The exponential increase in vehicles, quick urbanization, and rising demand for
transportation are straining the world's road infrastructure today. To have a sustainable …

Recent advancements in Large Language Models (LLMs) have ushered in opportunities to
craft agents that exhibit human-like cognitive abilities, notably reasoning and planning …

In urban cities, visual information on and along roadways is likely to distract drivers and lead
to missing traffic signs and other accident-prone (AP) features. To avoid accidents due to …

In this study, a novel wireless adaptive traffic signal control System architecture is proposed,
in which crowdsourced data is integrated to detect the traffic state on each approach of an …

The paper presents a model-based demand-responsive traffic control system for mixed
traffic conditions using sample travel time data. The model incorporates mixed traffic …

ABSTRACT A functioning roadway system is key to any society and economy. Traffic events
such as maintenance and accidents reduce roadway capacity and can have immediate …

The principle of system resilience is its ability to withstand disruptions and maintain an
equilibrium state. In urban network systems, adaptive traffic signal control (ATSC) has been …

Countdown timers at traffic signals display the time remaining for a phase to terminate,
influencing driver behaviour. Studies on their effects at the onset of yellow have generally …

Increasing usage of traffic cameras provides an opportunity to utilize them for smart city
applications. However, the efficacy of such systems is determined by their ability to detect …

Accurate traffic state estimation, vital for managing urban congestion, is often achieved
through simulation. Real-time data are invaluable for this, yet obtaining multisensor data is …