Driving Data Classification and Analysis using Statistical Approach & Neural Network
- Resource Type
- Conference
- Authors
- Yugank, Hanumant Kumar; Kaur, Jasleen; Kaur, Sanmukh; Moulik, Bedatri
- Source
- 2021 4th International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE) Recent Developments in Control, Automation & Power Engineering (RDCAPE), 2021 4th International Conference on. :292-297 Oct, 2021
- Subject
- Aerospace
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Power engineering
Roads
Neural networks
Electric vehicles
Real-time systems
Pattern recognition
Global Positioning System
EVs
HEVs
Drive Cycle
Driving pattern
- Language
Electric Vehicle is seen as alternative of traditional vehicles. The efficiency and range of electric vehicle depends upon the driving pattern and situation. This have been discerned that the design parameter that has been heightened for the vehicle in a country, may not be applicable for other. For generating drive cycles in real time & real road scenario, we have collected data using the GPS module.In this paper we had use Neural Network and a classification using Statistical approach for recognizing driving pattern by using the representative features obtained from various parameters. Each of these parameters have been defined by Statistically analyzing different recorded drive cycle. These input parameters will help in defining the driving pattern and classification of the drive cycle.