ItemArticle

ANFIS-Based Multi-Sensor Data Fusion Model for Optimized Autonomous Vehicle Navigation Using Big Data and Filtering Techniques

Title
ANFIS-Based Multi-Sensor Data Fusion Model for Optimized Autonomous Vehicle Navigation Using Big Data and Filtering Techniques
Creator
Kumar, Sanjay; Ranjan, Anand; Saxena, Surabhi; Ashish
Description
The navigation of an autonomous vehicle depends mostly on the integration of multi-sensor data from sources such as LiDAR, GPS, radar, and cameras. Issues like sensor noise, data asynchrony, and fusion inaccuracies hamper reliable real-time decision-making. This paper proposes an optimized multi-sensor data fusion framework integrating big data analytics with modern filtering techniques to increase navigation accuracy and system robustness. The proposed model integrates Kalman Filter (KF), Extended Kalman Filter (EKF), and Adaptive Neuro-Fuzzy Inference System (ANFIS) for dynamic state estimation and adaptive noise accommodation. In addition, sensor reliability and position tracking are enhanced via Bayesian data fusion and Particle Filter. Simulation results show that the proposed technique is evidently superior to existing models in accuracy (1.5 RMSE), convergence time (0.98s), and latency (50 ms). The fusion system enhances stability and responsiveness in autonomous navigation and offers an intelligent transportation framework that can be deployed efficiently at a real-time scale. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026.
Source
Mobile Networks and Applications;Volume;30;Issue;2026-04-03 00:00:00;pp.341-355
Date
01-01-2025
Publisher
Springer
Subject
Adaptive Neuro-Fuzzy inference system (ANFIS); Autonomous vehicle; Big data; Filtering technology; Kalman filter; Multi sensor
Coverage
Kumar S., KLEF College of Engineering, Department of Computer Science and Information Technology, KLEF, K L Deemed to be University, Green Fields, Vaddeswaram, Guntur District, 522302, India; Ranjan A., Department of Electronics and Communication Engineering, Faculty of Engineering andTechnology, University of Lucknow, Uttar Pradesh, Lucknow, 226021, India; Saxena S., Department of Computer Science, CHRIST University, 560 029, Karnataka, Bengaluru, India; Ashish, KLEF College of Engineering, Department of Computer Science and Information Technology, KLEF, K L Deemed to be University, Green Fields, Vaddeswaram, Guntur District, 522302, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 1383469X;
Format
online
Language
English
Type
Article

Citation

Kumar, Sanjay; Ranjan, Anand; Saxena, Surabhi; Ashish, “ANFIS-Based Multi-Sensor Data Fusion Model for Optimized Autonomous Vehicle Navigation Using Big Data and Filtering Techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/21933.

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