Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications A Review


The Behaviour Prediction Function of an Autonomous Vehicle is Responsible for Making Predictions Regarding the Future States of Other Vehicles in the Area Based on Current and Previous Observations of the Surrounding Environment. This helps them become more aware of the potential dangers that are nearby. However, conventional solutions for behavior prediction can be used in straightforward driving situations that call for limited time horizons for their predictions. In recent years, Deep Learning-based strategies have gained popularity as a result of their promising performance in more complex environments when compared to conventional strategies. This is due to the fact that Deep Learning strategies were originally developed by Google. In this article, we provide a comprehensive review of the state-of-the-art of Deep Learning-based approaches for predicting how a vehicle will behave. Our motivation for doing so comes from the growing popularity of this technique. First, we provide an overview of the more general problem of predicting vehicle behavior and discuss the difficulties associated with it. Next, we classify and review the most recent Deep Learning-based solutions based on three criteria: the representation of the input data, the type of output data, and the method of prediction. Additionally, the performance of several well-known solutions is discussed in this article, along with the identification of research gaps in the existing literature and an outline of potential new directions for research.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : SchrodinText: Strong Protection of Sensitive Textual Content of Mobile Applications ABSTRACT: A large number of mobile applications deliver and display sensitive and private textual content to users. Examples of
PROJECT TITLE : Predictive Auto-scaling of Multi-tier Applications Using Performance Varying Cloud Resources ABSTRACT: The performance of the same kind of cloud resources, such as virtual machines (VMs), can change over time for
PROJECT TITLE : Fast Multi-Criteria Service Selection for Multi-User Composite Applications ABSTRACT: Paradigms such as Software as a Service (SaaS) and Service-Based Systems (SBSs), which are becoming more prevalent as cloud
PROJECT TITLE : Energy-aware cloud workflow applications scheduling with geo-distributed data ABSTRACT: The cost of electricity shifts during the course of the day and varies from one geographic location to another. Workflow applications
PROJECT TITLE : User-Centric Interference-Aware Load Balancing for Cloud-Deployed Applications ABSTRACT: Virtual machines that are hosted in cloud environments are more likely to experience performance issues as a result of the

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry