Ben Waterson

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An automated signalized junction control system that can learn strategies from a human expert has been developed. This system applies Machine Learning techniques based on Logistic Regression and Neural Networks to affect a classification of state space using evidence data generated when a human expert controls a simulated junction. The state space is(More)
This paper shows how temporal difference learning can be used to build a signalized junction controller that will learn its own strategies though experience. Simulation tests detailed here show that the learned strategies can have high performance. This work builds upon previous work where a neural network based junction controller that can learn strategies(More)
This research describes a novel Delay Minimisation Algorithm (DEMA) for traffic signal control, which operates without a predetermined stage order. The paper includes a technical review of the problems surrounding a more flexible system compared to the traditional `cycle based' approach. Applying DEMA to a case study intersection (currently controlled by(More)
An experiment was conducted using the InnovITS proving ground in Nuneaton. Thirty cars with volunteer drivers were asked to drive around a tight closed road circuit causing them to pass repeatedly through a cross-roads junction from all directions. The junction was signalized. In different test-runs of the experiment the traffic lights were controlled by(More)
This paper describes a modelling approach used to investigate the significance of key factors (vehicle type, compaction type, site design, temporal effects) in influencing the variability in observed nett amenity bin weights produced by household waste recycling centres (HWRCs). This new method can help to quickly identify sites that are producing(More)
Introduction The purpose of this review is to explore how supply chain management, specifically within the NHS, can be improved through the use of emerging information and communications technologies (ICT). There are a range of technologies, such as Radio Frequency Identification (RFID) and barcodes, available to logistics providers which expedite the(More)
This paper presents a methodology for fusing data from multiple sensors, including wireless devices, to make an estimation of the state of an urban traffic network. An extended Kalman filter is employed along with a state evolution model to make estimates of the state in a discretized network. Results are presented from simulation tests of signal(More)
This paper describes a technique for estimating vehicle journey times on non-signalised roads using 250-ms digital loop-occupancy data produced by single inductive loop detectors. The technique was assessed to see whether abnormal periods of traffic congestion (caused by accidents and special events) could be identified using the journey time estimates(More)