Truck Driving Assistance System

Abstract

Eco-driving is an effective and immediate environmental protection and energy saving method. This research assists occupational driving license training to achieve eco-driving at two parts: 1. Combine g-sensor with on board diagnostics (OBD-II) and add parameters to improve the data analysis. 2. Through two kinds of neural network models, predict fuel consumption to analyze driving style, and provide reports to display evaluation and behavior suggestions. The experimental configuration designed in this research includes user interface, OBD-II system, neural network model, and is applied to public institutions to provide assistance. The results of this study show that the accuracy of predicting fuel consumption exceeds 97%, which verifies the practicability of the system. The system will also help extend other related applications, such as achieving a driving behavior model that compares energy saving and safety.