A novel adaptive vehicle speed recommender fuzzy system for autonomous vehicles on conventional two‐lane roads

Abstract

This paper presents an intelligent speed adaption system for vehicles on conventional roads. The fuzzy logic based expert system outputs a recommended speed to ensure both safety and passenger comfort. This intelligent system includes geometrical features of the road, as well as subjective perceptions of the drivers. It has been developed and checked with real data that were measured with an instrumental system incorporated in a vehicle, on several two-lane roads located in the Madrid Region, Spain. Along with the road geometrical characteristics, other input variables to the system are external factors, such as weather conditions, distance to the preceding vehicle, tire pressure, and other subjective criteria, such as the desired comfort level, selected by the driver. The expert system output is the most suitable speed for the specific road type, considering real factors that may modify the category of the road and thus, the appropriate speed. This information could be added to the adaptive cruise control of the vehicle. The recommended speed can be a very useful input for both, drivers and the autonomous vehicles, to improve safety on the road system.

Recent trends and advances in machine learning challenges and applications for industry 4.0

“…The protocol tackles data loss, reliability and big data in vital healthcare systems. Barreno et al (2022) unveil an adaptive speed recommender system for autonomous vehicles on two-lane roads, harnessing fuzzy logic.…”

“…Barreno et al (2022) unveil an adaptive speed recommender system for autonomous vehicles on two‐lane roads, harnessing fuzzy logic. Madrid Region data shapes its design, reflecting road geometry, weather, and driver insights.…”

Research on the optimal speed of vehicles passing speed bumps on the highway based on an immune algorithm

“…There are few studies on the comfort and safety of vehicles when passing over uneven surfaces, especially when it comes to passing speed bumps. When drivers encounter speed bumps while driving, they rapidly identify the type of speed bump and adjust their vehicle's speed based on their subjective experience to minimise discomfort during passage (Barreno et al, 2022). In the case of semi-automated driving, forward-facing cameras are used to detect speed bumps on the road ahead, and the driving assistance system assists the driver in adjusting the vehicle's speed to reduce vehicle vibrations (Zein and Darwiche, 2020).…”

Control longitudinal de un vehículo mediante aprendizaje por refuerzo profundo

“…El sistema de control se ha diseñado con aprendizaje profundo por refuerzo. El sistema inteligente aquí propuesto para la asistencia a la conducción se centra en caracterizar la conducción del vehículo en función del efecto de la curvatura de la carretera, de forma que incorpora la geometría de la misma a través de ciertas características relacionadas con ella, la aceleración longitudinal y lateral del vehículo, percibidas por el conductor al tomar las curvas (Barreno et al, 2022b). Esto contribuye a una conducción más segura, ya que una velocidad inadecuada en una curva podría ser insegura para un determinado tramo de carretera.…”