Jan$Lundgren$...

The Swedish Postgraduate School in Intelligent Transport Systems

Jan Lundgren ITS World Congress, October 8, 2015


CooperaDon between ITS Sweden and seven universiDes

Supported by the Swedish Transport AdministraDon and the Swedish Governmental Agency for InnovaDon Systems (VINNOVA)

Aim:

•  Improve the PhD-‐educaDon through specialised doctoral courses and extended supervision of students

• Promote academic research within the field of ITS relevant for industry and society

•  Increase the interest and focus of transportaDon research and educaDon within the universiDes

•  Establish networks for collaboraDon both naDonally and internaDonally


Modeling and Simula0on Study of Heavy-‐Duty Vehicle Platooning

Qichen Deng

KTH Royal InsDtute of Technology

Research ques0ons

•  What are the benefits of platooning heavy-‐duty vehicles on highway (HDVs)?

•  When can two HDVs form a platoon?

Benefits – Improve Fuel Efficiency of HDV

Benefits – Improve Traffic Efficiency

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No HDV PlatooningHDV Platooning with CVS Policy

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(a) 10% of total traffic is HDVs; (b) 15% of total traffic is HDVs; (c) 20% of total traffic is HDVs; (d) 25% of total traffic is HDVs.

(a) (b)

(c) (d)

When can two HDVs form a platoon?

•  Key factors affecDng the HDV platooning formaDon:

1.  Traffic density

2.  Driving behavior of passenger car

3.  Speed of HDVs

Lane 1

Lane 2

Platoon Forma0on of Two HDVs on a Two-‐Lane Highway

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18 vehicles540s

17 vehicles720s

Coopera0ve ITS in traffic management

Ellen Grumert Linköping University

Coopera0ve ITS in traffic management -‐ Mo0va0on

Source: Foto taken by user Fir0002, publiced at www.wikipedia.org (accessed 2014-‐09-‐21)

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Density

Flow

Coopera0ve ITS in traffic management -‐ Approach and method

InformaDon

InformaDon

InformaDon

InformaDon

InformaDon från central styrning

Source: Foto taken 2010 by Holger Ellgaard, publiced at www.wikipedia.org (accessed 2011-‐04-‐13)

V2V

I2V/V2I

SUMO

Coopera0ve ITS in traffic management -‐ Main conclusions

•  The performance of the variable speed limit systems is dependent on the choice of algorithm for deciding on which variable speed limit to use on the road.

•  CooperaDve variable speed limit systems using I2V harmonize the flow compared to regular variable speed limit systems.

•  LimitaDons in having fixed measurement points. V2V could probably improve the performance further allowing for measurement point in between detectors.

•  Speed limits reflecDng the condiDons on the road gives best performance.

•  Early prevision/early detecDon limits the effects of high flows.

•  The capacity levels are of high importance for the performance.

Performance evalua0on of coopera0ve awareness in C-‐ITS

Nikita Lyamin

Halmstad University

Background

Research problems

Dynamic Origin-‐Des0na0on Matrix Es0ma0on for off-‐line applica0ons

Athina Tympakianaki

KTH Royal InsDtute of Technology

OD es0ma0on problem

•  OD estimation is important in many applications - essential input traffic simulation models (microscopic, planning models)

- traffic management (ITS systems)

- traffic prediction - transportation planning

- evaluation of different strategies

•  Find an OD matrix that best matches a set of indirect observations (e.g. counts, speeds)

•  Underdetermined problem, many unknowns fewer equations: different OD matrices result in the same traffic counts

•  Addition of more data sources reduces the set of possible solutions – requires more general formulations of the problem and solution algorithms

•  Traffic simulation is used to capture the traffic conditions resulting from different OD matrices

Proposed OD es0ma0on methods 1. A gradient algorithm with formulation based on an assignment matrix that maps OD flows to counts at sensor locations (e.g. Toledo and Kolechkina, 2013). 2. Cluster-based SPSA algorithm (Tympakianaki, Koutsopoulos, Jenelius, 2014) - Modification of the commonly used SPSA (Spall, 1998) algorithm. Motivation: •  Different OD magnitudes •  Unstable performance, algorithm diverged

Modified algorithm, cluster-based SPSA: •  OD pairs are clustered based on some criteria:

§  Homogeneity within cluster §  Magnitude of OD flows §  Size of cluster §  Number of clusters

•  Gradient is approximated independently for each cluster

Case study – synthe0c data •  Södermalm network, Stockholm •  1100 urban and freeway and urban links •  ’True’ OD demand: synthetic data

- 462 OD pairs - 7-8 a.m. study period - 15 min time interval

•  Sensor coverage: 5% of the total number of links. •  Traffic observations: counts, speeds •  Mesoscopic traffic simulation model: Mezzo

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OD flows (veh/h) Counts (veh) Speeds (km/h)

•  More robust algorithmic performance •  More accurate OD matrices •  Less sensitive to the selection of the algorithmic parameters •  Improved practical convergence

Motorway applica0on using real data

How well does the method esDmates the OD flows when an incident occurs?

OD esDmaDon: •  Gradient descent algorithm •  MCS counts Counts (veh/h)

IniDal error Final error

RMSE 103 56

ME 29,3 0,83 -‐100

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Södertälje -‐ Bredäng

14 km 14 OD pairs

Transport for sustainable urban development – integrated modelling of

walk, cycle and public transport

Gerasimos Loutos Linköping University

Project View

The goal is to improve the modeling of bicycle trips in current demand models

AIM to: •  Develop techniques for modeling trips chains including bicycle and public transport legs.

•  IdenDficaDon of appropriate level of detail for non-‐motorized modes. •  IdenDfy factors important for bicycle mode choice and factors important for policy analyses.

Policy variables – Factors that influence the share of cyclists

Built environment Urban form (distance), infrastructure and faciliDes at work

Natural environment Hilliness, climate and weather

Socio-‐economics Gender, age, income, car and bicycle ownership, employment status

Psychological factors Amtudes, social norms and habits

Cost, travel 0me, effort & safety

Mode choice models

Built environment Urban form (distance), infrastructure and faciliDes at work

Natural environment Hilliness, climate and weather

Socio-‐economics Gender, age, income, car and bicycle ownership, employment status

Psychological factors Amtudes, social norms and habits

Cost, travel 0me, effort & safety

Mode choice models es0ma0on

Survey Data (Revealed Preference, ex. RVU) •  InformaDon on conducted trips & socio-‐economic variables •  Drawback: only characterisDcs for individual’s chosen mode

I. e. Missing travel Dme and distance (non-‐used) alternaDves

Regression Models Trip planning applikaDon

Available tools and future development Currently used models

•  Sweden: SAMPERS, Local EMME or VISUM-‐models, SLL VISUM-‐model •  Do not include specific bicycle and walk factors (e.g. infra, costs) •  Cycity: project targets to improved data collecDon (more surveys, GPS data

from cyclists etc.) •  MoveMeter (MoveMobility), Brutus (Strafica) in a Swedish semng.

Frame a new transport demand tool •  Include modelling trips chains with several modes •  Assignment of trips to the street (OpenStreetMap) network for all modes using,

•  Time table data for public transport for walk/PT-‐trips •  Bicycle rouDng using a trip planner (in OSM network) •  TradiDonal car assignment (in OSM network)

Access management in intermodal freight

transporta0on

Stefan P G Jacobsson Chalmers University

Access management in intermodal freight transporta0on -‐ Iden0fied problems1

Decentralised

Many actors Different modes

Deficiencies in the interaction

Practical problems in the hubs

Lack of high-quality real-time data2

Decentralised

Decentralised

Decentralised Decentralised

________________________ 1 According to Marchet et al., 2012, Perego et al., 2011, Bujis and Wortmann 2014 2 According to SteadiSeifi et al., 2014

Access management for carrier operaDons in intermodal freight transportaDon

Research gap Research agenda /

Next steps

(1) Problem idenDficaDon and

moDvaDon

Con-‐versaDons

Obser-‐vaDons

Literature study

Bench-‐marking

(2) Define the objecDves for a soluDon

Access management

Handling of carrier access

Beper understanding and knowledge

Literature study

Con-‐versaDons

Obser-‐vaDons

Access management in intermodal freight transporta0on -‐Methodology

•  For smaller actors •  Use already exisDng IT-‐systems •  InteracDon in real-‐Dme •  Qualify for access to an intermodal container

terminal

Access management in intermodal freight transporta0on -‐ Solu0on

Development & Evalua0on of Mobile Phone App for Detec0ng Safety Cri0cal Event of Motorcycle Rider

Noor Azreena Kamaluddin

Lund University

Introduc0on

q  An app for motorcyclists will be developed to register safety critical

events. q  Safety critical events will be identified by certain trigger

variables (e.g. jerk). q  The app helps to describe the course of events in a (near)

accident. q  The effects and rider acceptance of the system will be

studied in a real life study.

Background

Ø Safety : crucial issue of motorcycle (More than 60% of fatalities, 20x higher risk)

Ø Shortfalls issue – Complementary method (Reliable estimation)

Ø Vital prerequisite to set-up more realistic targets for crash/casualty reduction programmes

Ø No available or standard procedure in use for collecting self-reported accidents in Malaysia

Objec0ves

Ø  Collect self-reported accidents & determine under-reporting - GAP Ø  Develop & test of a mobile apps (e-Call) for motorcyclists – enrich current

system Ø  Identify/predict safety critical events based on sudden acceleration

change (jerk) Ø  Produce complementary method of accident recording system Ø  Map locations with a higher single-accident risk based on the smartphone

application (eCall app)

The eCall System for Motorcyclist

Usefulness: Ø Send/prepare message to

SOS centre

Ø Minimize rate of fatalities: Immediate medical assistant

Ø Collection of anonymous data & identify bike-accident prone area: Good basis of prevention

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