Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey

Driver driving style plays an important role in vehicle energy management as well as driving safety. Furthermore, it is key for advance driver assistance systems development, toward increasing levels of vehicle automation. This fact has motivated numerous research and development efforts on driving style identification and classification. This paper provides a survey on driving style characterization and recognition revising a variety of algorithms, with particular emphasis on machine learning approaches based on current and future trends. Applications of driving style recognition to intelligent vehicle controls are also briefly discussed, including experts’ predictions of the future development.

[1]  Mohan M. Trivedi,et al.  Driver Behavior and Situation Aware Brake Assistance for Intelligent Vehicles , 2007, Proceedings of the IEEE.

[2]  M. Akamatsu,et al.  Indices for characterizing driving style and their relevance to car following behavior , 2007, SICE Annual Conference 2007.

[3]  Kazuya Takeda,et al.  Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification , 2007, Proceedings of the IEEE.

[4]  Eckehard Steinbach,et al.  Android Smartphone Application for Driving Style Recognition Android Smartphone Applikation für Fahrstilerkennung , 2013 .

[5]  Ram Dantu,et al.  Safe Driving Using Mobile Phones , 2012, IEEE Transactions on Intelligent Transportation Systems.

[6]  Fei-Yue Wang,et al.  Data-Driven Intelligent Transportation Systems: A Survey , 2011, IEEE Transactions on Intelligent Transportation Systems.

[7]  Keiichi Uchimura,et al.  Driver inattention monitoring system for intelligent vehicles: A review , 2009 .

[8]  Reza Langari,et al.  Intelligent energy management agent for a parallel hybrid vehicle , 2003, Proceedings of the 2003 American Control Conference, 2003..

[9]  Joonwoo Son,et al.  Relationships between Driving Style and Fuel Consumption in Highway Driving , 2011 .

[10]  Guido Lenaers,et al.  Real Life CO 2 Emission and Consumption of Four Car Powertrain Technologies Related to Driving Behaviour and Road Type , 2009 .

[11]  F. Wang,et al.  Scanning the Issue and Beyond: Parallel Driving With Software Vehicular Robots for Safety and Smartness , 2014, IEEE Trans. Intell. Transp. Syst..

[12]  A. Augustynowicz.  Preliminary classification of driving style with objective rank method , 2009 .

[13]  Rosaldo J. F. Rossetti,et al.  Playing Transportation Seriously: Applications of Serious Games to Artificial Transportation Systems , 2013, IEEE Intelligent Systems.

[14]  Stefan Rass,et al.  A Game-Theoretic Approach to Co-operative Context-Aware Driving with Partially Random Behavior , 2008, EuroSSC.

[15]  Hong Jiang,et al.  Establishing Style-Oriented Driver Models by Imitating Human Driving Behaviors , 2015, IEEE Transactions on Intelligent Transportation Systems.

[16]  Frank Gauterin,et al.  Online driving style recognition using fuzzy logic , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[17]  Mara Tanelli,et al.  Quantitative Driving Style Estimation for Energy-Oriented Applications in Road Vehicles , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[18]  Jianbo Lu,et al.  Real-time driving behavior identification based on driver-in-the-loop vehicle dynamics and control , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[19]  A. Reig,et al.  Modelling driving behaviour and its impact on the energy management problem in hybrid electric vehicles , 2014, Int. J. Comput. Math..

[20]  Angelos Amditis,et al.  Online prediction of an electric vehicle remaining range based on regression analysis , 2014, 2014 IEEE International Electric Vehicle Conference (IEVC).

[21]  Hai Yu,et al.  Driving pattern identification for EV range estimation , 2012, 2012 IEEE International Electric Vehicle Conference.

[22]  Stefan Byttner,et al.  Data-Driven Methods for Classification of Driving Styles in Buses , 2012 .

[23]  Alex Pentland,et al.  Modeling and Prediction of Human Behavior , 1999, Neural Computation.

[24]  Fei-Yue Wang,et al.  Parallel Control and Management for Intelligent Transportation Systems: Concepts, Architectures, and Applications , 2010, IEEE Transactions on Intelligent Transportation Systems.

[25]  Jonghan Oh,et al.  The Flexible EV/HEV and SOC Band Control Corresponding to Driving Mode, Driver's Driving Style and Environmental Circumstances , 2012 .

[26]  Yi Lu Murphey,et al.  Driver's style classification using jerk analysis , 2009, 2009 IEEE Workshop on Computational Intelligence in Vehicles and Vehicular Systems.

[27]  Nanning Zheng,et al.  Cognitive Cars: A New Frontier for ADAS Research , 2012, IEEE Transactions on Intelligent Transportation Systems.

[28]  M. Mikulincer,et al.  The multidimensional driving style inventory--scale construct and validation. , 2004, Accident; analysis and prevention.

[29]  Dimitar Filev,et al.  Adaptive real-time advisory system for fuel economy improvement in a hybrid electric vehicle , 2009, NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society.

[30]  Samuel Madden,et al.  Drivers' Adaptation to Adaptive Cruise Control: Examination of Automatic and Manual Braking , 2012 .

[31]  Fazal Urrahman Syed,et al.  Design and Analysis of an Adaptive Real-Time Advisory System for Improving Real World Fuel Economy in a Hybrid Electric Vehicle , 2010 .

[32]  Ying Tan,et al.  An Intelligent Multifeature Statistical Approach for the Discrimination of Driving Conditions of a Hybrid Electric Vehicle , 2011, IEEE Transactions on Intelligent Transportation Systems.

[33]  Eva Ericsson,et al.  Independent driving pattern factors and their influence on fuel-use and exhaust emission factors , 2001 .

[34]  Eric Wood,et al.  Accounting for the Variation of Driver Aggression in the Simulation of Conventional and Advanced Vehicles , 2013 .

[35]  陈虹,et al.  Switching-Based Stochastic Model Predictive Control Approach for Modeling Driver Steering Skill , 2015 .

[36]  Srdjan M. Lukic,et al.  Review of driving conditions prediction and driving style recognition based control algorithms for hybrid electric vehicles , 2011, 2011 IEEE Vehicle Power and Propulsion Conference.

[37]  Mohan M. Trivedi,et al.  Examining the impact of driving style on the predictability and responsiveness of the driver: Real-world and simulator analysis , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[38]  Shuo Zhang,et al.  Adaptive energy management of a plug-in hybrid electric vehicle based on driving pattern recognition and dynamic programming , 2015 .

[39]  Mohan M. Trivedi,et al.  Driving style recognition using a smartphone as a sensor platform , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[40]  Mohan M. Trivedi,et al.  Driver classification and driving style recognition using inertial sensors , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[41]  Yangsheng Xu,et al.  On the fidelity of human skill models , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[42]  Andrew McGordon,et al.  An investigation on the effect of driver style and driving events on energy demand of a PHEV , 2012 .

[43]  Alicia L. Carriquiry,et al.  Driving behavior at a roundabout: A hierarchical Bayesian regression analysis , 2014 .

[44]  Paulius Lengvenis,et al.  Driving style classification using long-term accelerometer information , 2014, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR).

[45]  Monica Vladoiu,et al.  Driving Style Analysis Using Data Mining Techniques , 2010, Int. J. Comput. Commun. Control.

[46]  Junqiang Xi,et al.  Modeling and Recognizing Driver Behavior Based on Driving Data: A Survey , 2014 .

[47]  Angelos Amditis,et al.  Driving style recognition for co-operative driving: a survey , 2014 .

[48]  Jianqiang Wang,et al.  Stability and Scalability of Homogeneous Vehicular Platoon: Study on the Influence of Information Flow Topologies , 2016, IEEE Transactions on Intelligent Transportation Systems.

[49]  Sergio M. Savaresi,et al.  Driving style estimation via inertial measurements , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[50]  Kanok Boriboonsomsin,et al.  Dynamic Eco-Driving for Signalized Arterial Corridors and Its Indirect Network-Wide Energy/Emissions Benefits , 2013, J. Intell. Transp. Syst..

[51]  Hao Ying,et al.  Fuzzy Rule-Based Driver Advisory System for Fuel Economy Improvement in a Hybrid Electric Vehicle , 2007, NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society.

[52]  Huei Peng,et al.  Driving Pattern Recognition for Control of Hybrid Electric Trucks , 2004 .

[53]  Rubiyah Yusof,et al.  A review on the applications of driving data and traffic information for vehicles׳ energy conservation , 2014 .

[54]  Fei-Yue Wang,et al.  Agent-based control strategies for smart and safe vehicles , 2005, IEEE International Conference on Vehicular Electronics and Safety, 2005..

[55]  Jeremy Neubauer,et al.  Thru-life impacts of driver aggression, climate, cabin thermal management, and battery thermal management on battery electric vehicle utility , 2014 .

[56]  Chris Bingham,et al.  Impact of driving characteristics on electric vehicle energy consumption and range , 2012 .

[57]  Eva Ericsson,et al.  Variability in urban driving patterns , 2000 .

[58]  Jukka Riekki,et al.  Personalised assistance for fuel-efficient driving , 2015 .

[59]  Hao Ying,et al.  Real time Advisory System for Fuel Economy Improvement in a Hybrid Electric Vehicle , 2008, NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society.

[60]  Hermann Winner,et al.  Three Decades of Driver Assistance Systems: Review and Future Perspectives , 2014, IEEE Intelligent Transportation Systems Magazine.