Analysis of an adaptive cruise control under low visibility conditions

This work presents the analysis of an adaptive cruise control system for robotic vehicles. The proposed adaptive cruise control system assists in preventing rear-end collisions in low-visibility scenarios. Collision avoidance is achieved through speed adjustment, which is dependent on the distance f...

Descripción completa

Detalles Bibliográficos
Autores: Bañuelos-Peña, Gabriel Alejandro, Coronado-Andrade, Allan Christopher, Velázquez-Velázquez , Juan Eduardo, Rivera-Fernández, Josué Daniel, Fabila-Bustos, Diego Adrián
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:México
Institución:UNIVERSIDAD AUTÓNOMA DEL ESTADO DE HIDALGO
Repositorio:PÄDI Boletín Científico de Ciencias Básicas e Ingeniería del ICBI
Idioma:español
OAI Identifier:oai:repository.uaeh.edu.mx:article/11428
Acceso en línea:https://repository.uaeh.edu.mx/revistas/index.php/icbi/article/view/11428
Access Level:acceso abierto
Palabra clave:Reference model
Adaptive cruise control
computer vision
robotic vehicle
Modelo de referencia
Control crucero adaptable
visión artificial
vehículo robot
Descripción
Sumario:This work presents the analysis of an adaptive cruise control system for robotic vehicles. The proposed adaptive cruise control system assists in preventing rear-end collisions in low-visibility scenarios. Collision avoidance is achieved through speed adjustment, which is dependent on the distance from the vehicle in front of the robotic vehicle. It is implemented using computer vision, adaptive control, embedded systems, and computer-aided design. The functionality of the proposed system is analyzed through tests on terrains with varying inclinations, as well as in controlled scenarios with good visibility and poor visibility. Lack of visibility is a critical scenario in this work because, in case of limited visibility in the environment, the computer vision system will stop detecting vehicles. Then, LiDAR and radar sensors will measure the distance and speed of the vehicle ahead, and based on this data, reduce or maintain the vehicle's speed.