Exploring the Confluence of Technology and Driving: An Examination of Advanced Driver Assistance Systems
DOI:
https://doi.org/10.11594/ijer.v4i2.52Keywords:
Intelligent Transportation Systems (ITS), Vehicle Safety, Cooperative Intelligent Transportation Systems (C-ITS), Driver Assistance Systems, Advanced Driver Assistance Systems (ADAS)Abstract
This paper architecture analysis highlights the key components of the ADAS design, including the sensors, perception layer, decision-making layer, and action layer. It explains the flow of data through the system and how sensor fusion contributes to the creation of a comprehensive image of the car's surroundings. It goes on to cover further ADAS features and their advantages, such as automated braking, adaptive cruise control, traffic sign recognition, and blind-spot detection. The hopeful future of ADAS technology is highlighted in the article's conclusion, along with how it might change driving habits, boost traffic safety, and enhance driving in general. It draws attention to the critical issues that require more study and development in order to solve them and open the door for ADAS to be widely used in a variety of traffic situations, particularly in India.
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Alzu’bi, H., Dwyer, B., Nagaraj, S., Pischinger, M., & Quail, A. (2018). Cost-effective automotive platform for ADAS and autonomous development. SAE Technical Paper Series. https://doi.org/10.4271/2018-01-0588
Avetisyan, L., Zhang, C., Bai, S., Pari, E. M., Feng, F., Bao, S., & Zhou, F. (2022). Design a sustainable micro-mobility future: trends and challenges in the US and EU. Journal of Engineering Design, 33(8–9), 587–606. https://doi.org/10.1080/09544828.2022.214290
Bougna, T., Hundal, G., & Taniform, P. N. (2022). Quantitative Analysis of the Social Costs of Road Traffic Crashes Literature. Accident Analysis & Prevention, 165, 106282. https://doi.org/10.1016/j.aap.2021.106282
Colagrande, S. (2022). A methodology for the characterization of urban road safety through accident data analysis. Transportation Research Procedia, 60, 504–511. https://doi.org/10.1016/j.trpro.2021.12.065
Eboli, L., Forciniti, C., & Mazzulla, G. (2020). Factors influencing accident severity: an analysis by road accident type. Transportation Research Procedia, 47, 449–456. https://doi.org/10.1016/j.trpro.2020.03.120
Goddard, T., McDonald, A. D., Wei, R., & Batra, D. (2022). Advanced Driver Assistance Systems in Top-Selling Vehicles in the United States: Cost, vehicle type, and trim level disparities. Findings. https://doi.org/10.32866/001c.38291
González-Saavedra, J. F., Figueroa, M., Céspedes, S., & Montejo‐Sánchez, S. (2022). Survey of Cooperative Advanced Driver Assistance Systems: From a Holistic and Systemic Vision. Sensors, 22(8), 3040. https://doi.org/10.3390/s22083040
Gutierrez-Osorio, C., & Pedraza, C. (2020). Modern data sources and techniques for analysis and forecast of road accidents: A review. Journal of Traffic and Transportation Engineering (English Edition), 7(4), 432–446. https://doi.org/10.1016/j.jtte.2020.05.002
Li, X., Lin, K., Meng, M., Li, X., Li, L., Ye, H., & Chen, J. (2022). A survey of ADAS perceptions with development in China. IEEE Transactions on Intelligent Transportation Systems, 23(9), 14188–14203. https://doi.org/10.1109/tits.2022.3149763
Marques, I., Sousa, J. D., Sá, B., Costa, D., Sousa, P., Di Salvatore Pereira, S., Santos, A., Lima, C. S., Hammerschmidt, N., Pinto, S., & Gomes, T. (2022). Microphone Array for Speaker Localization and Identification in Shared Autonomous Vehicles. Electronics, 11(5), 766. https://doi.org/10.3390/electronics11050766
Nidamanuri, J., Nibhanupudi, C., Aßfalg, R., & Venkataraman, H. (2022). A Progressive Review: Emerging Technologies for ADAS Driven solutions. IEEE Transactions on Intelligent Vehicles, 7(2), 326–341. https://doi.org/10.1109/tiv.2021.3122898
Nieto, M., Otaegui, O., Vélez, G., Ortega, J. D., & Cortés, A. (2015). On creating vision‐based advanced driver assistance systems. Iet Intelligent Transport Systems, 9(1), 59–66. https://doi.org/10.1049/iet-its.2013.0167
Orlovska, J., Novakazi, F., Bligård, L., Karlsson, M., Wickman, C., & Söderberg, R. (2020). Effects of the driving context on the usage of Automated Driver Assistance Systems (ADAS) -Naturalistic Driving Study for ADAS evaluation. Transportation Research Interdisciplinary Perspectives, 4, 100093. https://doi.org/10.1016/j.trip.2020.100093
Rana, M., & Hossain, K. (2021). Connected and Autonomous Vehicles and Infrastructures: A literature review. International Journal of Pavement Research and Technology, 16(2), 264–284. https://doi.org/10.1007/s42947-021-00130-1
Sakhare, K. V., Tewari, T., & Vyas, V. (2019). Review of vehicle detection systems in advanced Driver Assistant systems. Archives of Computational Methods in Engineering, 27(2), 591–610. https://doi.org/10.1007/s11831-019-09321-3
Sharma, N., & Garg, R. (2021). Cost reduction for advanced driver assistance systems through hardware downscaling and deep learning. Systems Engineering, 25(2), 133–143. https://doi.org/10.1002/sys.21606
Srinivasan, C., Sridhar, P., Raj, M. P., & Raj, S. (2023). Advanced Driver Assistance System (ADAS) in Autonomous Vehicles: A Complete Analysis. 2023 8th International Conference on Communication and Electronics Systems (ICCES). https://doi.org/10.1109/icces57224.2023.10192617
Wang, L., Sun, P., Xie, M., Ma, S., Li, B., Shi, Y., & Su, Q. (2020). Advanced Driver-Assistance System (ADAS) for intelligent transportation based on the recognition of traffic cones. Advances in Civil Engineering, 2020, 1–8. https://doi.org/10.1155/2020/8883639
Weber, M., Weiß, T., Gechter, F., & Kriesten, R. (2023). Approach for improved development of advanced driver assistance systems for future smart mobility concepts. Autonomous Intelligent Systems, 3(1). https://doi.org/10.1007/s43684-023-00047-5
Winter, M. G., & Wong, J. C. F. (2020). The assessment of quantitative risk to road users from debris flow. Geoenvironmental Disasters, 7(1). https://doi.org/10.1186/s40677-019-0140-x
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