Statistical Analysis of Driver Behaviour and Eco-Driving model based on CAN bus Data
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
The objective of this thesis is to analyse driving behaviour and to characterize the effectsof an efficient way of driving, termed eco-driving, that enables the driver to reduce fuelconsumption and CO2emissions.The approach used to assess driving style is a collection of data from a CAN bus of acar equipped with OBD-II (on-board diagnostic) system. The driving experiment wasperformed for nine drivers who drove in a normal way or regular driving style and onedriver was an eco-driver who drove in an economical driving style. The driving routewas approximately 18.7 kms (which took between 25 to 30 minutes) in Halmstad city,Sweden.The drivers are compared using a statistical analysis of the driving parameters such as,speed, accelerator (gas pedal) and brake pressure, which are obtained from CAN busdata. A hierarchical clustering algorithm also used to classify the drivers based on theaverage result of the signals.In the results, a driving difference between the eco-driver and the normal drivers is visi-ble, most of the normal drivers have more or less similar behaviour. The average speed ofthe eco-driver lower than the normal drivers and the accelerator (gas pedal) result is alsoshown less usage by the eco-driver than the normal drivers. On the other hand, the eco-driver has braked more often than the normal drivers, but gently. Nevertheless, differenttraffic conditions during the experiment obstructs comparisons between the drivers.
Place, publisher, year, edition, pages
2015. , 44 p.
Fuel consumption, Drivers’ behaviour, Eco-driving, Relevant driving param-eters, Driving efficiency, Clustering
Engineering and Technology
IdentifiersURN: urn:nbn:se:hh:diva-28091OAI: oai:DiVA.org:hh-28091DiVA: diva2:805166
Subject / course
Computer science and engineering
2014-12-17, E3, Halmstad, 14:00 (English)
Larsson, Tony, ProfessorByttner, Stefan, Associate Professor
Larsson, Tony, Professor