Iisakki Kosonen

Intelligent Transport

SPT-E8010 -Smart and Liveable City Studio

22.03.2017

Iisakki Kosonen, Staff ScientistDepartment of Built Environment

Spatial Planning and Transportation Engineering

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A Short Overview

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Smart City – Processes

Planning

Constructing

Improving

SmartLiving

SmartMobilityRecycling

SmartEnergy

SmartX

Maintenance

Operating

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Technology and the Traffic Processes

Vehicles

Travellers

Infrastructure

Software &Hardware

Algorithms &Communications

ApplicationsServices &

Traffic Vehicle

ITSTechnology

Mobility

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Collecting the Traffic Data

1 2 3

4 5 6

Mobile Phones

Internet

Digital TV

Vehicle TerminalsSocial networks

Beacons-Bluetooth- RFiD- WLAN

ImageProcessing

Connectedvehicles

DetectorsDetectors

Laser,Radar

Analysis & Modeling

Automatedvehicles

ConnectedTravellers

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Intelligence to Traffic Management

80 P

Controllers

1 2 3

4 5 6

Modeling / Predicting

Decision makingAdapting, Optimizing,

PlanningObjectives

Sensors

V2VV2I

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Supporting PlanningPublic sector

Private sector

TechnologicalEvolution

Smart Policy

Smart CityIntelligent Transport

Planning support systems

Emerging Business Models

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Multiple Objectives

Fluency

Safety

Economy

Environmentalimpact

Demandmanagement

Trafficinformation

Traffic control

Driver support

Traffic demand

Mode selection

Route & time selection

Traveller & driverbehavior

R.Kulmala

Userfriendliness

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Traffic control

Demand

Demand vs. Supply

Trips generatedDeparture time

Destination choiceMode of transport

Route choice

Traffic flows

Urban structure

Socio-economical factors Values and attitudes

Backgroundvariables

SupplyThe efficiency and level of service

of all modes of transport

Road works, accidents,incidents

Road & Street network,Public transport system,

Parking, Shared transport

Road and weatherconditions

Traf

ficm

anag

emen

tsys

tem

s

Experiences

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More Flexible ServicesOld structures

Timetabled trafficSeparate paymentsystemsFew real timeinformation services

Traveller

Profiling - segmentationConsumer behavior & motivations

New structures and models

Demandresponsivepublictransportaton

Mobile ordering

Smart traffic controlReal-timetrafficinformation

Payment systemsRoute planners

Sharedvehicles

Public transportation

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Vehicle Automation

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Electric Mobility

Fastcharging

Slowcharging

Electric car Compact city vehicle Electrically assissted bicycle

Optimization of production, distribution and energy efficiency

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CaseOtaniemi

What can we do ?

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General Goals for the Otaniemi Region

• A living urban area• More people living in the region• More houses, not offices only• More local services• Well connected to Tapiola and Keilaniemi• A living lab environment• A digital hub• Green environment

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Transport Related Goals

• Improving public transport• Limiting car traffic• Walkable region• Improved biking facilities• Saving the scenic walking routes

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Concrete Actions• Improving public transport

• New routes for the bus traffic (roundabout)• Metro line• Jokeri Tram line

• Limiting to car traffic• Closing of the main road (Otanimentie)• New parking policy

• Walking & biking• The main building with metro station serve as a

hub for walking trips

Otaniemi as a major hub

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TravelingData

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Detect the service:bus/tram line number

Identify themain activity

locationsShow the real-time

traffic situations

Detect the modes oftransport: walk, bike,car, public transport

TrafficSense smartphone application

Download from Google Play: TrafficSenseor go to trafficsense.aalto.fi

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The RawData

Analysis of the traveling behavior

Trip Chain Analysis

Car

PublicTransport

Indicators

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PersonalAssistants

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Congestion aheadTraffic incidentNo parking availableDelayed bus connection

Faster routeBetter connectionRidesharing optionPark&ride optionShared taxi

TrafficSense mobile service• Facilitate the use of shared transportation

(public transportation, ride sharing)• Shorten the travel time (avoiding congestions)• Improve the awareness of transportation

energy consumption

1. Collectuser

mobilitydata

2. Predict orrecognizethe current

route

2. Predict orrecognizethe current

route

3. Combine theprediction withreal-time traffic

information

4. Create moreenergy-efficient

options

5. Notify the user,if needed

Traveling Assistant

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Smart Parking

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New VehicleTypes

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Improving CyclingCargo bikesCampus bikes

City bikes

Electric bikes

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Personal Electric VehiclesAlready available right away in Finland

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Personal Electric Vehicles(in development)

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New Modes ofTransport

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Last-mile Services

• Robot buses can support the public transport• Frequent service rate• Fixed route or or flexible• Door-to-door if necessary• Campus traffic (universities, hospitals …)• Remote control for unexpected situations

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Shared vehicle

• Rental car is the prevailing mode of sharing car• The process is not very attractive for regular use with short notice• Booking, fetching, agreement, insurance, fueling, returning etc.• Mostly used when out of your own city/country• More flexible ways of using rental cars• A private car is unused most of the time (ca. 95%)• Can someone use the car meanwhile ?• Similar issues need to be solved than with rental car• Finding available car, booking it (smart phone apps)• Get access to the car (keys or smart phone opening)• Insurance, liabilities, car damage, fueling

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Shared Ride• A company service• Kutsuplus• Airport taxi, Uber and similar services• The driver is not going where you are• A private service• A car owner plans to go from A to B• Another person plans to got from C to D• Depends on how good match

• Route (e.g. is C to D along the route from A to B)• Time (departure time, arrival time, flexibility in time)• Uncertainties (e.g. last minute change of plans, reliability of the service/customer)

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PlanningSupport forTransport

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Traffic Simulation

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Traffic Assigment Models

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Activity Based Simulation

Age 26 26 7

Income $27k $16k $0

Status worker worker student

Automobile

POPULATION

HOME

WORKLUNCH

WORK

DOCTOR

SHOP

HOME

ROUTES AND MODES

HOME

WORKLUNCH

WORK

DOCTOR

SHOP

HOME

ACTIVITIES

SIMULATION OF EVENT S

The traveler hasstarted his trip.An event isrecorded.

TravelerEvents

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Microscopic Simulation

• Detailed level modelingof traffic

• Each vehicle and otheragents

• Interaction betweenagents, environmentand control system

S

Y P

V2

V1

Actual traffic

V1 V2

P

D

V3 V4D

V5

P

YG

S

G

S

G

Model of traffic

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Real-time Data Modeling• Data modeling for static structures

• GIS, BIM …• Data modeling for dynamic systems

• Scenarios, real-time, predictive• TIM ? (Transport Information Model)

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Thank you !

Let’s discuss