| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 2.3 MB | Adobe PDF |
Advisor(s)
Abstract(s)
This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.
Description
Keywords
Driver profile Eco-driving Fuel efficiency Data warehouse Knowledge discovery (KD) Public transportation
Citation
FERREIRA, João Carlos; ALMEIDA, José de; SILVA, Alberto Rodrigues da - The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process. IEEE Transactions on Intelligent Transportation Systems. ISSN. 1524-9050. Vol. 16. N.º 5 (2015), pp. 2653-2662
Publisher
IEEE-Institute Electrical Electronics Engineers INC