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.

This paper first presents a fuzzy expert system to identify and classify conventional two‐lane roads based on geometric characteristics. Both fuzzy and neuro‐fuzzy techniques have been used. Fuzzy logic has proved suitable to address this problem, since in this case, there is a variability of input information, and classical rules are not suitable to be used due to the uncertainty introduced by some combinations of the variables. Each road's geometric features were measured by sensors in an equipped vehicle, and are subsequently used to classify the roads according to their real condition. The conventional two‐lane roads used for this research are located in the Madrid Region, in Spain. This intelligent system may be used to update the road database regarding the assigned type to each conventional road, according to their present features and state. Also, a risk identification system has been developed to assess whether a vehicle is driving on a two‐lane road with an inappropriate speed, combining variables such as the former identification model, vehicle type, road longitudinal gradient, the angle covered by each horizontal curve, and the existence or not of an additional traffic lane. A fuzzy risk index is proposed for this approach. This fuzzy model may be useful to detect road sections where safety must be enhanced by revising the speed limit, since less safe situations may arise from travelling at unappropriated speeds.

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