
(2) Tarik Ligabi

(3) * Yassine Zahraoui

*corresponding author
AbstractThis study introduces an architecture for an autonomous vehicle control system based on a collision detector and geometric modeling of trajectories. The goal is to develop a robust and reliable control model that can navigate metropolitan environments, often crowded with pedestrians and bicycles, as well as suburban areas, where traffic patterns can fluctuate. We have created a modular control unit that includes a collision predictor, which interacts closely with the decision module. The executed algorithm demonstrates the effectiveness of our system by ensuring the safety and comfort of the passengers. It can identify potential collisions from a distance and initiate braking preventively, following precise guidelines for deceleration and acceleration. To validate our methods, we are looking at simulations of realistic case studies. The research conducted underscores a crucial advancement in the development of safer and more flexible autonomous driving technologies.
KeywordsAutonomous Vehicle; Collision Prediction; Control Block; Adaptive Cruise Control; Urban Drive Modeling
|
DOIhttps://doi.org/10.31763/ijrcs.v5i1.1681 |
Article metrics10.31763/ijrcs.v5i1.1681 Abstract views : 87 | PDF views : 12 |
Cite |
Full Text![]() |
References
[1] A. Chand, S. Jayesh, and A. B. Bhasi, “Road traffic accidents: An overview of data sources, analysis techniques and contributing factors,†Materials Today: Proceedings, vol. 47, pp. 5135–5141, 2021, https://doi.org/10.1016/j.matpr.2021.05.415.
[2] H. Wang and B. Liu, “Path Planning and Path Tracking for Collision Avoidance of Autonomous Ground Vehicles,†in IEEE Systems Journal, vol. 16, no. 3, pp. 3658-3667, 2022, https://doi.org/10.1109/JSYST.2021.3085479.
[3] L. Zheng, P. Zeng, W. Yang, Y. Li, and Z. Zhan, “Bézier curve-based trajectory planning for autonomous vehicles with collision avoidance,†IET Intelligent Transport Systems, vol. 14, no. 13, pp. 1882–1891, 2020, https://doi.org/10.1049/iet-its.2020.0355.
[4] M. Ammour, R. Orjuela and M. Basset, “A MPC Combined Decision Making and Trajectory Planning for Autonomous Vehicle Collision Avoidance,†in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, pp. 24805-24817, 2022, https://doi.org/10.1109/TITS.2022.3210276.
[5] H. Alghodhaifi and S. Lakshmanan, “Autonomous Vehicle Evaluation: A Comprehensive Survey on Modeling and Simulation Approaches,†in IEEE Access, vol. 9, pp. 151531-151566, 2021, https://doi.org/10.1109/ACCESS.2021.3125620.
[6] P. S. Perumal et al., “An insight into crash avoidance and overtaking advice systems for Autonomous Vehicles: A review, challenges and solutions,†Engineering Applications of Artificial Intelligence, vol. 104, p. 104406, 2021, https://doi.org/10.1016/j.engappai.2021.104406.
[7] J.-B. Receveur, S. Victor, and P. Melchior, “Autonomous car decision making and trajectory tracking based on genetic algorithms and fractional potential fields,†Intelligent Service Robotics, vol. 13, no. 2, pp. 315–330, 2020, https://doi.org/10.1007/s11370-020-00314-x.
[8] T. Zhang, W. Song, M. Fu, Y. Yang, X. Tian and M. Wang, “A Unified Framework Integrating Decision
[9] Making and Trajectory Planning Based on Spatio-Temporal Voxels for Highway Autonomous Driving,†in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, pp. 10365-10379, 2022, https://doi.org/10.1109/TITS.2021.3093548.
[10] N. Klinjun, M. Kelly, C. Praditsathaporn, and R. Petsirasan, “Identification of Factors Affecting Road
[11] Traffic Injuries Incidence and Severity in Southern Thailand Based on Accident Investigation Reports,†Sustainability, vol. 13, no. 22, p. 12467, 2021, https://doi.org/10.3390/su132212467.
[12] F. Leon and M. Gavrilescu, “A Review of Tracking and Trajectory Prediction Methods for Autonomous Driving,†Mathematics, vol. 9, no. 6, p. 660, 2021, https://doi.org/10.3390/math9060660.
[13] P. Kothari, S. Kreiss and A. Alahi, “Human Trajectory Forecasting in Crowds: A Deep Learning Perspective,†in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 7, pp. 7386-7400, 2022, https://doi.org/10.1109/TITS.2021.3069362.
[14] S. Wang, Z. Bao, J. S. Culpepper, and G. Cong, “A Survey on Trajectory Data Management, Analytics, and Learning,†ACM Computing Survey, vol. 54, no. 2, pp. 1–36, 2021, https://doi.org/10.1145/3440207.
[15] S. Capobianco, L. M. Millefiori, N. Forti, P. Braca and P. Willett, “Deep Learning Methods for Vessel Trajectory Prediction Based on Recurrent Neural Networks,†in IEEE Transactions on Aerospace and Electronic Systems, vol. 57, no. 6, pp. 4329-4346, 2021, https://doi.org/10.1109/TAES.2021.3096873.
[16] L. Lin, W. Li, H. Bi and L. Qin, “Vehicle Trajectory Prediction Using LSTMs With Spatial–Temporal Attention Mechanisms,†in IEEE Intelligent Transportation Systems Magazine, vol. 14, no. 2, pp. 197-208, 2022, https://doi.org/10.1109/MITS.2021.3049404.
[17] X. Song et al., “Pedestrian Trajectory Prediction Based on Deep Convolutional LSTM Network,†in IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 6, pp. 3285-3302, 2021, https://doi.org/10.1109/TITS.2020.2981118.
[18] R. Quan, L. Zhu, Y. Wu and Y. Yang, “Holistic LSTM for Pedestrian Trajectory Prediction,†in IEEE Transactions on Image Processing, vol. 30, pp. 3229-3239, 2021, https://doi.org/10.1109/TIP.2021.3058599.
[19] C. Vishnu, V. Abhinav, D. Roy, C. K. Mohan and C. S. Babu, “Improving Multi-Agent Trajectory Prediction Using Traffic States on Interactive Driving Scenarios,†in IEEE Robotics and Automation Letters, vol. 8, no. 5, pp. 2708-2715, 2023, https://doi.org/10.1109/LRA.2023.3258685.
[20] S. Mozaffari, O. Y. Al-Jarrah, M. Dianati, P. Jennings and A. Mouzakitis, “Deep Learning Based Vehicle Behavior Prediction for Autonomous Driving Applications: A Review,†in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 1, pp. 33-47, 2022, https://doi.org/10.1109/TITS.2020.3012034.
[21] R. Hajiloo, M. Abroshan, A. Khajepour, A. Kasaiezadeh and S. -K. Chen, “Integrated Steering and Differential Braking for Emergency Collision Avoidance in Autonomous Vehicles,†in IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 5, pp. 3167-3178, 2021, https://doi.org/10.1109/TITS.2020.2984210.
[22] A. P. Carrone, J. Rich, C. A. Vandet, and K. An, “Autonomous vehicles in mixed motorway traffic: capacity utilisation, impact and policy implications,†Transportation, vol. 48, no. 6, pp. 2907–2938, 2021, https://doi.org/10.1007/s11116-020-10154-4.
[23] C. Wang, X. Zhao, R. Fu, and Z. Li, “Research on the Comfort of Vehicle Passengers Considering the Vehicle Motion State and Passenger Physiological Characteristics: Improving the Passenger Comfort of Autonomous Vehicles,†International Journal of Environmental Research and Public Health, vol. 17, no. 18, p. 6821, 2020, https://doi.org/10.3390/ijerph17186821.
[24] D. Parekh, N. Poddar, A. Rajpurkar, M. Chahal, N. Kumar, G. P. Joshi, and W. Cho, “A Review on Autonomous Vehicles: Progress, Methods and Challenges,†Electronics, vol. 11, no. 14, p. 2162, 2022, https://doi.org/10.3390/electronics11142162.
[25] Y. Li, Y. Cai, X. Sun, H. Wang, Y. Jia, Y. He, L. Chen, and Y. Chao, “Trajectory tracking of four-wheel driving and steering autonomous vehicle under extreme obstacle avoidance condition,†Vehicle System Dynamics, vol. 62, no. 3, pp. 601–622, 2024, https://doi.org/10.1080/00423114.2023.2186249.
[26] A. Boubakri and S. M. Gamar, “A New Architecture of Autonomous Vehicles: Redundant Architecture to Improve Operational Safety,†International Journal of Robotics and Control Systems, vol. 1, no. 3, pp. 355–368, 2021, https://doi.org/10.31763/ijrcs.v1i3.437.
[27] W. Farag, M. Abouelela, and M. Helal, “Finding and Tracking Automobiles on Roads for Self-Driving Car Systems,†International Journal of Robotics and Control Systems, vol. 3, no. 4, pp. 704–727, 2023, https://doi.org/10.31763/ijrcs.v3i4.1022.
[28] M. H. Harun, S. S. Abdullah, M. S. M. Aras, M. B. Bahar, and F. Ali Ibrahim, “Recent Developments and Future Prospects in Collision Avoidance Control for Unmanned Aerial Vehicles (UAVS): A Review,†International Journal of Robotics and Control Systems, vol. 4, no. 3, pp. 1207–1242, Jul. 2024, https://doi.org/10.31763/ijrcs.v4i3.1482.
[29] T. Feng, K. Liu, and C. Liang, “An Improved Cellular Automata Traffic Flow Model Considering Driving Styles,†Sustainability, vol. 15, no. 2, p. 952, 2023, https://doi.org/10.3390/su15020952.
[30] Y. E. Hafid, A. E. Rharras, M. Wahbi, and R. Saadane, “GPU optimized parallel implementation of NaSch traffic model,†Proceedings of the Third International Conference on Computing and Wireless Communication Systems, 2019, http://dx.doi.org/10.4108/eai.24-4-2019.2284233.
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Yassine El Hafid, Tarik Ligabi, Yassine Zahraoui

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
About the Journal | Journal Policies | Author | Information |
International Journal of Robotics and Control Systems
e-ISSN: 2775-2658
Website: https://pubs2.ascee.org/index.php/IJRCS
Email: ijrcs@ascee.org
Organized by: Association for Scientific Computing Electronics and Engineering (ASCEE), Peneliti Teknologi Teknik Indonesia, Department of Electrical Engineering, Universitas Ahmad Dahlan and Kuliah Teknik Elektro
Published by: Association for Scientific Computing Electronics and Engineering (ASCEE)
Office: Jalan Janti, Karangjambe 130B, Banguntapan, Bantul, Daerah Istimewa Yogyakarta, Indonesia