Enhancing Vehicle Navigation and Safety through Integration of Pre-Recorded Maps with Vehicle Control Unit
Keywords:
Offline Mapping, Local Sensor-Based Positioning, Autonomous Vehicles, ADAS, Navigation Systems, Edge Detection, Computer Vision, GPS, Vehicle Safety, Real-Time Navigation, Autonomous Driving, Sensor Fusion, Vehicle LocalizationAbstract
Powerful navigation and safety systems are vital to ensuring autonomous (DV) or semi-autonomous vehicles continue well in varied environmental conditions. However, in such a world those who depend on that internet connectivity to navigate their car would have problems in areas where network reliability is less than perfect. The purpose of this work is to investigate the feasibility and advantages of combining offline mapping with locally sensed positioning systems for better vehicle navigation and safety. While connected to the internet, vehicles cache offline maps and use local sensor information (such as GPS) from their inertial navigation system or computer vision without needing continuous access. The research outlines a hardware-software architecture with embedded offline map data storage, edge-based road following algorithms and an integration mechanism to advanced driving assistance systems (ADAS). In the evaluation of performance, accuracy assessments with online mapping systems are considered for offline maps and how these can have implications on end driver usability as well impacts on real-world autonomous driving technologies. The results suggest that offline mapping and on-board sensor-based localization would be able to improve vehicle contextual navigation performance in diverse driving scenarios.
References
Ministry of Road Transport and Highways, "Road Accident in India," Ministry of Road Transport and Highways, Government of India. Available from: https://morth.nic.in/road-accident-in-india.
J. Nidamanuri, C. Nibhanupudi, R. Assfalg, and H. Venkataraman, "A Progressive Review: Emerging Technologies for ADAS Driven Solutions," IEEE Trans. Intell. Vehicles, vol. 7, no. 2, pp. 123-134, Jun. 2022. Available from https://doi.org/10.1109/TIV.2021.3122898
Y. Maalej, S. Sorour, A. Abdel-Rahim, and M. Guizani, "VANETs Meet Autonomous Vehicles: Multimodal Surrounding Recognition Using Manifold Alignment," IEEE Access, vol. 6, pp. 29026–29040, 2018. Available from https://doi.org/10.1109/ACCESS.2018.2839561
K. Lim and K. M. Tuladhar, "LIDAR: Lidar Information Based Dynamic V2V Authentication for Roadside Infrastructure-Less Vehicular Networks," in Proc. 16th IEEE Annu. Consum. Commun. Netw. Conf. (CCNC), 2019, pp. 1–6. Available from https://doi.org/10.1109/CCNC.2019.8651684
P. Marzec and A. Kos, "Road Line Detection by Reflected Heat Assistant System for Car Navigation," in Proc. Mixed Design of Integrated Circuits and Systems (MIXDES), 2022, pp. [page numbers]. AGH University of Science and Technology, Institute of Electronics, Cracow, Poland. Available from https://doi.org/10.23919/MIXDES55591.2022.9838012
R. Hayashi and M. Yagi, "An Observation Method of Vehicle Lateral Position Based on Map Matching in Winter Road Condition," in 2023 IEEE 12th Global Conference on Consumer Electronics (GCCE), Sapporo, Japan, 2023, pp. 979-8-3503-4018-1/23/$31.00, Available from https://doi.org/10.1109/GCCE59613.2023.10315649
R. Saranya, V. Adarsh, S. Akash, P. Amirthap, S. Dinesh Ram, and N. Ajay Kumar, "Advanced Driver Assistance System for Enhanced Road Safety Analysis," in Proc. 2023 International Conference on System, Computation, Automation and Networking (ICSCAN), Chennai, India, 2023, pp. 1-7, Available from https://doi.org/10.1109/ICSCAN58655.2023.10395036.
B. Ganguly, D. Dey, and S. Munshi, "An Unsupervised Learning Approach for Road Anomaly Segmentation Using RGB-D Sensor for Advanced Driver Assistance System," IEEE Trans. Intelligent Transportation Systems, vol. 23, no. 10, pp. 1234-1245, Oct. 2022. Available from https://doi.org/10.1109/TITS.2022.3164847
World Health Organization, Global Status Report on Road Safety 2018, WHO, Geneva, Switzerland, 2018. Available from https://www.who.int/publications/i/item/9789241565684.
