-­‐based  Simulation  of  Passenger  Transport  in  Urban  Areas  – Results

• A  state-­‐of-­‐the-­‐art  analysis  of  relevant  models• A  questionnaire  survey  of  the  needs  of  the  relevant  stakeholders  • A  first  version  of  the  simulation  model  • An  initial  case  study  concerning  public  transport  pricing  and  

commuting  in  the  Malmö-­‐Lund  area  (16  persons)

Three scenarios:• Half the price• Current prices• Double the price

Agent-­‐based  Simulation  of  Passenger  Transport  in  Urban  Areas  – The  future

• Model  development:  The  agent-­‐based  model  will  be  further  developed  based  on  the  experience  of  the  initial  experiment  and  the  results  of  the  survey  of  the  needs.

• Validation:  A  larger  simulation  study  regarding  commuting  in  the  Malmö-­‐Lund  region.  Possibly  also  case  studies  in  other  urban  regions  in  Sweden.– Difficult  to  get  actual  data  with  sufficient  precision,  e.g.,  the  

home  and  working  addresses  (from  RVU).  Maybe  necessary  to  generate  artificial  populations.  

• Long-­‐term:  A  follow-­‐up  project  to  validate  and  apply  the  simulation  model  in  different  European  urban  regions  is  considered,  possibly  funded  by  H2020.

Efficient  Interchange  Stations  – Problem

• Interchange  stations  are  important  in  a  high  quality  public  transport  system– Connects  different  modes  and  routes– High  impact  on  passenger  satisfaction

• How  should  the  bus  and  tram  terminal  at  interchange  stations  be  designed?– High  capacity  to  avoid  congestion  and  queues  ® Large  terminal– Commercially  valuable  land– Short  walking  distances

• Need  of  good  tools  to  evaluate  this  trade-­‐off

® Small  terminal

Wikipedia/Ilya  Plekhanov

Efficient  Interchange  Stations  – Approach

• A  simulation  model of combined bus  and  tram terminals– Discrete Event  Simulation

• The  model will evaluate a  given  layout  in  terms  of its capacity• Applied to  Norrköping’s new  interchange station• A  first step:  A  two-­‐berth,  off-­‐street combined bus  and  tram

stop  at  Norrköping  interchange station

Event  1

Event  2 Event  4 Event  7

Event  5

Event  3 Event  6

Efficient  Interchange  Stations  – Results

• Two lanes,  buses  canovertake at  departure– Performs  marginally better at  

the  present  situation– Greater differences at  higher

inflow of vehicles,  but toolong  queues to  be  feasible

• One lane,  no  overtaking– Present  design

• A  simulation  model capable of comparing two stop  designs

Efficient  Interchange  Stations  – The  future

• The  stop  model  will  be  further  developed  and  expanded  into  a  model  of  a  bus  and  tram  terminal

• Application  of  the  model  to  Norrköping’s new  interchange  station• Evaluation  of  dynamic  platform  allocation• Long  term:  Optimize  platform  allocation,  interaction  between  

station  and  surroundings,  effects  of/for  different  passenger  groups,  the  station  in  the  lager  public  transport  system,  innovative  solutions  for  future  public  transport  systems  at  the  station…

Information-­‐based  Disturbance  Management  for  Public  Transport  – Problem

Jan  Persson  and  Åse  Jevinger

Situation:  Given  disturbances  in  the  public  transport  system,  there  are  a  number  of  potential  actions  that  can  be  taken  by  multiple  actors  (including  travellers)

Challenge:• Relevant  actors  need  to  have  information  related  to  the  

disturbance  when  deciding  what  actions  to  take• Actors  often  need  information  about  actions  taken  by  other  actors• Include  the  view  of  the  traveller  as  an  actor  (i.e.  being  a  decision  

maker  and  a  potential  provider  of  information)• Adopt  to  the  new  law  of  travellers  rights.

Information-­‐based  Disturbance  Management  for  Public  Transport  – Approach

• Identifying  missing  information  by  different  actors  in  situations  of  disturbances  – Focus  on  short  to  mid  range  journeys– Multiple  transport  modes  and  operators  typically  involved– Focus  on  information  needed  for  taking  actions  (e.g.  re-­‐planning  

resource,  take  another  route  etc.)– Also  include  operators  not  directly  involved  (e.g.  taxi  and  timetabled  

substitute  transports)• Mapping  information  needs  to  information  availability• Interviews,  participating  in  workshops  and  literature/report  reviews

Information-­‐based  Disturbance  Management  for  Public  Transport  – Results

• A  map  of  the  available  information,  including  the  information  flows  to/from  the  traveler  and  between  different  public  transport  actors

• Identified  a  rather  large  set  of  missing  information  (and  problems)  from  the  perspectives  of  the  actors  and  the  travelers

• The  effects  of  the  new  law  are  also  considered• Suggested  concepts  that  may  support  the  situation

– Check-­‐in  system  (including  intended  end  destination)

– Open  information  system• Suggested  some  rather  straight  forward  solutions  

to  some  problems

 

Travelers  directed  to  other  train  

Information-­‐based  Disturbance  Management  for  Public  Transport  – The  future

• Further  investigations  of  the  suggested  concepts• Further  investigations  of  the  effects  of  the  new  law• Traveller  opinions• Information  need  of  operators  not  directly  involved  in  the  

disturbance• Need  for  information  processing• Information  reliability

Some  Publications  – Digitalization

• Banafsheh  Hajinasab,  Paul  Davidsson,  Jan  A.  Persson,  Johan  Holmgren  (2016)  The  requirements  on  transport  models  for  estimating  the  effects  of  policies  and  infrastructure  investments:  A  questionnaire  study,  5th  Nationella Transportforskningskonferensen.

• Banafsheh  Hajinasab,  Paul  Davidsson,  Jan  A.  Persson,  Johan  Holmgren  (2016)  Towards  an  Agent-­‐based  Model  of  Passenger  Transportation.  Multi  Agent  Based  Simulation  XVI,  Lecture  Notes  in  Computer  Science,  Vol.  9568,  Springer.

• Banafsheh  Hajinasab,  Paul  Davidsson,  Jan  A.  Persson,  Johan  Holmgren  (2016)  Using  on-­‐line  services  for  outsourcing  the  computations  in  transport  simulation,  International  Symposia  of  Transport  Simulation  and  the  International  Workshop  on  Traffic  Data  Collection  and  its  Standardisation

• Banafsheh  Hajinasab,  Paul  Davidsson,  Jan  A.  Persson,  Johan  Holmgren  (2015)  Agent-­‐based  simulation  of  passenger  transport  in  urban  areas,  4th  Nationella Transportforsknings-­‐konferensen.

• Banafsheh  Hajinasab,  Paul  Davidsson,  Jan  A.  Persson  (2015)  Att beräkna styrmedelseffekter,  K2  Working  Papers  2015:4.

• Åse  Jevinger  and  Jan  A.  Persson  Information-­‐based  Disturbance  Management  for  Public  Transport  -­‐ Project  report  1.  K2  Working  Papers  2016:15.