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View article: Prediction of Drivers’ Red-Light Running Behaviour in Connected Vehicle Environments Using Deep Recurrent Neural Networks
Prediction of Drivers’ Red-Light Running Behaviour in Connected Vehicle Environments Using Deep Recurrent Neural Networks Open
Red-light running at signalised intersections poses a significant safety risk, necessitating advanced predictive technologies to predict red-light violation behaviour, especially for advanced red-light warning (ARLW) systems. This research…
View article: A Review on Drivers’ Red Light Running Behavior Predictions and Technology Based Countermeasures
A Review on Drivers’ Red Light Running Behavior Predictions and Technology Based Countermeasures Open
Red light running at signalised intersections is a growing road safety issue\nworldwide, leading to the rapid development of advanced intelligent\ntransportation technologies and countermeasures. However, existing studies have\nyet to summ…
View article: A Feasible Solution for Rebalancing Large-Scale Bike Sharing Systems
A Feasible Solution for Rebalancing Large-Scale Bike Sharing Systems Open
City bikes and bike-sharing systems (BSSs) are one solution to the last mile problem. BSSs guarantee equity by presenting affordable alternative transportation means for low-income households. These systems feature a multitude of bike stat…
View article: Simulation Study on an ICT-Based Maritime Management and Safety Framework for Movable Bridges
Simulation Study on an ICT-Based Maritime Management and Safety Framework for Movable Bridges Open
Maritime management is a crucial concern for movable bridge safety. Irregular management of water vehicles near movable bridges may lead to collision among ships and bridge infrastructures, causing massive losses of life and property. The …
View article: Crashes classification in naturalistic driving scenarios using random forest machine learning algorithm
Crashes classification in naturalistic driving scenarios using random forest machine learning algorithm Open
This research analyses the viability of utilising observed kinematics in machine learning models to identify safety critical events (SCE’s). There is a need for efficient algorithms to idenfitify SCE’s in large datasets, such as naturalist…