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Development of Adaptive Cruise Control for Cut-In Scenario Using Crow Search Algorithm

Journal of Robotics and Control (JRC) · Vol. 7 No. 2 (2026) · hlm. 3587–3597

DOI
10.18196/jrc.v7i2.28813
ISSN
2715-5072, 2715-5056
Terbit
2026-03-01
Penerbit
Universitas Muhammadiyah Yogyakarta
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Cut-in maneuvers pose a major challenge for Adaptive Cruise Control (ACC) systems because they require rapid re-identification of the lead vehicle and immediate adjustment of longitudinal control to maintain safety. Conventional ACC controllers often struggle to respond quickly and smoothly under these abrupt disturbances. This study proposes the use of the Crow Search Algorithm (CSA) to optimize key ACC control parameters, enabling improved adaptability and stability during cut-in events. CSA is employed to tune the controller gains through an iterative search process that balances exploration and exploitation. Simulation experiments are conducted to evaluate the influence of iteration numbers and population sizes on optimization performance. The optimized ACC system is validated through a cut-in scenario, assessing relative distance error, velocity error, and recovery behavior after the disturbance. The results show that CSA significantly enhances the controller’s ability to reduce transient errors, stabilize inter-vehicle distance, and restore speed in a smooth and safe manner. These findings demonstrate that CSA is a promising metaheuristic for improving ACC robustness in highly dynamic traffic environments. Future extensions include testing in multi-scenario conditions, incorporating cooperative vehicle-to-vehicle communication, and integrating hybrid optimization methods to further enhance real-time performance.

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  • State University of Semarang
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Rekan penulisOrganisasiArtikel bersama
Alfa Faridh SuniState University of Semarang2
Anan NugrohoState University of Semarang2
Raihan Fa’iq MubarakState University of Semarang2
Muhammad GhulamzakiState University of Semarang2
Khoirudin FathoniState University of Semarang2
Mona SubagjaState University of Semarang2
Anggraini MulwindaState University of Semarang1
Agus SuryantoState University of Semarang1
Bambang SatrioState University of Semarang1
KriswantoAfiliasi tidak diketahui1
Atta Putra HarjantoState University of Semarang1
Khoirul HudaState University of Semarang1
AbdurrahmanState University of Semarang1
MUHAMMAD NUR FAIZINState University of Semarang1
R. Imanu Danar HerunandiState University of Semarang1
R. Ambar Kuntoro Mursit GendroyonoState University of Semarang1
Nugroho Fajar SusantoState University of Semarang1
Nur IksanBandung Institute of Technology1
Mohammad Sofyan AzizState University of Semarang1
Aryo Baskoro UtomoState University of Semarang1
Arimaz HanggaState University of Semarang1
Oky Putra PamungkasState University of Semarang1
ArlintoAfiliasi tidak diketahui1
Izzati Gemi SeinsianiState University of Semarang1
Yogi Agung PrasetyoState University of Semarang1
Muhammad Alvan FauziState University of Semarang1
Raditya Wisnu WardhanaState University of Semarang1
Muhammad Azil MaskurState University of Semarang1
Ali MasyharState University of Semarang1
Nadhira Madania DimartiState University of Semarang1
Sunusi DaudaAfiliasi tidak diketahui1
Widi AstutiState University of Semarang1
Triastuti SulistyaningsihState University of Semarang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.umy.ac.id/index.php/jrc/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Development of Adaptive Cruise Control for Cut-In Scenario Using Crow Search Algorithm</dc:title>
	<dc:creator>Prastiyanto, Dhidik</dc:creator>
	<dc:creator>Pribadi, Feddy Setio</dc:creator>
	<dc:creator>Fathoni, Khoirudin</dc:creator>
	<dc:creator>Prastyo, Ilham Ari</dc:creator>
	<dc:creator>Maulana, Ahnaf</dc:creator>
	<dc:subject xml:lang="en-US">Adaptive Cruise Control</dc:subject>
	<dc:subject xml:lang="en-US">Crow Search Algorithm</dc:subject>
	<dc:subject xml:lang="en-US">Traffic Scenarios</dc:subject>
	<dc:subject xml:lang="en-US">Cut-in</dc:subject>
	<dc:subject xml:lang="en-US">Autonomous Vehicles</dc:subject>
	<dc:description xml:lang="en-US">Cut-in maneuvers pose a major challenge for Adaptive Cruise Control (ACC) systems because they require rapid re-identification of the lead vehicle and immediate adjustment of longitudinal control to maintain safety. Conventional ACC controllers often struggle to respond quickly and smoothly under these abrupt disturbances. This study proposes the use of the Crow Search Algorithm (CSA) to optimize key ACC control parameters, enabling improved adaptability and stability during cut-in events. CSA is employed to tune the controller gains through an iterative search process that balances exploration and exploitation. Simulation experiments are conducted to evaluate the influence of iteration numbers and population sizes on optimization performance. The optimized ACC system is validated through a cut-in scenario, assessing relative distance error, velocity error, and recovery behavior after the disturbance. The results show that CSA significantly enhances the controller’s ability to reduce transient errors, stabilize inter-vehicle distance, and restore speed in a smooth and safe manner. These findings demonstrate that CSA is a promising metaheuristic for improving ACC robustness in highly dynamic traffic environments. Future extensions include testing in multi-scenario conditions, incorporating cooperative vehicle-to-vehicle communication, and integrating hybrid optimization methods to further enhance real-time performance.</dc:description>
	<dc:publisher xml:lang="en-US">Universitas Muhammadiyah Yogyakarta</dc:publisher>
	<dc:date>2026-03-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.umy.ac.id/index.php/jrc/article/view/28813</dc:identifier>
	<dc:identifier>10.18196/jrc.v7i2.28813</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Robotics and Control (JRC); Vol. 7 No. 2 (2026); 3587-3597</dc:source>
	<dc:source>2715-5072</dc:source>
	<dc:source>2715-5056</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.umy.ac.id/index.php/jrc/article/view/28813/12482</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Dhidik Prastiyanto, Feddy Setio Pribadi, Khoirudin Fathoni, Ilham Ari Prastyo, Ahnaf Maulana</dc:rights>
	<dc:rights xml:lang="en-US">https://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>