Recent Talks

 

EU COST-action TU1102, Towards Autonomic Road Transport Support Systems (ARTS)

5.-6.10.2015 Bordeaux: Personal Agents for Multi-Modal Transport – TrafficSense.

6.– 9.10.2013. The Hague: Traffic Control with Autonomic Features.

12.-14.9.2012, Sofia: Outlining autonomic management of electric traffic.

14.-16.4.2010, Durham: Urban street traffic management based on real-time micro-simulation and multi-agent fuzzy logic.

EU COST-action TU0903, Calibration, Validation of Traffic Simulation Models (MULTITUDE)

4.-5.2.2010, Barcelona: Towards automated   calibration methods.

Projects

SOHJOA: Physical and virtual innovation platform of autonomous (EU Regional Funding 2016- )

Project Sohjoa addresses the challenges of new economic growth industries as well as sustainable intelligent transportation development. This is accomplished by bringing autonomous small electric buses to operate in 6Aika areas as part of the pilot innovation platforms created within the project. These buses have the potential to reduce operating costs, lower the overall emissions and offer better service to the mobility customer.

MulSimCo – Multilevel Traffic Simulation with Cognitive Basis
(Academy of Finland 2015- )

This project is carried out in co-operation with Helsinki University/Cognitive Science Unit and funded by the Academy of Finland (2015-2018). The aim is to develope a more realistic traffic simulation by combining the knowledge of transportation engineering with cognitive science.

TrafficSense – Energy Efficient Traffic with Crowdsensing
(Aalto Energy Efficiency Funding, 2013-)

TrafficSense is a multi-disciplinary project with other research groups in Aalto funded by the Aalto Energy Efficiency Program (AEF). The aim is to promote more energy efficient and green modes of transport through personal mobility management assistant (PMMA) based on crowdsensing of traveling behavior. The TrafficSense system is able to automatically detect the basic parameters of individual trips including the mode of transport and the public transport services used. Based on this data the system learns the mobility patterns and is able to predict next trip to done. Based on prediction the system look for potential problems or opportunities and suggest alternatives which are more energy efficient. TrafficSense approach is one of the necessary steps toward mobility as a service (MaaS).

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MUSIG – Multi-Objective Optimal Signal Control
(Aalto-KTH co-operation 2012-)

In the MUSIG project our aim is to develop intelligent traffic signal control by employing advanced computational methodology. Real-time situation awareness combined with multi-agent control provides the framework (the FUSICO-software). Most recently multi-objective optimization of traffic signals is studied in co-operation with KTH (Royal Institute of Technology).

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Light Energy – Efficient and Safe Traffic Environments
(Aalto Energy Efficiency Funding, 2012-)

The Light Energy – Efficient and Safe Traffic Environments project improves the energy efficiency of transport environments and outdoor lighting while maintaining a good level of road safety and taking into account the needs of road users. The project studies the optimal realization of lighting and develops smart control of lighting by considering the visibility and safety of road users, the traffic situation, and environmental and economic factors.

The specific target of Transportation Engineering is to study the effects of street lighting to traffic safety and develop an energy efficient and safe traffic responsive street lighting control method.

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Microscopic simulation of pedestrian flows (2011-)

This study investigates the effects of attractions to pedestrian flows. The aim is to model interactions between pedestrians and attractions including shopping displays and museum exhibits. In reality, such attractive interactions may lead to impulse stop behavior; pedestrians stop walking to destinations and join the attractions. The simulations indicate clear phases of the pedestrian flow, namely free flow, agglomerate state and competitive state. The results can be applied to the planning of public spaces.

The research work was partly funded by the MIDE-institute of the Aalto University though the 4D-space project.

Aalto ITS Initiative
(Aalto Special funding 2011-2012)

The challenges and opportunities of the research and education of intelligent transport was studied together with other related departments of the Aalto University. As an outcome three focus areas were suggested namely: intelligent traveling, intelligent traffic management and intelligent vehicle technology.

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Electric Mobility: SIMBe and eSINi projects (TEKES 2010-2014)

In SIMBe-project (Smart Infrastructures for Electric Mobility in Built Environments) the integration and effects of electric mobility to transportation system was studied. Especially the smart infrastructures for fast and slow charging for electric vehicles was investigated. A blueprint of charging infrastructure to the Helsinki region was planned.

The research was continued with a piloting project eSINi -(Electrical Vehicle Charging Infrastructure for Urban Environments), in which actual electric vehicles were used and the users were interviewed. Both project were funded by Tekes – the Finnish Funding Agency for Innovation.

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Emergent Social Mobility (EIT ICT-labs, 2013)

The emerging social aspect of mobility was studied in the research project funded by the EIT European Institute of Innovation and Technology, ICT-labs (now EIT Digital). The development of the Electric Trip Diary at Aalto University was carried out within this project.

EIT Digital

FOTsis – Cooperative ITS from Inrastructure Perspective (EU)

In the FOTsis project the focus was especially on Vehicle-Infra communication (V2I) and its potential in improving the traffic fluency and safety. In Aalto University the aspects and data regarding to traffic safety was studied.

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4D-Space – Intelligent and learning public spaces (MIDE 2010-2012)

In this project the measurement and modeling of public spaces was researched. Emerging positioning and sensor technologies were investigated. The modeling and simulation of indoors pedestrian movements was developed.

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