A Study on Deep Learning Model Autonomous Driving Based on Big Data

1 Introduction

Autonomous driving combines the Internet of Things (IoT) and automotive technology using cars connected to big data. Vehicles connected via a network work the same as IoT devices and require a central management system to analyze and process the data generated by multiple terminals, hence a network-based data delivery service to efficiently deliver big data stand-alone data traffic Data provided in the form of dots in. This is a roadmap construction project to overcome the limitations of the will range of autonomous vehicles that depend on the vehicle's own sensor. Receive public traffic data and vehicle detection traffic data for service functions. Point data based on vehicle location CMR grid-based storage and analysis Provides the information needed when a vehicle is approaching a specific grid. Road safety information is provided by indexing after the creation of a real-time traffic Big Data database and a vehicle selection grid network. (Felipe Arango & Bergasa, n.d.) This project is based on ROS (Robot Operating System), an open-source framework software that provides libraries and tools for software developers to create robotic applications (Autoware, n.d.). In this article, we present the process of developing a Drive-By-Wire system designed for self-driving car prototypes. Predictive maintenance is perhaps the smartest big data use case in the automotive industry. Predictive analytics can be used to predict issues with vehicle parts in order to take timely action and improve vehicle health. Logical forecasting also proactively prevents automotive problems and service schedules are automated in a timely manner.

Figure 1.

Alpha Go and the era of autonomous vehicles

Figure 2.

Research trends

When we look at the video of Tesla's self-driving car, we can see the road condition being checked from the lane of the road in the front camera to traffic signs and vehicles and pedestrians. currently, a lot of research and remarkable achievements have been achieved in the academic world. It is not far from a point in time that deep learning technology, which is almost similar Figures 1 and 2 to human's ability to perceive visual objects, will be installed in autonomous vehicles. Deep learning used in autonomous driving is visually judged by humans, and deep learning used in autonomous driving is a technology that allows computers to judge and drive themselves when driving a car.