Modelling Road Congestion Using a Fuzzy System and Real-World Data for Connected and Autonomous Vehicles

Abstract

Road congestion is estimated to cost the United Kingdom £307 billion by 2030. Furthermore, congestion contributes enormously to damaging the environment and people's health. In an attempt to combat the damage congestion is causing, new technologies are being developed, such as intelligent infrastructures and smart vehicles. The aim of this study is to develop a fuzzy system that can classify congestion using a real-world dataset referred to as Manchester Urban Congestion Dataset, which contains data similar to that collected by connected and autonomous vehicles. A set of fuzzy membership functions and rules were developed using a road congestion ontology and in conjunction with domain experts. Experiments are conducted to evaluate the fuzzy system in terms of its precision and recall in classifying congestion. Comparisons are made in terms of performance with traditional classification algorithms decision trees and Naïve Bayes using the Red, Amber, and Green classification methods currently implemented by Transport for Greater Manchester to label the dataset. The results have shown the fuzzy system has the ability to predict road congestion using volume and journey time, outperforming both decision trees and Naïve Bayes.

Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncertainty

“…As a result, in this study, road travel time and loading/unloading time are considered as the sources of time uncertainty. Road travel time uncertainty emerges due to traffic congestion, bad weather and accidents [1,27,28], while loading/unloading time uncertainty results from the unstable proficiency and state of staff that conduct loading/unloading operations, technical issues of the loading/unloading equipment and unpredictable tasks that occupy staff and equipment. These two sources of time uncertainty will not only influence the goods delivery but also disrupt the transshipment between road and rail.…”

Conceptual Model for Connected Vehicles Safety and Security using Big Data Analytics

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