International Journal of Computer Networks and Applications

Open Access Open Access  Restricted Access Subscription Access

Optimized Controller Scheme for Autonomous Navigation in Infotainment on Internet-of-Vehicles


Affiliations
1 Department of Artificial Intelligence and Machine Learning, Dayananda Sagar College of Engineering, Bengaluru, Karnataka., India
2 Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka., India
 

The infotainment system curves an innovative mechanism of essential information dissemination for ensuring driving safety and improved driving experiences. However, there are significant challenges in developing an infotainment system to fit into the operational design of advanced technology, e.g., Internet-of-Vehicle (IoV). A review of existing studies has witnessed advantages and shortcomings, especially from the perspective of navigational services. Therefore, the proposed scheme introduces a novel autonomous signal control system that can realize the navigational demands of each vehicle meeting at the intersection to offer a faster clearance in the traffic management system. Analytically designed with a collaborative cloud environment, the proposed scheme implements a novel optimized controller scheme that can operate in a decentralized manner using a Fuzzy controller system for efficient traffic management in IoV applications..

Keywords

Infotainment, Internet of Vehicle, Navigation, Signal, Traffic Management, Clearance.
User
Notifications
Font Size

  • J. Zhang, G. Lu, H. Yu, Y. Wang, and C. Yang, "Effect of the Uncertainty Level of Vehicle-Position Information on the Stability and Safety of the Car-Following Process," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 6, pp. 4944-4958, June 2022, doi: 10.1109/TITS.2020.3044623.

  • E. de Gelder et al., "Towards an Ontology for Scenario Definition for the Assessment of Automated Vehicles: An Object-Oriented Framework," in IEEE Transactions on Intelligent Vehicles, vol. 7, no. 2, pp. 300-314, June 2022, doi: 10.1109/TIV.2022.3144803.

  • B. Vinoth Kumar, P. Sivakumar, R. S. Sandhya Devi, Software Engineering for Automotive Systems-Principles and Applications, CRC Press, ISBN: 9781000548006, 1000548007, 2022

  • Z. Mahmood, Connected Vehicles in the Internet of Things-Concepts, Technologies, and Frameworks for the IoV, Springer International Publishing, ISBN: 9783030361679, 3030361675, 2020

  • K. P. Srinivasan and T. Muthuramalingam, "Design, Fabrication, and Crack Analysis of Silver Track Printed Flexible Sensor for Automobile Infotainment Application," in IEEE Sensors Journal, vol. 21, no. 12, pp. 13910-13915, 15 June 15, 2021, doi: 10.1109/JSEN.2021.3071582.

  • B. L. Nguyen, D. T. Ngo, N. H. Tran, M. N. Dao, and H. L. Vu, "Dynamic V2I/V2V Cooperative Scheme for Connectivity and Throughput Enhancement," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 2, pp. 1236-1246, Feb. 2022, doi: 10.1109/TITS.2020.3023708.

  • P. Agbaje, A. Anjum, A. Mitra, E. Oseghale, G. Bloom and H. Olufowobi, "Survey of Interoperability Challenges in the Internet of Vehicles," in IEEE Transactions on Intelligent Transportation Systems, 2022, doi: 10.1109/TITS.2022.3194413.

  • X. Xu, H. Li, W. Xu, Z. Liu, L. Yao, and F. Dai, "Artificial intelligence for edge service optimization in the Internet of Vehicles: A survey," in Tsinghua Science and Technology, vol. 27, no. 2, pp. 270-287, April 2022, doi: 10.26599/TST.2020.9010025.

  • O. S. Al-Heety, Z. Zakaria, M. Ismail, M. M. Shakir, S. Alani, and H. Alsariera, "A Comprehensive Survey: Benefits, Services, Recent Works, Challenges, Security, and Use Cases for SDN-VANET," in IEEE Access, vol. 8, pp. 91028-91047, 2020, doi: 10.1109/ACCESS.2020.2992580.

  • R. Han, Y. Wen, L. Bai, J. Liu, and J. Choi, "Age of Information Aware UAV Deployment for Intelligent Transportation Systems," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 2705-2715, March 2022, doi: 10.1109/TITS.2021.3117974.

  • A. Gholamhosseinian and J. Seitz, "A Comprehensive Survey on Cooperative Intersection Management for Heterogeneous Connected Vehicles," in IEEE Access, vol. 10, pp. 7937-7972, 2022, doi: 10.1109/ACCESS.2022.3142450.

  • H. Wu, J. Zhang, Z. Cai, F. Liu, Y. Li, and A. Liu, "Toward Energy-Aware Caching for Intelligent Connected Vehicles," in IEEE Internet of Things Journal, vol. 7, no. 9, pp. 8157-8166, Sept. 2020, doi: 10.1109/JIOT.2020.2980954.

  • Z. Xue, Y. Liu, G. Han, F. Ayaz, Z. Sheng and Y. Wang, "Two-Layer Distributed Content Caching for Infotainment Applications in VANETs," in IEEE Internet of Things Journal, vol. 9, no. 3, pp. 1696-1711, 1 February 1, 2022, doi 10.1109/JIOT.2021.3089280.

  • B. L. Nguyen, D. T. Ngo, N. H. Tran, M. N. Dao, and H. L. Vu, "Dynamic V2I/V2V Cooperative Scheme for Connectivity and Throughput Enhancement," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 2, pp. 1236-1246, Feb. 2022, doi: 10.1109/TITS.2020.3023708.

  • T. Andreica, C. -D. Curiac, C. Jichici and B. Groza, "Android Head Units vs. In-Vehicle ECUs: Performance Assessment for Deploying In-Vehicle Intrusion Detection Systems for the CAN Bus," in IEEE Access, vol. 10, pp. 95161-95178, 2022, doi: 10.1109/ACCESS.2022.3204746.

  • Y. Ni et al., "Toward Reliable and Scalable Internet of Vehicles: Performance Analysis and Resource Management," in Proceedings of the IEEE, vol. 108, no. 2, pp. 324-340, Feb. 2020, doi: 10.1109/JPROC.2019.2950349.

  • P. Sharma and H. Liu, "A Machine-Learning-Based Data-Centric Misbehavior Detection Model for Internet of Vehicles," in IEEE Internet of Things Journal, vol. 8, no. 6, pp. 4991 -4999, 15 March 15, 2021, doi: 10.1109/JIOT.2020.3035035.

  • F. Quintal and M. Lima, "HapWheel: In-Car Infotainment System Feedback Using Haptic and Hovering Techniques," in IEEE Transactions on Haptics, vol. 15, no. 1, pp. 121-130, 1 Jan.-March 2022, doi: 10.1109/TOH.2021.3095763.

  • X. Wang, S. Han, L. Yang, T. Yao, and L. Li, "Parallel Internet of Vehicles: ACP-Based System Architecture and Behavioral Modeling," in IEEE Internet of Things Journal, vol. 7, no. 5, pp. 3735 -3746, May 2020, doi: 10.1109/JIOT.2020.2969693.

  • G. J. Dimitrakopoulos and I. E. Panagiotopoulos, "In-Vehicle Infotainment Systems: Using Bayesian Networks to Model Cognitive Selection of Music Genres," in IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 11, pp. 6900-6909, Nov. 2021, doi: 10.1109/TITS.2020.2997003.

  • H. Vasudev, V. Deshpande, D. Das and S. K. Das, "A Lightweight Mutual Authentication Protocol for V2V Communication in Internet of Vehicles," in IEEE Transactions on Vehicular Technology, vol. 69, no. 6, pp. 6709-6717, June 2020, doi: 10.1109/TVT.2020.2986585.

  • S. Kassir, G. de Veciana, N. Wang, X. Wang, and P. Palacharla, "Analysis of Opportunistic Relaying and Load Balancing Gains Through V2V Clustering," in IEEE Transactions on Vehicular Technology, vol. 71, no. 9, pp. 9896-9911, Sept. 2022, doi: 10.1109/TVT.2022.3178129.

  • C. Sonmez, C. Tunca, A. Ozgovde, and C. Ersoy, "Machine Learning-Based Workload Orchestrator for Vehicular Edge Computing," in IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 4, pp. 2239-2251, April 2021, doi: 10.1109/TITS.2020.3024233.

  • L. Leonardi, L. L. Bello, and G. Patti, "Bandwidth Partitioning for Time-Sensitive Networking Flows in Automotive Communications," in IEEE Communications Letters, vol. 25, no. 10, pp. 3258-3261, Oct. 2021, doi: 10.1109/LCOMM.2021.3103004.

  • D. Maffiola, S. Longari, M. Carminati, M. Tanelli, and S. Zanero, "GOLIATH: A Decentralized Framework for Data Collection in Intelligent Transportation Systems," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, pp. 13372-13385, Aug. 2022, doi: 10.1109/TITS.2021.3123824.

  • K. Tan, D. Bremner, J. Le Kernec, Y. Sambo, L. Zhang, and M. A. Imran, "Intelligent Handover Algorithm for Vehicle-to-Network Communications With Double-Deep Q-Learning," in IEEE Transactions on Vehicular Technology, vol. 71, no. 7, pp. 7848-7862, July 2022, doi: 10.1109/TVT.2022.3169804.

  • F. Fu, Y. Kang, Z. Zhang, F. R. Yu and T. Wu, "Soft Actor–Critic DRL for Live Transcoding and Streaming in Vehicular Fog-Computing-Enabled IoV," in IEEE Internet of Things Journal, vol. 8, no. 3, pp. 1308-1321, 1 February 1, 2021, doi: 10.1109/JIOT.2020.3003398.

  • K. N. Qureshi, M. M. Idrees, J. Lloret, and I. Bosch, "Self-Assessment Based Clustering Data Dissemination for Sparse and Dense Traffic Conditions for Internet of Vehicles," in IEEE Access, vol. 8, pp. 10363-10372, 2020, doi: 10.1109/ACCESS.2020.2964530.

  • G. Choi, K. Lim and S. B. Pan, "Driver Identification System Using 2D ECG and EMG Based on Multistream CNN for Intelligent Vehicle," in IEEE Sensors Letters, vol. 6, no. 6, pp. 1-4, June 2022, Art no. 6001904, doi: 10.1109/LSENS.2022.3175787.

  • A. Gagliardi, V. Staderini and S. Saponara, "An Embedded System for Acoustic Data Processing and AI-Based Real-Time Classification for Road Surface Analysis," in IEEE Access, vol. 10, pp. 63073-63084, 2022, doi: 10.1109/ACCESS.2022.3183116.

  • N. Zaeri, "A heterogeneous short-range communication platform for the Internet of Vehicles," International Journal of Electrical and Computer Engineering, Vol.11, No.3, June-2021, pp. 2165~2177.DOI: 10.11591/ijece.v11i3.pp2165-2177

  • L. Kristiana, A. R. Darlis, I. A. Dewi, "The feasibility of obstacle awareness forwarding scheme in a visible light communication vehicular network," International Journal of Electrical and Computer Engineering, Vol.10, No.6, December-2020, pp. 6453~6460, DOI: 10.11591/ijece.v10i6.pp6453-6460

  • K. Ahed, M. Benamar, R. El Ouazzan, "The impact of channel model on the performance of distance-based schemes in vehicular named data networks," International Journal of Electrical and Computer Engineering, Vol. 12, No. 5, October 2022, pp. 5279~5290, DOI:10.11591/ijece.v12i5.pp5279-5290

  • T. Mouad, L. M. Driss, K. Mustapha, "Big data traffic management in a vehicular ad-hoc network," International Journal of Electrical and Computer Engineering, Vol.11, No.4, August 2021, pp. 3483~3491, DOI: 10.11591/ijece.v11i4.pp3483-3491

  • S. Ahn, J. Choi, "Internet of Vehicles and Cost-Effective Traffic Signal Control," MDPI-Sensors, vol.19, No.6, 2019, DOI: https://doi.org/10.3390/s19061275

  • J.H. Gomez, J. D. Romo, R.S. Cebrera, A.P. de la Cruz, J.M. M. Molina, "Traffic Signal Control System Based on Intelligent Transportation System and Reinforcement Learning," MDPI-Electronics, vol.10, no.19, 2021, DOI: ttps://doi.org/10.3390/electronics10192363

  • W-H Lee, C-Y Chiu, "Design and Implementation of a Smart Traffic Signal Control System for Smart City Applications," MDPI-Sensors, Vol.20, No.2, 2020, DOI: https://doi.org/10.3390/s20020508 How to cite this article:

  • J. Alarcon, I. Balcazar, C.A. Collazos, H. Luna, F. Moreira, "User Interface Design Patterns for Infotainment Systems Based on Driver Distraction: A Colombian Case Study," MDPI-sustainability, vol.14, no.13, 2022, DOI: https://doi.org/10.3390/su14138186

  • S. Reshma, C. Chetanaprakash, "Advancement in infotainment system in the automotive sector with vehicular cloud network and current state of the art," International Journal of Electrical and Computer Engineering, vol.10, No.2, pp.2077-2087, 2020, DOI: http://doi.org/10.11591/ijece.v10i2.pp2077-2087

  • S. Reshma, C. Chetanaprakash, "Framework of Infotainment using Predictive Scheme for Traffic Management in Internet-of-Vehicle" International Journal of Advanced Computer Science and Applications (IJACSA), 13(4), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130473.

  • S. Reshma, C. Chetanaprakash, "Novel Hybrid Architecture of Infotainment for Streaming Signals in Vehicular Network," Research Square, 16 March 2021, DOI: 10.21203/rs.3.rs-273846/v1.


Abstract Views: 114

PDF Views: 0




  • Optimized Controller Scheme for Autonomous Navigation in Infotainment on Internet-of-Vehicles

Abstract Views: 114  |  PDF Views: 0

Authors

Reshma S.
Department of Artificial Intelligence and Machine Learning, Dayananda Sagar College of Engineering, Bengaluru, Karnataka., India
Chetanaprakash
Department of Computer Science and Engineering, Bapuji Institute of Engineering and Technology, Davangere, Karnataka., India

Abstract


The infotainment system curves an innovative mechanism of essential information dissemination for ensuring driving safety and improved driving experiences. However, there are significant challenges in developing an infotainment system to fit into the operational design of advanced technology, e.g., Internet-of-Vehicle (IoV). A review of existing studies has witnessed advantages and shortcomings, especially from the perspective of navigational services. Therefore, the proposed scheme introduces a novel autonomous signal control system that can realize the navigational demands of each vehicle meeting at the intersection to offer a faster clearance in the traffic management system. Analytically designed with a collaborative cloud environment, the proposed scheme implements a novel optimized controller scheme that can operate in a decentralized manner using a Fuzzy controller system for efficient traffic management in IoV applications..

Keywords


Infotainment, Internet of Vehicle, Navigation, Signal, Traffic Management, Clearance.

References





DOI: https://doi.org/10.22247/ijcna%2F2023%2F221882