Resumen
Taking into consideration the role of the transportation sector in terms of energy consumption and environmental impacts, the characterization of vehicle use and driver behavior opens new opportunities for energy and emissions savings. The use of information and communication technologies can potentially be a powerful driver to promote change in this sector. Considering this, the objective of this research work was to identify driving behavior patterns for several driving contexts (based on hierarchical street level and weather conditions) from real-world driving data and to assess their impacts on energy consumption. The case study for this work was the city of Lisbon, where driving data from 46 drivers were collected with on-board data loggers for at least 6 months. The analysis performed in this work provides an insight on the impacts of driving context on driving behavior and consequently on energy consumption. Both infrastructure characteristics and weather conditions were found to cause a speed reduction and an energy consumption increase. Rain intensity was found to increase energy consumption up to 16%, while regarding infrastructure characteristics, for level 4 streets, energy consumption is 54% higher than for level 1 streets. Results provide evidence that drivers tend to drive more calmly (lower speeds and acceleration patterns) for higher rain intensities compared with dry weather. However, more local streets (level 2, 3 and 4 streets) are the ones that present more aggressive driving patterns (in terms of acceleration).