An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic
Volume-3 | Issue-3
Cloud Load Estimation with Deep Logarithmic Network for Workload and Time Series Optimization
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Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
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Population Based Meta Heuristics Algorithm for Performance Improvement of Feed Forward Neural Network
Volume-2 | Issue-1
Comparative Analysis of an Efficient Image Denoising Method for Wireless Multimedia Sensor Network Images in Transform Domain
Volume-3 | Issue-3
A Comprehensive Review on Power Efficient Fault Tolerance Models in High Performance Computation Systems
Volume-3 | Issue-3
An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet
Volume-3 | Issue-4
An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model
Volume-3 | Issue-3
Design of Distribution Transformer Health Management System using IoT Sensors
Volume-3 | Issue-3
Design of a Food Recommendation System using ADNet algorithm on a Hybrid Data Mining Process
Volume-3 | Issue-4
Automatic Diagnosis of Alzheimer’s disease using Hybrid Model and CNN
Volume-3 | Issue-4
Effective Prediction of Online Reviews for Improvement of Customer Recommendation Services by Hybrid Classification Approach
Volume-3 | Issue-4
Acoustic Features Based Emotional Speech Signal Categorization by Advanced Linear Discriminator Analysis
Volume-3 | Issue-4
Analysis of Statistical Trends of Future Air Pollutants for Accurate Prediction
Volume-3 | Issue-4
Identification of Electricity Threat and Performance Analysis using LSTM and RUSBoost Methodology
Volume-3 | Issue-4
Review on Data Securing Techniques for Internet of Medical Things
Volume-3 | Issue-3
Volume - 4 | Issue - 2 | june 2022
Published
16 July, 2022
In recent years, automotive industry is experiencing an unprecedented transformation with the rise of digital technologies. While in the past, acceleration, top speed, and mechanical design were the most essential factors for purchasing an automobile, electronics and software innovations define the characteristics of the future. One among such innovations is the Advanced Driver Assistance System (ADAS). This innovation is now considered as the major drive force of the automotive domain with the intelligent electronic and software architectures. ADAS is primarily designed with an objective to assist drivers by providing an alert/automate the manual tasks in any adverse conditions. ADAS functions will also have the capability to obtain the signals from roadways, Road Side Units (RSUs) and other vehicles. This research article attempts to provide a comprehensive review on the research developments and technologies used in design, development and implementation of advanced driver assistance systems. The sections included in the proposed study describe about the different ADAS methods such as adaptive and automated cruise control, smart navigation with collision warning and avoidance system, automated vehicle parking assistance and object detection. The primary goal of this research study is to achieve a collective knowledge of ADAS operational capabilities and limitations, as well as to suggest research requirements for future investigations.
KeywordsAdvanced Driver Assistance System (ADAS) warning system human machine interface crash detection collision warning and avoidance
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