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Driving Style Clustering using Naturalistic Driving Data

https://doi.org/10.1177/0361198119845360
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Principal Component Analysis
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Multivariate Analysis
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Short-term effects of training in economical driving: Passenger comfort and driver acceleration behavior
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Introducing a multivariate model for predicting driving performance: The role of driving anger and personal characteristics
inferredcites →https://doi.org/10.1016/j.patrec.2009.09.011openalex-snapshot
Data clustering: 50 years beyond K-means
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In-vehicle data recorders for monitoring and feedback on drivers’ behavior
inferredcites →https://doi.org/10.1016/j.trc.2018.03.018openalex-snapshot
Utilizing naturalistic driving data for in-depth analysis of driver lane-keeping behavior in rain: Non-parametric MARS and parametric logistic regression modeling approaches
inferredcites →https://doi.org/10.1016/j.trf.2016.05.005openalex-snapshot
Objective metrics of comfort: Developing a driving style for highly automated vehicles
inferredcites →https://doi.org/10.1016/j.trf.2017.06.004openalex-snapshot
How to define the accident risk level of car drivers by combining objective and subjective measures of driving style
inferredcites →https://doi.org/10.1016/j.trf.2018.02.036openalex-snapshot
Comfort in automated driving: An analysis of preferences for different automated driving styles and their dependence on personality traits
inferredcites →https://doi.org/10.1016/s0001-4575(00)00021-xopenalex-snapshot
Self-reports of safe driving behaviors in relationship to sex, age, education and income in the US adult driving population
inferredcites →https://doi.org/10.1016/s0001-4575(00)00102-0openalex-snapshot
An instrumented vehicle assessment of problem behavior and driving style:
inferredcites →https://doi.org/10.1016/s0001-4575(03)00010-1openalex-snapshot
The multidimensional driving style inventory—scale construct and validation
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1080/00140139008925335openalex-snapshot
Errors and violations on the roads: a real distinction?
inferredcites →https://doi.org/10.1080/00140139308967925openalex-snapshot
Decision-making style, driving style, and self-reported involvement in road traffic accidents
inferredcites →https://doi.org/10.1080/00140139508925284openalex-snapshot
Speeding in relation to perceptions of risk, utility and driving style by British company car drivers
inferredcites →https://doi.org/10.1093/bioinformatics/btg038openalex-snapshot
Bagging to improve the accuracy of a clustering procedure
inferredcites →https://doi.org/10.1177/001316446002000116openalex-snapshot
The Application of Electronic Computers to Factor Analysis
inferredcites →https://doi.org/10.1177/0018720815591313openalex-snapshot
A Review of Research on Driving Styles and Road Safety
inferredcites →https://doi.org/10.1198/106186006x94072openalex-snapshot
Unsupervised Learning With Random Forest Predictors
inferredcites →https://doi.org/10.15837/ijccc.2010.5.2221openalex-snapshot
Driving Style Analysis Using Data Mining Techniques
inferredcites →https://doi.org/10.17226/22362openalex-snapshot
Naturalistic Driving Study: Technical Coordination and Quality Control
inferredcites →https://doi.org/10.2307/2290430openalex-snapshot
Finding Groups in Data: An Introduction to Cluster Analysis.
inferredcites →https://doi.org/10.3141/2248-04openalex-snapshot
Age and Gender Differences in Overtaking Maneuvers on Two-Lane Rural Highways

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Generation of a Reduced, Representative, Virtual Test Drive for Fast Evaluation of Tire Wear by Clustering of Driving Data
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Consistency Analysis of Driving Style Classification Based on Subjective Evaluation and Objective Driving Behavior
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The Real Sorting Hat – Identifying Driving and Scanning Strategies in Urban Intersections with Cluster Analysis
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Distance-Based Speed Prediction Models Using Naturalistic Driving Data on Two-Lane Roads in Mountainous Regions
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Identify aggressive longitudinal driving behavior of heavy goods vehicle drivers based on naturalistic driving data
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DP and DS-LCD: A New Lane Change Decision Model Coupling Driver’s Psychology and Driving Style
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Lane-Changing Decision Intention Prediction of Surrounding Drivers for Intelligent Driving
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Lane Change Style Identification for Natural Driving Environments
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Driver Profile Modeling Based on Driving Style, Personality Traits, and Mood States
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Trajectory Prediction of High-Speed Train Based on GMM-LSTM
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Driving Performance Evaluation based on Driving Volatility Measures – A Case Study on Indian Drivers
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Exploring the Influence of Driving Context on Lateral Driving Style Preferences: A Simulator-Based Study
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Identification of Out-of-the-Normal Driving Behaviors Using Instantaneous Driving Decisions—A Case-Study on Indian Drivers
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A Review of Driving Style Recognition Methods From Short-Term and Long-Term Perspectives
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Cooperative Driving of Connected Autonomous Vehicles in Heterogeneous Mixed Traffic: A Game Theoretic Approach
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Situation Awareness for Driver-Centric Driving Style Adaptation
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What Driving Says About You: A Small-Sample Exploratory Study Between Personality and Self-Reported Driving Style Among Young Male Drivers
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Research on Car-Following Model considering Driving Style
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Comparing Subjective Similarity of Automated Driving Styles to Objective Distance-Based Similarity
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Model for Predicting Lateral Shifts and Driving Style of Motorized Two-Wheelers
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Research on driving proneness in car-following behaviours based on multi-source real driving data
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Intra-trip driving style variability: influences of traffic conditions and parking durations using high-frequency vehicle data
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Can Digital Road Safety Campaigns Nudge Sustained Safer Riding? Evidence from Behavioural Segmentation of Two-Wheeler Riders using Naturalistic Riding Data
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Behavior Analysis and Modeling of Traffic Participants
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DriverSVT: Smartphone-Measured Vehicle Telemetry Data for Driver State Identification
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Machine Learning-Based Driving Style Identification of Truck Drivers in Open-Pit Mines
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Modeling the Impact of Driving Styles on Crash Severity Level Using SHRP 2 Naturalistic Driving Data
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