An online estimation of driving style using data-dependent pointer model

Abstract The paper focuses on a task of stochastic modeling the driving style and its online estimation while driving. The driving style is modeled by means of a mixture model with normal and categorical components as well as a data-dependent pointer. The mixture parameters and the actual driving style are estimated with the help of a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the online estimation of the driving style while driving, taking into account data up to the current time instant; (ii) the joint model for continuous and discrete data measured on a vehicle; (iii) the data-dependent model of the driving style conditioned by the values of fuel consumption; (iv) the use of the model both for detection of clusters according to the driving style and prediction of the fuel consumption along with other variables; and (v) the universal modeling with the help of mixtures, which allows us to use different combinations of components and pointer models as well as to specify the initialization approach suitable for the considered problem. Results of the driving style detection in real measurements and comparison with the theoretical counterparts are demonstrated.

[1]  Tomer Toledo,et al.  In-vehicle data recorders for monitoring and feedback on drivers' behavior , 2008 .

[2]  D. French,et al.  Behavioral correlates of individual differences in road-traffic crash risk: an examination method and findings. , 1993, Psychological bulletin.

[3]  Joonwoo Son,et al.  Comparative study between Korea and UK: relationship between driving style and real-world fuel consumption , 2016 .

[4]  Václav Peterka,et al.  Bayesian system identification , 1979, Autom..

[5]  Evgenia Suzdaleva,et al.  Bayesian estimation of dynamic finite mixtures , 2011 .

[6]  C. Reilly,et al.  A rapid method for the comparison of cluster analyses , 2005 .

[7]  B. Cheng,et al.  A hierarchical driver model , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[8]  Michael Burrow,et al.  Driving style for better fuel economy , 2017 .

[9]  W. Kruskal,et al.  Use of Ranks in One-Criterion Variance Analysis , 1952 .

[10]  Manfred Plöchl,et al.  Driver models in automobile dynamics application , 2007 .

[11]  Yvonne Barnard,et al.  How I reduce fuel consumption: An experimental study on mental models of eco-driving , 2015 .

[12]  Haris N. Koutsopoulos,et al.  Integrated driving behavior modeling , 2007 .

[13]  Orit Taubman-Ben-Ari,et al.  The multidimensional driving style inventory a decade later: Review of the literature and re-evaluation of the scale. , 2016, Accident; analysis and prevention.

[14]  Hongjie Ma,et al.  Effects of driving style on the fuel consumption of city buses under different road conditions and vehicle masses , 2015 .

[15]  Nir Menachemi,et al.  Associations between driving performance and engaging in secondary tasks: a systematic review. , 2014, American journal of public health.

[16]  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).

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

[18]  Joeri Van Mierlo,et al.  Impacts of electricity mix, charging profile, and driving behavior on the emissions performance of battery electric vehicles: A Belgian case study , 2015 .

[19]  Johnathon P Ehsani,et al.  Conscientious personality and young drivers' crash risk. , 2015, Journal of safety research.

[20]  Yilu Zhang,et al.  A Pattern-Recognition Approach for Driving Skill Characterization , 2010, IEEE Transactions on Intelligent Transportation Systems.

[21]  Maya R. Gupta,et al.  Theory and Use of the EM Algorithm , 2011, Found. Trends Signal Process..

[22]  Alberto Rodrigues da Silva,et al.  The Impact of Driving Styles on Fuel Consumption: A Data-Warehouse-and-Data-Mining-Based Discovery Process , 2015, IEEE Transactions on Intelligent Transportation Systems.

[23]  Orit Taubman-Ben-Ari,et al.  Parents' perceptions of the family climate for road safety. , 2015, Accident; analysis and prevention.

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

[25]  D. Kerridge.  Inaccuracy and Inference , 1961 .

[26]  Karen Sentoff,et al.  Implications of Driving Style and Road Grade for Accurate Vehicle Activity Data and Emissions Estimates , 2015 .

[27]  Feng Guo,et al.  Individual driver risk assessment using naturalistic driving data. , 2013, Accident; analysis and prevention.

[28]  James M. Keller,et al.  A possibilistic fuzzy c-means clustering algorithm , 2005, IEEE Transactions on Fuzzy Systems.

[29]  Laura Eboli,et al.  The influence of physical and emotional factors on driving style of car drivers: A survey design , 2017 .

[30]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..

[31]  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.

[32]  Y. Zou,et al.  Analyzing different functional forms of the varying weight parameter for finite mixture of negative binomial regression models , 2014 .

[33]  Miroslav Kárný,et al.  Optimized bayesian dynamic advising : theory and algorithms , 2006 .

[34]  Fridulv Sagberg,et al.  A Review of Research on Driving Styles and Road Safety , 2015, Hum. Factors.

[35]  Evgenia Suzdaleva,et al.  Data-based speed-limit-respecting eco-driving system , 2014 .

[36]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[37]  Jie Yu,et al.  A particle filter driven dynamic Gaussian mixture model approach for complex process monitoring and fault diagnosis , 2012 .

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

[39]  Vladimir Nikulin.  Driving Style Identification with Unsupervised Learning , 2016, MLDM.

[40]  Evgenia Suzdaleva,et al.  Expert-based initialization of recursive mixture estimation , 2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS).

[41]  Bo Cheng,et al.  Estimation of driving style in naturalistic highway traffic using maneuver transition probabilities , 2017 .

[42]  Thorsten Benter,et al.  Impact of driving style and road grade on gaseous exhaust emissions of passenger vehicles measured by a Portable Emission Measurement System (PEMS) , 2017 .

[43]  Josef F. Krems,et al.  Objective Metrics of Comfort: Developing a Driving Style for Highly Automated Vehicles , 2016 .

[44]  S. Eben Li,et al.  Field operational test of advanced driver assistance systems in typical Chinese road conditions: The influence of driver gender, age and aggression , 2015 .

[45]  Timo Juhani Lajunen,et al.  Self-Report Instruments and Methods , 2011 .

[46]  Junqiang Xi,et al.  Statistical Pattern Recognition for Driving Styles Based on Bayesian Probability and Kernel Density Estimation , 2016, ArXiv.

[47]  Tomer Toledo,et al.  A multidimensional intergenerational model of young males' driving styles. , 2016, Accident; analysis and prevention.

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

[49]  Petr Nedoma,et al.  Prior information in structure estimation , 2003 .

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

[51]  L. Evans,et al.  The dominant role of driver behavior in traffic safety. , 1996, American journal of public health.

[52]  Rochdi Trigui,et al.  Eco-driving: An economic or ecologic driving style? , 2014 .

[53]  Sanjay Kumar Dubey,et al.  Comparative Analysis of K-Means and Fuzzy C- Means Algorithms , 2013 .

[54]  Dominique Lord,et al.  Bayesian mixture modeling approach to account for heterogeneity in speed data , 2010 .

[55]  Andreas A. Malikopoulos,et al.  Optimization of driving styles for fuel economy improvement , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

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

[57]  Hussein Dia,et al.  An agent-based approach to modelling driver route choice behaviour under the influence of real-time information , 2002 .

[58]  Kazuya Takeda,et al.  Prediction model of driving behavior based on traffic conditions and driver types , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.

[59]  Junichi Murata,et al.  Driver-Adaptive Assist System for Avoiding Abnormality in Driving , 2007, 2007 IEEE International Conference on Control Applications.