A safe speed guidance model for highways

Abstract

This paper presents a fuzzy logic model to support decisions for the suggested speed limit for sections of highways as they become affected by adverse road conditions, environmental factors and differing traffic levels. The definition of the main factors, and their weight, that reduce safety on highways was conducted by the Delphi method, consulting traffic engineering experts. The survey served as a basis for structuring indicators and indexes in a soft decision tree, structured by a fuzzy logic system. The system can be used to support the decisions of those that manage the roads, indicating to drivers' speeds, by visual, audible or combined systems.

A systematic literature review of vehicle speed assistance in intelligent transportation system

“…Due to the importance of safety and effects of environmental factors for selecting appropriate speed by drivers, De Mello et al. have presented a fuzzy logic model to speed limit suggestions in highways [52]. In this study, investigating main safety factors was conducted by the Delphi method and further classified by a soft decision tree, and the proposed model was simulated in a single lane highway traffic scenario.…”

Multilane Spatiotemporal Trajectory Optimization Method (MSTTOM) for Connected Vehicles

“…Wei et al [10] proposed a cooperative optimization method for multivehicle spatiotemporal trajectories, which is established based on the simplified Newell linear carfollowing model. Considering different road environments and weather conditions, De Mello and Chiodi [11] proposed a fuzzy logic control model of spatiotemporal trajectory, which increases the effectiveness of decision-making process by 13%. Liang et al [12] presented a method to optimize the common spatiotemporal trajectories for both autonomous vehicles and manual driving vehicles.…”