A LiDAR-Driven Fallback Longitudinal Controller for Safer Following in Sudden Braking Scenarios

Mohamed Sabry; Enrico Del Re; Walter Morales-Alvarez; Cristina Olaverri-Monreal

doi:10.48550/arXiv.2509.16642

A LiDAR-Driven Fallback Longitudinal Controller for Safer Following in Sudden Braking Scenarios

Mohamed Sabry^*
, Enrico Del Re^*
, Walter Morales-Alvarez^*
, Cristina Olaverri-Monreal^*

^*Corresponding author for this work

Department Intelligent Transport Systems

Research output: Working paper and reports › Preprint

Abstract

Adaptive Cruise Control has seen significant advancements, with Collaborative Adaptive Cruise Control leveraging Vehicle-to-Vehicle communication to enhance coordination and stability. However, the reliance on stable communication channels limits its reliability. Research on reducing information dependencies in Adaptive Cruise Control systems has remained limited, despite its critical role in mitigating collision risks during sudden braking scenarios. This study proposes a novel fallback longitudinal controller that relies solely on LiDAR-based distance measurements and the velocity of a follower vehicle. The controller is designed to be time-independent, ensuring operation in the presence of sensor delays or synchronization issues. Simulation results demonstrate that the proposed controller enables vehicle-following from standstill and prevents collisions during emergency braking, even under minimal onboard information.

Original language	English
Number of pages	7
DOIs	https://doi.org/10.48550/arXiv.2509.16642
Publication status	Published - 20 Sept 2025

Publication series

Name	arXiv.org

Fields of science

102003 Image processing
102002 Augmented reality
102001 Artificial intelligence
102029 Practical computer science
211911 Sustainable technologies
102021 Pervasive computing
303 Health Sciences
303008 Ergonomics
211917 Technology assessment
102026 Virtual reality
501026 Psychology of perception
501025 Traffic psychology
102024 Usability research
102013 Human-computer interaction
202034 Control engineering
202003 Automation
211902 Assistive technologies
201306 Traffic telematics
201305 Traffic engineering
202031 Network engineering
202030 Communication engineering
102 Computer Sciences
102034 Cyber-physical systems
203 Mechanical Engineering
202040 Transmission technology
102019 Machine learning
211909 Energy technology
202 Electrical Engineering, Electronics, Information Engineering
202038 Telecommunications
211908 Energy research
202041 Computer engineering
501 Psychology
202037 Signal processing
102015 Information systems
202036 Sensor systems
501030 Cognitive science
202035 Robotics
203004 Automotive technology

JKU Focus areas

Sustainable Development: Responsible Technologies and Management
Digital Transformation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.48550/arXiv.2509.16642

1 Conference proceedings

A LiDAR-Driven Fallback Longitudinal Controller for Safer Following in Sudden Braking Scenarios
Sabry, M., Del Re, E., Morales Alvarez, W. & Olaverri-Monreal, C., 2025, (Accepted/In press) IEEE International Conference on Vehicular Electronics and Safety (ICVES) 2025.
Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Cite this

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abstract = " Adaptive Cruise Control has seen significant advancements, with Collaborative Adaptive Cruise Control leveraging Vehicle-to-Vehicle communication to enhance coordination and stability. However, the reliance on stable communication channels limits its reliability. Research on reducing information dependencies in Adaptive Cruise Control systems has remained limited, despite its critical role in mitigating collision risks during sudden braking scenarios. This study proposes a novel fallback longitudinal controller that relies solely on LiDAR-based distance measurements and the velocity of a follower vehicle. The controller is designed to be time-independent, ensuring operation in the presence of sensor delays or synchronization issues. Simulation results demonstrate that the proposed controller enables vehicle-following from standstill and prevents collisions during emergency braking, even under minimal onboard information. ",

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AB - Adaptive Cruise Control has seen significant advancements, with Collaborative Adaptive Cruise Control leveraging Vehicle-to-Vehicle communication to enhance coordination and stability. However, the reliance on stable communication channels limits its reliability. Research on reducing information dependencies in Adaptive Cruise Control systems has remained limited, despite its critical role in mitigating collision risks during sudden braking scenarios. This study proposes a novel fallback longitudinal controller that relies solely on LiDAR-based distance measurements and the velocity of a follower vehicle. The controller is designed to be time-independent, ensuring operation in the presence of sensor delays or synchronization issues. Simulation results demonstrate that the proposed controller enables vehicle-following from standstill and prevents collisions during emergency braking, even under minimal onboard information.

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