Rakesh Poorella
Sai Kumar Reddy
Charanjeet Singh
- Student, Department of Electronics and Electrical Engineering, Lovely Professional University Phagwara, Punjab, India
- Student, Department of Electronics and Electrical Engineering, Lovely Professional University Phagwara, Punjab, India
- Assistant Professor, Department of Electronics and Electrical Engineering, Lovely Professional University Phagwara, Punjab, India
Abstract
New technologies are constantly being created in the modern era of the automotive industry to increase driver comfort and safety. The vehicle industry is focused on creating new designs that prioritize comfort and safety to overcome this problem. The technology which helps the automotive industry is the Adaptive Cruise Control system (ACC). The ACC system is an electronic device that assists drivers to keep a guarded distance from the upcoming vehicle by automatically adjusting the vehicle’s speed. It works on sensors and radars which are the heart of the system. The implementation of this system can significantly reduce the risk of accidents caused by the driver’s inability to keep a safe space from the moving car ahead. The use of this technology provides a basis for additional studies concerning automotive safety and automation. In this review paper, we have explored the different technologies and mechanisms associated with ACC and their performance metrics have also been put there of.
Keywords: Adaptive cruise control (ACC), sensors, radars, metrics, FLCs
[This article belongs to International Journal of Advanced Control and System Engineering(ijacse)]
Browse Figures
References
S. Dawood, A. K. Mahmood, & M. A. Ibrahim (2018). Comparison of PID, GA and fuzzy logic controllers for cruise control systems. International Journal of Computing and Digital Systems, 7(05), 311–319, Volume-7, Issue-5, University of Behrain.
Huang, Y., Ding, H., Zhang, Y., Wang, H., Cao, D., Xu, N., & Hu, C. (2019). A motion planning and tracking framework for autonomous vehicles based on artificial potential field elaborated resistance network approach. IEEE Transactions on Industrial Electronics, Volume-67, Issue-2, February-2020 1376–1386, IEEE Xplore, https://ieeexplore.ieee.org/document/8643096.
Van Keulen, T., Naus, G., De Jager, B., Van De Molengraft, R., Steinbuch, M., & Aneke, E. (2009). Predictive cruise control in hybrid electric vehicles. World Electric Vehicle Journal, Volume-3, ISSN: 2032–6653, 494–504,
Vahidi, A., & Eskandarian, A. (2003). Research advances in intelligent collision avoidance and adaptive cruise control. IEEE transactions on intelligent transportation systems, Volume-4, Issue-3, September-2003, 143–153, IEEE Xplore, https://ieeexplore.ieee.org/document/1255576.
Milanes, V., Shladover, S. E., Spring, J., Nowakowski, C., Kawazoe, H., & Nakamura, M. (2013). Cooperative adaptive cruise control in real traffic situations. IEEE Transactions on intelligent transportation systems, Volume-15, Issue-1, February-2014, 296–305, IEEE Xplore, https://ieeexplore.ieee.org/document/6588305
Hwisoo Eom and Sang Hun Lee. Human-Automation Interaction Design for Adaptive Cruise Control Systems of Ground Vehicles. Sensors 2015, 15(6), 13916–13944; https://doi.org/10.3390/s150613916
Dey, C., Yan, L., Wang, X., Wang, Y., Shen, H., Chowdhury, M., … & Soundararaj, V. (2015). A review of communication, driver characteristics, and controls aspects of cooperative adaptive cruise control (CACC). IEEE Transactions on Intelligent Transportation Systems, Volume-17, Issue-2, February-2016, 491–509, IEEE Xplore, https://ieeexplore.ieee.org/document/7314936.
Okuda, R., Kajiwara, Y., & Terashima, K. (2014, April). A survey of technical trend of ADAS and autonomous driving. In Technical Papers of 2014 International Symposium on VLSI Design, Automation and Test (pp. 1–4). IEEE, printed ISSN:1524–766X, IEEE Xplore, https://ieeexplore.ieee.org/document/6839646.
| Volume | 01 |
| Issue | 01 |
| Received | July 27, 2023 |
| Accepted | August 29, 2023 |
| Published | January 9, 2024 |