• Home
  • Search
  • Driving Behavior Modelling with Graph Attention Networks
  • https://doi.org/10.4271/2026-26-0661Copy DOI Icon

Driving Behavior Modelling with Graph Attention Networks

  • Abstract
  • Literature Map
  • References
  • Similar Papers
Abstract

<div class="section abstract"><div class="htmlview paragraph">In automotive engineering, understanding driving behavior is crucial for decision on specifications of future system designs. This study introduces an innovative approach to modeling driving behavior using Graph Attention Networks (GATs). By leveraging spatial relationships encoded in H3 indices, a graph-based model constructed, which captures dependencies between various vehicle operational parameters and their operational regions using H3 indices. The model utilizes CAN signal features such as speed, fuel efficiency, engine temperature, and categorical identifiers of vehicle type and sub-type. Additionally, regional indices are incorporated to enrich the contextual information. The GAT model processes these heterogeneous features, learning to identify patterns indicative of driving behavior. This approach offers several significant advantages. Firstly, it enhances the accuracy of driving behavior modeling by effectively capturing the complex spatial and operational dependencies inherent in vehicle data. The use of GATs allows for the dynamic weighting of different features, ensuring that the most relevant information is prioritized in the analysis. Secondly, the integration of regional indices provides a deeper contextual understanding, enabling the model to discern region-specific driving patterns that might otherwise be overlooked. Furthermore, this method facilitates the identification of abnormal behavioral trends, offering valuable insights for design engineers. By understanding region-based driving behavior, engineers can modify vehicle systems to better meet the needs of specific areas, leading to improved performance and user satisfaction. The combination of graph-based methods with attention mechanisms represents a significant advancement in vehicle performance monitoring, paving the way for a more comprehensive understanding of driving behavior across different regions.</div></div>

Similar Papers
  • Standard
  • Citations3

Safety-Relevant Guidance for On-Road Testing of Prototype Automated Driving System (ADS)-Operated Vehicles

  • Dec 07, 2020
  • On-Road Automated Driving (Orad) Committee
  • Research Article
  • Citations1

Necessity of Body Torsional Rigidity of Personal Mobility Vehicles (PMVs) with an Inward Tilting Mechanism

  • Apr 18, 2025
  • SAE International Journal of Advances and Current Practices in Mobility
  • Tetsunori Haraguchi +1
  • Conference Article
  • Citations1

The Spiral Compressor - An Innovative Air Conditioning Compressor for the New Generation Automobiles

  • Jan 01, 1983
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Masaharu Hiraga
  • Conference Article
  • Citations53

Metal Oxide Particle Emissions from Diesel and Petrol Engines

  • Apr 16, 2012
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Andreas Mayer +4
  • Conference Article

DFSS to Design Engine Cooling System of Small Gasoline Vehicle with Rear Engine

  • Jan 09, 2019
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Chandrakant Parmar
  • Conference Article
  • Citations6

An Investigation of the Control of Tire Thump by Tire Shape

  • Jan 01, 1959
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Guy J Sanders
  • Conference Article
  • Citations4

A Feasibility Analysis of a Simple Cycle Gas Turbine Engine for Automobiles

  • Feb 01, 1972
  • SAE technical papers on CD-ROM/SAE technical paper series
  • E S Wright +2
  • Conference Article
  • Citations187

FASTSim: A Model to Estimate Vehicle Efficiency, Cost and Performance

  • Apr 14, 2015
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Aaron Brooker +5
  • Conference Article
  • Citations134

Automotive Engine Modeling for Real-Time Control Using MATLAB/SIMULINK

  • Feb 01, 1995
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Robert W Weeks +1
  • Conference Article
  • Citations2

LABORATORY QUALITIES AS PREDICTORS OF ROAD OCTANE NUMBER

  • Jan 01, 1957
  • SAE technical papers on CD-ROM/SAE technical paper series
  • I A Caputo +2
  • Conference Article
  • Citations12

Investigation on Dual Fuel Engine Gas Combustion using Tomographic In-Cylinder Measurement Technique and Simultaneous High Speed OH-Chemiluminescence Visualization

  • Oct 17, 2016
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Fridolin Unfug
  • Conference Article
  • Citations5

A User-Centered Design Exploration of Fully Autonomous Vehicles’ Passenger Compartments for At-Risk Populations

  • Apr 03, 2018
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Johnell O Brooks +4
  • Conference Article
  • Citations4

A First Look at Android Automotive Privacy

  • Apr 11, 2023
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Mert D Pese
  • Conference Article

Some Factors Controlling Part-Load Economy

  • Jan 01, 1938
  • SAE technical papers on CD-ROM/SAE technical paper series
  • Hector Rabezzana
  • Conference Article
  • Citations2

MECHANICAL FRICTION AS AFFECTED BY THE LUBRICANT

  • Jan 01, 1924
  • SAE technical papers on CD-ROM/SAE technical paper series
  • L H Pomeroy
Cactus Communications logo

Copyright 2026 Cactus Communications. All rights reserved.