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Jan 12, 2024
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Feb 23, 2024
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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.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Maharajpet, S. S., & S, C. (2024). Exploring the Confluence of Technology and Driving: An Examination of Advanced Driver Assistance Systems. Indonesian Journal of Engineering Research, 4(2). https://doi.org/10.11594/ijer.v4i2.52
References
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[9] 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
[10] 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
[11] 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
[12] 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
[13] 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
[14] 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
[15] 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
[16] 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
[17] 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
[18] 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
[19] 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
[20] 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
[2] 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
[3] 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
[4] 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
[5] 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
[6] 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
[7] 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
[8] 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
[9] 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
[10] 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
[11] 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
[12] 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
[13] 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
[14] 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
[15] 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
[16] 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
[17] 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
[18] 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
[19] 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
[20] 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