- Alessandrini, A., Cattivera, A., Filippi, F., & Ortenzi, F. "Driving style influence on car CO2 emissions," 2012 International Emission Inventory Conference. , 2012.
- Androsensor mobile application (2021).
https://cafebazaar.ir/app/com.fivasim.androsensor?l=en last access : 2021/12.
- Austroads, "Horizontal curve tables for general road design," 2011.
- Bilgiç, T., & Türkşen, I. B. Measurement of membership functions: theoretical and empirical work. In Fundamentals of fuzzy sets (pp. 195-227). Springer US.2000.
- C. B. A. Jarque, "Efficient tests for normality homoscedasticity and serial independence of regression residuals," Econometric Letters 6, pp. 255-259, 1980.
- C. Troncoso, G. Danezis, E. Kosta, J. Balasch and B. Preneel, "PriPAYD: Privacy-Friendly Pay-As-You-Drive Insurance", IEEE Transactions on Dependable and Secure Computing, vol. 8, no. 5, pp. 742-755, 2011.
- Castrogiovanni, P., Fadda, E., Perboli, G., & Rizzo, A. (2020). Smartphone data classification technique for detecting the usage of public or private transportation modes. IEEE Access, 8, 58377-58391.
- Chaovalit, P., Saiprasert, C., & Pholprasit, T. A method for driving event detection using SAX on smartphone sensors. In ITS Telecommunications (ITST), 2013 13th International Conference on (pp. 450-455). IEEE, 2013.
- Dabiri, S., & Heaslip, K. (2018). Inferring transportation modes from GPS trajectories using a convolutional neural network. Transportation Research Part C:Emerging Technologies, 86, 360–371.
- Deffenbacher, J. L., Oetting, E. R., & Lynch, R. S. (1994). Development of a driving anger scale. Psychological Reports, 74(1), 83–91.
- Eftekhari, H. R., & Ghatee, M. (2016). An inference engine for smartphones to preprocess data and detect stationary and transportation modes. Transportation Research Part C: Emerging Technologies, 69, 313-327.
- Eftekhari, H. R., & Ghatee, M. (2018). Hybrid of discrete wavelet transform and adaptive neuro fuzzy inference system for overall driving behavior recognition. Transportation research part F: traffic psychology and behaviour, 58, 782-796.
- Fazeen, M., Gozick, B., Dantu, R., Bhukhiya, M., & González, M. C. Safe driving using mobile phones. Intelligent Transportation Systems, IEEE Transactions on, 13(3), 1462-1468, 2012.
- Gjoreski, M., Janko, V., Slapničar, G., Mlakar, M., Reščič, N., Bizjak, J., ... & Gams, M. (2020). Classical and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors. Information Fusion, 62, 47-62.
- H. F. Durrant-Whyte, "Sensor models and multisensor integration," The International Journal of Robotics Research 7.6 , pp. 97-113, 1988.
- Hennessy, D.A. and Wiesenthal, D.L., (1997). “The relationship between traffic congestion, driver stress and direct versus indirect coping behaviors”. Ergonomics, 40(3), pp.348-36.
- Hickman, Jeffrey S., and E. Scott Geller, "Self-management to increase safe driving among short-haul truck drivers," Journal of Organizational Behavior Management 23.4, 2005.
- J. Paetz, "A note on core regions of membership functions," in Proc. of the 2nd Europ. Symp. on Intelligent Technologies, Hybrid Systems and their Implementation on Smart Adaptive Systems, Albufeira, Portugal, 2002.
- Johnson, D., & Trivedi, M. M. "Driving style recognition using a smartphone as a sensor platform." In Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on, pp. 1609-1615. IEEE, 2011.
- Makrehchi, M., Basir, O., & Kamel, M., "Generation of fuzzy membership function using information theory measures and genetic algorithm.," IEEE Transaction on Fuzzy Systems, p. pages 603–610, 2003.
- N. H. Derbel, "Membership Functions Generation Based on Density Function," in International Conference on Computational Intelligence and Security, 2008.
- NCHRP, "A Guide for Addressing Aggressive-Driving Collisions," National Cooperative Highway Research Program,Report 500,Volume 1, 2003.
- Promwongsa, N., Chaisatsilp, P., Supakwong, S., Saiprasert, C., Pholprasit, T., & Prathombutr, P. (2014). Automatic accelerometer reorientation for driving event detection using smartphone. In In13th ITS Asia Pacific Forum, Auckland, New Zealand, 2014 Apr.
- Vaiana, R., Iuele, T., Astarita, V., Caruso, M. V., Tassitani, A., Zaffino, C., & Giofrè, V. P. "Driving behavior and traffic safety: an acceleration-based safety evaluation procedure for smartphones." Modern Applied Science 8, no. 1: p88. 2014.
- Wahlström, J., Skog, I., & Händel, P. (2017). Smartphone-based vehicle telematics: A ten-year anniversary. IEEE Transactions on Intelligent Transportation Systems, 18, 2802–2825.
- Wouters, P. I., & Bos, J. M., "Traffic accident reduction by monitoring driver behaviour with in-car data recorders," Accident Analysis & Prevention 32.5: 643-650., 2000.
- Yuniar, D., Djakfar, L., Wicaksono, A., & Efendi, A. (2020). Truck driver behavior and travel time effectiveness using smart GPS. Civil Engineering Journal, 6(4), 724-732.
- Zhang, H., & Fu, R. (2021). An Ensemble Learning-Online Semi-Supervised Approach for Vehicle Behavior Recognition. IEEE Transactions on Intelligent Transportation Systems.