Selpi Selpi

Forskare at Chalmers, Mechanics and Maritime Sciences, Vehicle Safety

Selpi is a project leader at the department of Applied Mechanics, division of Vehicle Safety. Within this division, she belongs to the research group Accident Prevention. For most days, she can be visited at SAFER. (Lindholmspiren 3, Lindholmen Science Park, Göteborg).Her research interests include understanding how drivers behave differently from one another in different situations (e.g., driving styles) and exploring the application of machine learning and data mining for analysis of large-scale naturalistic driving data.

Source: chalmers.se

Projects

2017–2019

Analysis of SHRP2 Data to Understand Normal and Abnormal Driving Behavior in Work Zones: Phase II

Selpi Selpi Vehicle Safety
Robert Thomson Vehicle Safety
Jordanka Kovaceva Vehicle Safety
Federal Highway Administration (FHWA)

2015–2016

Driver modelling and cross-cultural analysis of driving styles based on large-scale driving data

Selpi Selpi Accident Prevention
The Swedish Foundation for International Cooperation in Research and Higher Education (STINT)

2015–2016

Att bättre förstå körstil från naturalistisk kördata

Selpi Selpi Accident Prevention
Swedish Transport Administration

There might be more projects where Selpi Selpi participates, but you have to be logged in as a Chalmers employee to see them.

Publications

2017

Combining Support Vector Regression with Scaling Methods for Highway Tollgates Travel Time and Volume Predictions

Amanda Yan Lin, Mengcheng Zhang, Selpi Selpi
Proceedings of International Work-Conference on Time Series Analysis (ITISE 2017), Granada, 18-20 September 2017. Vol. 1, p. 411-421
Paper in proceedings
2017

Economics of Road Safety – What does it imply under the 2030 Agenda for Sustainable Development?

Jac Wismans, Selpi Selpi, Marie Thynell et al
10th Regional Environmentally Sustainable Transport (EST) Forum in Asia, 14-16 March 2017 in Vientiane, Lao PDR, p. 1-58
Conference contribution
2015

A Review of Research on Driving Styles and Road Safety

Fridulv Sagberg, Selpi Selpi, Giulio Bianchi Piccinini et al
Human Factors. Vol. 57 (No. 7, November 2015), p. 1248- 1275
Journal article
2015

Driving Signature Extraction

Ekim Yurtsever, Chiyomi Miyajima, Selpi Selpi et al
Paper in proceedings
2015

The effect of curve geometry on driver behaviour in curves by using naturalistic driving data

Andréa Palmberg, Jakob Imberg, Selpi Selpi et al
Paper in proceedings
2015

Mutual Recognition Methodology Development

Carol A.C. Flannagan, Paul E. Green, Kathleen D. Klinich et al
Report
2012

Deliverable D3.3: Data management in euroFOT

Selpi Selpi, Samuel Borgen, Jonas Bärgman et al
Report
2012

Investigating visually distracted driver reactions in rear-end crashes and near crashes based on 100-car study data

Henrik Lind, Selpi Selpi, Marco Dozza
In D. de Waard, N. Merat, A.H. Jamson, Y. Barnard, and O.M.J. Carsten (Eds.) (2012). Human Factors of Systems and Technology, p. 201-211
Paper in proceedings
2012

Deliverable D5.3: Final delivery of data and answers to questionnaires

Stefanie Schoch, Leandro Guidotti, Andràs Csepinszky et al
Report
2012

Deliverable D11.3: Final Report

Christoph Kessler, Aria Etemad, Giancarlo Alessandretti et al
Report
2011

Automatic real-time FACS-coder to anonymise drivers in eye tracker videos

Selpi Selpi, Torsten Wilhelm, Marcus N E Jansson et al
Proceedings of the IEEE International Conference on Computer Vision. 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011, Barcelona, 6-13 November 2011, p. 1986-1993
Paper in proceedings
2011

On data security and analysis platforms for analysis of naturalistic driving data

Jonas Bärgman, Helena Gellerman, Jordanka Kovaceva et al
Paper in proceedings
2009

Predicting functional upstream open reading frames in Saccharomyces cerevisiae

Selpi Selpi, Christopher H. Bryant, Graham Kemp et al
BMC Bioinformatics. Vol. 10, p. 451-
Journal article
2008

Using mRNA Secondary Structure Predictions Improves Recognition of Known Yeast Functional uORFs

Selpi Selpi, C. H. Bryant, Graham Kemp
Wehenkel, L., d'Alché-Buc, F., Moreau, Y. and Geurts, P. (eds.) MLSB08, The Second International Workshop on Machine Learning in Systems Biology, Brussels, 13-14 September 2008., p. 85-93
Paper in proceedings
2007

Using Inductive Logic Programming to Predict Functional Upstream Open Reading Frames in Yeast

Selpi Selpi, C. H. Bryant, Graham Kemp et al
Conference poster
2006

A First Step towards Learning which uORFs Regulate Gene Expression

Selpi Selpi, C. H. Bryant, Graham Kemp et al
Journal of integrative bioinformatics. Vol. 3 (2), p. 31-
Journal article
2005

Using the Functional Data Model to Store and Query Recursive Biological Data

Graham Kemp, Selpi Selpi, Merja Karjalainen
Workshop on Database Issues in Biological Databases (DBiBD),8-9 January 2005, Edinburgh, UK, p. 24-28
Conference contribution
2004

Pathway and Protein Interaction Data: from XML to FDM Database

Graham Kemp, Selpi Selpi
Lecture Notes in Computer Science. Vol. 2994, p. 212-219
Journal article