Abstract Traditional Adaptive Cruise Control (ACC) systems often struggle to dynamically
adapt to rapidly changing traffic conditions, resulting in suboptimal performance …

Existing transportation infrastructure and traffic control systems face increasing strain as a
result of rising demand, resulting in frequent congestion. Expanding infrastructure is not a …

Smart traffic congestion reduction is actually a real challenge for big cities. Machine learning
algorithms can play a significant role in traffic analysis, congestion prediction, and rerouting …

Freeway networks, despite being built to handle the transportation needs of large traffic
volumes, have suffered in recent years from an increase in demand that is rarely resolvable …

Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and
decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow …

Traffic congestion remains a pressing challenge in urban areas, causing significant
economic and environmental repercussions. To address this issue, accurate detection and …

Several factors over the years have contributed to stigma in public transport. Many studies
have highlighted the need to make the transport system more equitable both from economic …

Data dissemination is one of the applications used to provide infotainment to the end-users
in vehicular ad hoc networks (VANET). During this process, the vehicles receive the data …

This paper presents a two-stage fuzzy-logic application based on the Mamdani inference
method to classify the observed road traffic conditions. It was tested using real data extracted …

The process of traffic control systems significantly relies on the immediate detection of
breakdown states. As a result of their crisp (non-fuzzy) based calculation procedures …