Assessing the impacts of driving environment on driving behavior patterns

  • Marta V. FariaEmail author
  • Patrícia C. Baptista
  • Tiago L. Farias
  • João M. S. Pereira


Considering the role of behavioral and environmental factors on road accidents and traffic intensities, the characterization of vehicle use and driver behavior opens new opportunities for safety improvements and energy savings. Thus, the objective of this work was to identify driving behavior patterns for several driving environments (based on street level and weather conditions) from real-world driving data and to analyze how these driving environments influenced driving behavior. The case study for this work was Lisbon, Portugal, where driving data from 47 drivers were collected with on-board data loggers for at least 6 months. The results show that both street level and weather conditions impact driving behavior significantly. However, while for rainy conditions, the results provide evidence that drivers tend to drive more calmly (average speed is 22% lower for heavy rain than without rain, while positive and negative accelerations decrease by 8% and 11%, respectively), when considering the influence of street level more local streets (level 2, 3 and 4 streets) are the ones that present more aggressive driving patterns in terms of acceleration (30–40% increase from level 1 to level 4 streets). This work contribution regards the quantification of the impacts of driving environment on driving behavior, providing evidence that rain conditions significantly affect driving behavior, leading drivers to adjust their driving behavior to the driving environment. However, regarding street level, the differences found in driving behavior seem to be more a consequence of the infrastructure characteristics than an adjustment of driving behavior.


Driving environment Driving behavior Weather conditions Street function ICT Real-world data 



The authors acknowledge Fundação para a Ciência e Tecnologia for the Doctoral (PD/BD/105714/2014) financial support, as well as a project grant (SusCity Project, MITP-TB/C S/0026/2013). This work was also supported by Fundação para a Ciência e Tecnologia, through IDMEC, under LAETA, project UID/EMS/50022/2013 and through IN+, Strategic Project UID/EEA/50009/2013. The authors would also like to acknowledge the investigation group MARETEC/LARSYS, Grupo de Previsão Numérica do Tempo (Instituto Superior Técnico, Universidade de Lisboa) for providing the meteorological data.

Authors’ contribution

MVF: Literature search and review, content planning, data analysis, manuscript writing. PCB: Content planning, data analysis, manuscript writing. TLF: Manuscript editing. JMSP: Statistical analysis, manuscript editing

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.LAETA, Department of Mechanical Engineering, IDMEC/IST, Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal
  2. 2.IN+, Center for Innovation, Technology and Policy Research – Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal
  3. 3.Laboratory of Biostatistics and Medical Informatics, IBILI – Faculty of MedicineUniversity of CoimbraCoimbraPortugal

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