Den Regionale DatahubOpstartsmøde mobilitetssporet

27.6.2018

Program for dagen8.30 Kaffe, te og morgenbrød

9.00 Velkommen - ved Lise Søderberg, Projektleder Gate 21

9.10 Den Regionale Datahub og mobilitetssporet - Ved Lise Søderberg, Projektleder Gate 21

9.20 Intro til processen (design thinking) - Ved Troels Behrenthz Andersen, Konsulent, Teknologisk Institut

9.30 Åbne mobilitetsdata – erfaringer fra ind- og udland - Ved Frans La Cour, Chefkonsulent, Københavns kommune

9.40 Indspark udefra: TDC, Location insight services - Ved Dennis Alan Larting, TDC

10.00 Indspark udefra: How data analysis can help the municipalities to better understand movement of people by vehicle, on foot and by public transport - Ved Stephen Leece, Managing Director, Citi Logik

10.20 Pause

10.30 Gruppearbejde Hvilke mobilitetsudfordringer er der i kommunerne?

12.30 Frokost

13.15 Gruppearbejde (fortsat)Hvilke mobilitetsudfordringer er der i kommunerne?

14.35 Næste skridt i mobilitetssporet - ved Lise Søderberg, Projektleder, Gate 21

14.50 –15.00 Farvel og tak

Deltagelse i mobilitetssporet

Projektets overordnede mål

Vision:

At skabe værdi for borgere, kommuner, regioner og virksomheder i Greater Copenhagen ved øget brug af data på tværs

Mission:

Vi udvikler en model for Den Regionale Datahub, der fremmer datasamarbejde på tværs af forvaltninger, kommuner og sektorer - til fordel for grøn vækst og øget livskvalitet

4 + 2 + 1 spor

Hvad skal projektet munde ud i?• Overblik over udfordringer i kommunen,

hvor data er svaret

• Afklaring af gevinster de enkelte løsninger kan give

• Hvordan en model for en teknisk platform kan se ud

• Et forslag til en fremtidig forretnings- og samarbejdsmodel for en hub

… efterfølgende kan der tages stilling til implementeringen af en fælles regional datahub.

Hvad siger projektaftalen- specielt om mobilitet?

Strategisk fokus i projektet er i udgangspunktet på mobilitetsudfordringer i forbindelse med anlæg og drift af letbanen…..

Udgangspunktet på mobilitet er bredt (pendlere og kommunens borgere) og der tages udgangspunkt i understøttelse af det udvidede stationsnærhedsprincip. Herudover vil der være fokus på optimalt samspil mellem Letbane og øvrige mobilitetsformer og initiativer

Formålet vil være i første omgang at bidrage til at løse konkrete mobilitets- og trængselsproblemstillinger i forbindelse med etableringen af letbanen

Mobilitetsudfordringer – lokale < > på tværs…

Datakombinationer = løsning på udfordringerne

Kommunale data

Nye data Dataanalyse Løsning

Kommunale data

Dataanalyse Løsning

Nye data Løsning

Eksempler på data …

GeodataKommunale data

Nye data

Trafiktællinger

Trafiksignaler, hvor?

Trafiksignaler, skift hvor ofte?

IOT data

Data fra mobiltelefoner

Eksterne webservices

(vejr, ulykker realtid ….)

Gravearbejde, hvor?

DESIGN THINKING

Gate 21

DESIGN THINKING

Gate 21

Program

DESIGN THINKING

• Systematisk metode til at løse problemer

• Brugeren er altid i fokus

• Vi skal nå længere end det ”åbenlyse”

• Metode til at arbejde med ”wicked problems”

Hvad er design thinking?

DOUBLE DIAMOND

GENERELT

PROBLEM

SPECIFIKT

PROBLEM

SPECIFIK

SOLUTION

DOUBLE DIAMOND

DOUBLE DIAMOND

DOUBLE DIAMOND

GENERELT

PROBLEM

SPECIFIKT

PROBLEM

“If I had one hour to solve a problem,

I'd spend 55 minutes thinking about

the problem and 5 minutes thinking

about the solutions”

ALBERT EINSTEIN

Vi parkerer de gode løsninger…

Vores fælles hjerne…

EKSPERT OPLÆGNU:

Fælles brainstorm

Erfaringer med mobilitetsdata

Mobilitetsdata

Data om den kollektive trafik, herunder

positionsdata fra busser og toge

Data om antallet af passagerer

Realtidsmålinger af trafikdensiteten

Data om transportinfrastrukturen,

herunder vejnettet og jernbanenettet

Data om cyklister og gående

Anvendelser

Dataprocessering: Forædling eller berigelse af data med henblik på videresalg

Produktudvikling: Udvikling af nye produkter og services på baggrund af data

Udvikling af data infrastruktur: Udvikling af underliggende data infrastruktur

Forretningsanalyser: Brug af data som datagrundlag for forretnings-beslutninger

Planlægning og dokumentation: Offentligemyndigheders dataanvendelse

Forventede effekter

Luftkvalitet

Trængsel, parkering

Adfærdspåvirkning

Flexibilitet – multimodal

Beslutningsstøtte om mobilitet

Danske aktører

”Letbanen” (2025)

Movia, Metroselskabet, DSB

Rejseplanen, Rejsekortet

Navigation: Google, Apple, Inrix, TomTom, Nokia, Microsoft, Strava

Vejdirektoratet m.m.

Københavns trafikmodel, Transportministeriets trafikmodel

Nationale erfaringer

Business Region Aarhus

(2016 - …)

City Data Exchange

Dele data der er

indrapporteret centralt

Konkrete use cases

Ledelse og ressourcer til fremskaffelse og distribution

Fællesskaber

Dialog med aftagere Standarder

Datahub

Presentation to Wigan CCInsight into the way people move on foot, in a vehicle

or by public transport

Vodafone & Citi Logik have created a big data capability focused on predictive analytics

to drive value from the existing mobile network. Derived data sets help our customers:

City Planners, Transport Planners, Infrastructure Operators and Consulting Engineers

to understand people & vehicle movements

Stephen Leece, Managing Director

Stephen Leece, Managing Director

Presentation to Wigan CCInsight into the way people move on foot, in a vehicle

or by public transport

Vodafone & Citi Logik have created a big data capability focused on predictive analytics

to drive value from the existing mobile network. Derived data sets help our customers:

City Planners, Transport Planners, Infrastructure Operators and Consulting Engineers

to understand people & vehicle movements

Stephen Leece, Managing Director

Stephen Leece, Managing Director

Citi Logik was established in 2011 to analyse movement by vehicle, on foot

and by public transport - better, faster and cheaper than current out-dated

transport techniques.

Big data derived from the mobile phone network offers the opportunity to

create comprehensive and high value understandings and pictures of people

movements, from the 3/4G infrastructure that is already in place.

This capability is genuinely disruptive, capturing anonymized and aggregated

information from millions of ever-moving sensors (mobile phones), facilitating

analysis across transport modes, across every minute of every day, for every

major road, rail route and pedestrian walkway.

EXPLOITING THE 3/4/5G/IoT NETWORKS

LONG TERM SUPPORT FROM UK plc

✔

✔

✔

✔

✔

✔

✔

✔

✓ Improve journey time reliability ✓ Reduce congestion ✓ Create economic activity

In a recent Deloitte report (2017), it was reported :

➢ In the UK, smartphone penetration is now 85 per cent of adults; expect this to reach 90 per cent by 2020, if not earlier.

➢91% of the 41 million 16-75 year olds who have a smartphone in the UK use their device every day.

➢17% of 16-24 year olds look at their smartphones at least 100 times daily; 12% of 16-19 year olds claim 200 views or more daily.

➢Eleven per cent of 16-75 year olds use their phones while crossing the road; more than half (53 per cent) do so while walking.

➢Video is increasingly likely to be streamed into cars, buses and trains for passengers’ consumption

http://www.deloitte.co.uk/mobileuk/assets/img/download/global-mobile-consumer-survey-2017_uk-cut.pdf - page=23

EMERGENCE OF SMART PHONE BASED SOCIETIES

WHY IS IT SO DIFFICULT TO DEVELOP SMART CITIES AS A MARKETPLACE?

70-80% of mobility information owned by commercial entities

Platform companies are taking a predatory position

Improving traffic flow and reducing pollution is not their priority

WHY IS IT SO DIFFICULT TO DEVELOP SMART CITIES AS A MARKETPLACE?

70-80% of mobility information owned by commercial entities

Platform companies are taking a predatory position

Improving traffic flow and reducing pollution is not their priority

34%

‘CREATING LOCAL VALUE THROUGH COLLABORATION’

Locally generated 3/4/5G data

App Based Data

Blue Tooth

GPS (Traffic Master, INRIX, HERE)

Global Platforms (Google Waze/Facebook)

GARTNER INDEX

Encrypted & Stored

Algorithms

Aggregation

Transport Assessment

Integrated Design

Client Solution

Raw Data

Integration/Complexity

Mee

tin

g R

equ

irem

en

ts

High

High

• Networks• Data Capture• Real-Time

• Keys/Privacy• Cloud Storage

• Trip O-D’s• Modal Breakdown• Route Mapping

• Big Data• Analytics• Multi-Feeds

• Policy Driven• Smart Cities• Clear Benefits• Client Management

Analysis of National ProjectsKick-start Regional Programmes

Create Connected CityEnhance Transport Agency

Data Broker

• Evidence Based• Project Mngm’t• Core Processes• Key Outputs

3/4/5G/IoT Network Operator

• Scheme Based• Challenge Driven• Human Factors• Urban/Built • Business Case• Outcome Focussed

Low

THE CONNECTED TRANSPORT VALUE CHAIN

http://www.vodafone.com/content/dam/vodafone-images/sustainability/drf/pdf/vodafone_drf_customer_privacy.pdf

Example of individual journeys

EXAMPLE JOURNEY

A LOCAL 3/4G NETWORK (1200 MASTS)

SPATIAL RESOLUTION: DEPENDENT ON THE MAST DENSITY OF THE LOCALITY

Citi Logik is able to operate Census level (LSOA) and to analyse Origin Destination, Traffic Flow and Demographics:

✓URBAN AREA (1:15,000). Mast density supports analysis of large buildings e.g. rail stations, secondary roads and also determine pedestrian movements

✓RURAL AREA (1:200,000). Mast density supports analysis of primary roads and flows into and out of geo fences BUT dependant on the location and orientation of the masts

Project awards include: regional analysis of traffic movements, optimal location of bridges, passenger flows to/from airport, analysis of metro stations, pedestrian movement in a city centre

Central London 1:15,000

Caernarfon at 1:200,000

WORKING WITH NATIONAL DATA SETS (CENSUS)

-30

-20

-10

0

10

20

30

40

50

60

70

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

Epso

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omm

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ow in

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Thou

sand

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Perc

enta

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iffer

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bet

wee

n M

obile

Pho

ne d

ata

and

adju

sted

Cen

sus

flow

s) Top 20 Census commuting flows (smallest to largest) from Resident LA of

% difference

Census Flow

REGENERATING WALES

Mobile data is a much richer and more comprehensive data set

than derived by traditional survey techniques. It represents the

actual journey paths of Vodafone customers encompassing

home zone, workplace zone and their modes of travel or journey

pathsSensor Network

Example: Raw Data Size 9 TB

Total number of data files 4 million

Number of transactions 40 billion

Unique IDs 3 million

Geo Events 20 billion

Events per mobile 47 per day

Regional Data – 8 weeks of collection v geo fence

Within City Centre more than 676 location points were used as derived form cell towers.

Information on origin, destination, time of the day, mode, access location to the city centre were recorded

Mode Share for Trips that originated outside

the city Centre

LIVERPOOL CITY CENTRE

Amey commissioned Citi Logik to undertake an assessment of travel patterns from and to Liverpool City Centre. Focus included understanding main access to City Centre by the main mode of transport but also how users reach their final destination from the various car parks and rail stations in and around the City Centre.

Post processing of the data allowed us to split trips into various legs to specifically understand pedestrian trips between the travellers final destination and motorised (rail/road) point of access to the city centre.

Slow Mode Journeys in Liverpool City Centre

LIVERPOOL CITY CENTRE

Over a 2 weeks period about 250,000

trips a day were observed travelling

from/to the city centre (about 750,000

trips per day after expansion to full UK

population)

ORIGIN DESTINATION ANALYSIS OF A KEY

ROAD

ANALYSIS OF ‘JOURNEY TIME RELIABILITY’ AND FEEDER ROUTES

LONDON MARYLEBONE ROAD

‘The data looked at how vehicles and pedestrians interacted with the Marylebone Road. Citi Logik

collected data for eight weeks, aggregating a total of 1.2 billion anonymous journeys into, around and

out of a pre-defined geographical area in London to give a picture of how people travel.’ Eddie

Copeland, Policy Exchange

London commuters suffer more stress than in any major European city’ 93% say they add half an hour to their commute to allow for delays

Vauxhall Fire: 5th May 2016 Change in Travel Patterns at Victoria Tube

Stressed London commuters are late for work more often than those in any other major European city, a major

survey finds today. Four out of five workers in the capital say they are delayed by hold ups on their daily

journey at least once a month, while 47 per cent admit to being late two or three times a month. The findings

come after today issued a major apology to commuters caught in hours of travel chaos at Waterloo station last

night. Disruption was so severe there were more delays this morning because trains were out of place.

LONDON HEATHROW

Study: To develop the full transport model by mode for the airport and the

surrounding area with Motts and AECOM representing the clients interests

0K 1K 2K 3K 4K 5K 6K 7K 8K 9K 10K

Raw Trips(o)

1K

2K

3K

4K

5K

6K

7K

8K

9K

10K

Raw

Tri

ps(

d)

Y = 0.97*X + 9

R2 = 0.97

Geo Fence

Data Integrity

Activity Levels

Zoning Model

MOVEMENT AROUND A METRO STATION

Actual demand around a health care facility

HOSPITAL ANALYSIS OF JOURNEY TIME (SYNTHETIC &

ACTUAL)

CITI ANALYTICS

FUTURE CITIES CATAPULT - URBAN INNOVATION CENTRE

Citi Logik is a resident innovator within the Urban Innovation Centre in London

Citi Logik supported by Vodafone, the Future Cities Catapult and QinetiQ won the ‘first of a kind’ a competition run by Innovate UK on 1st

April 2017

Over the period April 2017 – March 2018 we we built a real time 3/4G analytics suitable for UK Cities Citi Analytics (formerly Citi Watch)

Citi Analytics was awarded a further £900k of grant monies for Rail Watch / Pollution Watch and is the first Innovate UK sponsored company to secure £1m of long-terms loans

Commercial in Confidence

• Cell density also varies by area –

Typically more density within

urban areas.

• Density also affected by cell

technology - 2G large coverage to

4G small coverage

For data privacy and security

reasons, we will aggregate trip end

points outside the geofence

boundaries to borough/district level.

WORCESTER CITY – 3/4G NETWORK COVERAGE

Note: Only one icon shown per cell location, some sites contain more than 1 cell

Corridor 1• The cell-to-corridor allocation

process utilises the snap-2-road methodology

• It takes into consideration various characteristics of the cells to allocate the cell location to a corridor segment

• The process is repeated for all corridor segments

• A cell cannot be allocated to more than one segment per corridor

ALLOCATION OF THE NETWORK TO ROAD NETWORKS

TECHNICAL ARCHITECTURE

• Model calibrated using MIDAS data• MIDAS data = red line• Current CitiWatch data = blue line; • New calibration methodology = green line

COMPARISON OF LEGACY, 3/4G AND PREDICTIVE CAPABILITIES

• Differs from traditional approaches in that:• Requires no historical data to be trained, and minimal computational resources to run• Easy to integrate into CitiWatch and deploy to new locations

• Central Idea:• Given observations in a previous window, can define a function to estimate

observations at time 𝑡 + 1 from those observed at time 𝑡• The estimates for 𝑡 + 1 are refined using expected values (i.e. the baselines) to give

more accurate estimates (essentially a weighted average)

PREDICTION ENGINE

WHAT DOES OUR PRODUCT LOOK LIKE TODAY

AND IN THE FUTURE

DISCOVERFASE 1:

DISCOVERFormål

• Vidensindsamling• Hvem er berørt?• Påvirkninger• Kontekst• Udforsk hvad der giver værdi for brugerne• Kvantitet!

Output• Mulige retninger/tematikker for projektet• Nøgleindsigter• Kontekstforståelse• Empati

Bra

inst

orm

Fælles brainstorm

Jobs

to b

edone

“People don’t want to buy a quarter inch

drill. They want a quarter inch hole” Theodore Levitt

An excuse for an informal chat

To help me not feeling awkward during breaks with colleages

Helping me feel awake

Free wifi

A morning ritual

Why do you buy a cup of coffee?

FUNCTIONAL

A desired

goal

A ”job to be done” is…

The progress a customer is trying to achieve under specific cirtumstances…

EMOTIONAL

A desired

feeling

SOCIAL

A desired

perception

FUNCTIONAL

EMOTIONAL SOCIAL

Foru

dsæ

tnin

ger

& a

nta

gels

er

Hvilke kritiske antagelser og forudsætninger skal undersøges for at fastslå, hvordan ”jobbet” skal udføres?

ANTAGELSESØVELSE

Inte

rvie

w

Udarbejd interviews der kan skabe indsigt og teste jeres forudsætninger & antagelser.

INTERVIEW

Spørg ind til forudsætninger &

antagelser – og byg videre på dem!

DEFINEFASE 2:

DefineFormål

• Afgrænse problemfelt

• Se potentiale

• Specificere værdi for brugeren

• Definere problemstilling

• Kvalitet!

Output• Specifik problemstilling

Gru

pperin

g a

f in

dsig

ter –

find

tem

aer!

Gruppér jeres indsigterGruppér jeres indsigter og efter temaer, ligheder, afhængighed, geografi, osv.

Illustrér forbindelser og forhold mellem problemerne.

Hvord

an k

an

vi…

Hvordan kan vi…Formuler mulige problemstillinger og start dem med "hvordan kan vi ..."

Spørgsmålene skal hjælpe med at gøre problemet mere specifikt.

Forbered 2-3 HMW pitchesFokus:• Hvem er målgruppen• Hvad er potentialet inden for (1-5):

• Samfund• Vækst• Drift• Innovation

Findes der lign. problemer andre

steder? Hvordan er de løst?

Next steps … mobilitet

Mobilitetssporet – overordnet tidsplan

OpstartsmødeKvalificering af udfordringer

MarkedsdialogPrioritering af udfordringer

Udbud/

konkurrence

Udvikling af prototyper

Test og evaluering

Juni 2018 Juli/Aug 2018 Aug/Sept 2018 Sept. 2018 Nov/Dec 2018Sept/ Okt 2018 Jan 2019

Efter mødet får I nogle spørgsmål tilsendt ….

Efter dette møde – udsendelse af papir

• Hvad har i af data, der kan bruges til den udfordring?

• Kan de data stilles til rådighed for offentligheden/ andre kommuner?

• Har i et sted, hvor prototypen gerne skal udvikles?

• Etc.

Gerne tilbagemelding hen over sommeren

Udefra ind … perspektivet….

Borgerinvolvering …. / Virksomhedsinvolvering ….

Hvordan ser de på udfordringen? Hvilket behov har de?

Vil de være med/interviewes/ evt. inddrages hvis vi udvikler en prototype?

Værktøjskasse – din toolbox

Idéer til indhold:

• Kan data deles? … med andre kommuner?… med offentligheden?

• Hvordan kan man tilgå data?

• Opendata.dk – hvordan uploader jeg data?

• Metadata – “vare”beskrivelse hvordan?

• Dataregistrering – hvad findes i x-fagsystem?

• Andre ønsker…..

Spørgsmål og kontakt

Lise Søderberg

Projektleder Den Regionale Datahub

Gate 21

Tlf. 2125 1426

Lise.soederberg@gate21.dk