illustration

Research Interests
Supervised Students
Code and Data
Publications
Talks
Funding and Fellowships
Availability
Contact Information

Welcome to Nicolas Saunier's professional homepage.

I am an associate professor in transportation engineering at Polytechnique Montréal (PM) in Canada (official page). You can find my CV (in French) and a short bilingual biography.

I am a member of the Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), the Québec network for research in road safety and of Catherine Morency's research Chair on the evaluation and implementation of sustainability in transportation (MOBILITÉ Chair). I am co-head of the ITS lab of CIRRELT with Teodor Gabriel Crainic (UQàM). I am also a member of the following TRB committees: Committee on Artificial Intelligence and Advanced Computing Applications (ABJ70), Committee on Safety Data, Analysis, and Evaluation (ANB20) and Pedestrian Committee (ANF10).

Prospective Students: I am always looking for graduate students who are interested in research in transportation and computing (see my research interests: being able to prototype software to test your ideas, automate data processing and enable reproducibility is mandatory). Due to large volume of sollicitation by email, make sure to make a well articulated case for yourself and provide relevant information, or you will be ignored. Although all teaching is done in French at Polytechnique Montréal, you may write your thesis in English.

News may be provided more regularly on Twitter and this blog.

Research Interests

My research interests focus on intelligent transportation systems, road safety and information technology for transportation (data collection, processing, using machine learning techniques, and visualization).

I am interested in really intelligent transportation systems, i.e. systems that actually exhibit intelligent features such as adaptation to changing conditions with minimal supervising. Using video sensors and computer vision techniques, road users' trajectories can be extracted automatically. This rich microscopic data can then be interpreted automatically to understand road users' behaviour and analyze road safety (without waiting for accidents to happen). A robust probabilistic framework was developed for automated road safety analysis. I am also very interested in mobility in general, in particular vulnerable road users, cyclists and pedestrians (or active modes of transportation). Research on them has been typically limited, in particular in regard of their importance.

Massive amounts of data are now collected continuously in our highly connected world, from geo-location devices in common cell phones to video sensors. If this data can be automatically analyzed, there are great opportunities for a better understanding and optimization of transportation systems, from their management to user information. The field of computational transportation science is thus emerging at the intersection of computer science and transportation, to apply advanced data processing techniques to transportation. The following is a list of keywords that are relevant to my research interests:

Transportation keywords: intelligent transportation systems, road safety, surrogate safety measures, interactions, traffic conflicts (near miss), risk of collision, exposure, simulation, utility cycling, walking.
Computer science keywords: machine learning, semi-supervised learning (ref), active learning, data selection, incremental algorithms, ensemble methods (e.g. Bagging), computer vision.

Finally, I am a supporter of open science for many reasons, both from a philosophical and moral point of view, and from a practical point of view. From a philosophical and moral point of view, it is the right thing to do, especially for publicly funded research institutions and it allows reproducible research: why should you trust my claims if you cannot replicate my work? From a practical point of view, it is a better method (open source software is a better software development technique) and my research benefits from collaboration and sharing code and data with you, as you reference my research and release publicly your improvements in turn). Join the movement!

This material is Open Knowledge This material is Open Data This material is Open Content

Supervised Students

Past Students

Resources

As stated in my research interests I support open science, i.e. sharing data and code. The most important project I started is a code repository called Traffic Intelligence, containing various tools for transportation data processing, in particular an implementation of a feature-based tracking algorithm similar to our CRV paper of 2006.

Open source code

Data

Publications

I support Open Access.

Disclaimer: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be re-posted without the explicit permission of the copyright holder.

An html page exported from JabRef is available here with bibtex entries (whole bibtex file). My Google Scholar profile is here.

Talks

Funding

Research funding has been obtained from various sources, in particular the Québec Ministry of Transportation (MTQ), the Québec for Research on Nature and Technology (FRQNT), Québec Fund for Health Research (FRQS) and the Natural Sciences and Engineering Research Council of Canada (NSERC)

Past funding

Availability

Contact Information

Links

> Nicolas Saunier -- October 31st, 2015 <

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