scispace - formally typeset
Proceedings ArticleDOI

Profiling of automobile drivers using car games

Reads0
Chats0
TLDR
In this paper, car games are used as a simulator for real automobiles, and driving logs that contain the vehicle data, which includes values for parameters like gear used, speed, left turns taken, right Turns taken, accelerator, braking and so on are generated.
Abstract
In this paper we use car games as a simulator for real automobiles, and generate driving logs that contain the vehicle data. This includes values for parameters like gear used, speed, left turns taken, right turns taken, accelerator, braking and so on. From these parameters we have derived some more additional parameters and analyzed them. As the input from automobile driver is only routine driving, no explicit feedback is required; hence there are more chances of being able to accurately profile the driver. Experimentation and analysis from this logged data shows possibility that driver profiling can be done from vehicle data. Since the profiles are unique, these can be further used for a wide range of applications and can successfully exhibit typical driving characteristics of each user.

read more

Citations
More filters
Proceedings ArticleDOI

Driver Profiling Using Realistic Racing Games

TL;DR: This work attempts to identify drivers based on this characteristic driving profile of humans operating vehicles with several in-puts such as Support Vector Machine, K Nearest Neighbour, KNN and Naive Bayes.
Book ChapterDOI

A Novel Proof of Concept for Twitter Analytics Using Popular Hashtags: Experimentation and Evaluation

TL;DR: This work retrieved real-time twitter data pertaining to three currently popular hashtags in the Indian context and carried out extensive experimentation analysis about the prevailing sentiment of a strata of population.
Book ChapterDOI

Investigating the Impact of Data Analysis and Classification on Parametric and Nonparametric Machine Learning Techniques: A Proof of Concept

TL;DR: In this paper, the performance of four popular machine learning classification algorithms (Naive Bayes, decision trees, logistic regression, and random forest) on two popular benchmarked datasets (wine quality dataset and glass identification dataset) is compared.
References
More filters
Book

Data Mining: Concepts and Techniques

TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.

Data Mining: Concepts and Techniques (2nd edition)

TL;DR: There have been many data mining books published in recent years, including Predictive Data Mining by Weiss and Indurkhya [WI98], Data Mining Solutions: Methods and Tools for Solving Real-World Problems by Westphal and Blaxton [WB98], Mastering Data Mining: The Art and Science of Customer Relationship Management by Berry and Linofi [BL99].
Journal ArticleDOI

In-Vehicle Data Recorder for Evaluation of Driving Behavior and Safety

TL;DR: The overall framework and components of an in-vehicle data recorder (IVDR) called DriveDiagnostics is described and results from a study to validate its performance are presented and show significant correlations between the two data sets.
Journal ArticleDOI

Soft biometrics for keystroke dynamics: Profiling individuals while typing passwords

TL;DR: A new profiling approach of individuals based on soft biometrics for keystroke dynamics based on the hand category, gender category, age category and the handedness category is presented.
Related Papers (5)