125,258 research outputs found
Design process
No full textChristina Waterson interviews Queensland interior designer Marisha McAuliffe about her PhD research into process, and why some people are drawn to create
Simulating the impacts of strong bus priority measures
No full textPolicies to reduce levels of traffic congestion and pollution in major urban areas often focus strongly on the concept of a sustainable transport system, but to achieve this vision a significant modal shift from private car to public transport will be required. This paper reports on a recent research study which provides a framework within which to model the behavioral responses of travelers following the implementation of strong bus priority measures (where road capacity is deliberately removed from general traffic and given to buses). A summary of the different behavioral responses which can be expected is given and results from a practical implementation of the framework which has been based on two commercial transport modeling packages (CONTRAM and TRIPS) are discussed. These results suggest firstly that the effect of implementing such strong bus priority measures is as dependent on the characteristics of the local travelers as on the scheme itself and secondly that implementing too strong a scheme may not benefit public transport overall
Comparison of signalized junction control strategies using individual vehicle position data
No full textThis paper is concerned with the development of control strategies for urban signalized junction that can make use of individual vehicle position data from localization probes on board the vehicles. Strategy development involves simulating the behaviour of vehicles as they negotiate junctions controlled by prototype strategies and evaluating performance. Two strategies are discussed in this paper, a simple auctioning agent strategy and an extended auctioning agent strategy where a machine learning approach is used to enable agents to be trained by a human expert to improve performance. The performance of these two strategies are compared with each other and with the MOVA algorithm in simulated tests. The results show that auctioning agents using individual vehicle position data can out perform MOVA, but that this performance can be improved further still by using learning auctioning agents trained by a human expert
A methodology for traffic state estimation and signal control utilizing high wireless device penetration
No full textThis 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 controllers on a network with three signalized junctions. Two signal control methods are tested: SCOOT and a machine learning junction control algorithm that employs the discretized state structure described in this paper. These tests represent lower and upper performance benchmarks and present a significant difference. The tests also demonstrate a framework for the future evaluation of the proposed methodology
Signal control using vehicle localization probe data
No full textThis paper presents a simulation test bed and methodology for evaluating urban signalized junction control algorithms that use localization probe data from all vehicles in the local area. The simulator is based on SIAS Paramics micro-simulation software with bespoke software modules built on top for automatic network generation, localization data processing and signal control. Localization algorithms tested use a hierarchical structure of auctioning agents. Early tests of control algorithms on an isolated signalized junction indicate performance that compares favourably with the MOVA algorithm using inductive loop data.<br/
An automated signalized junction controller that learns strategies by temporal difference reinforcement learning
No full textThis paper shows how temporal difference learning can be used to build a signalized junction controller that will learn its own strategies through 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 from a human expert was developed. In the simulations presented, vehicles are assumed to be broadcasting their position over WiFi giving the junction controller rich information. The vehicle’s position data are pre-processed to describe a simplified state. The state-space is classified into regions associated with junction control decisions using a neural network. This classification is the strategy and is parameterized by the weights of the neural network. The weights can be learned either through supervised learning with a human trainer or reinforcement learning by temporal difference (TD).Tests on a model of an isolated T junction show an average delay of 14.12s and 14.36s respectively for the human trained and TD trained networks. Tests on a model of a pair of closely spaced junctions show 17.44s and 20.82s respectively. Both methods of training produced strategies that were approximately equivalent in their equitable treatment of vehicles, defined here as the variance over the journey time distributions
Quantifying the potential savings in travel time resulting from parking guidance systems - a simulation case study
No full textParking Guidance and Information (PGI) signs are thought to enable a more efficient use of the available parking stock. Despite the installation of PGI systems in many cities and their operation for a number of years, there is a lack of reliable evidence of the size of the benefits that these systems can achieve. This paper describes the development of driver parking choice models (both during the journey and pre-trip) and the implementation of these models in the existing network traffic simulation model RGCONTRAM. Besides quantifying the effects of the PGI system on both the drivers seeking suitable parking spaces and the parking stock itself, this also enables quantification of the impact of parking choice on the wider network. Factors influencing PGI effectiveness are described and conclusions are drawn that illustrate the potential of PGI to induce the demand to spread more efficiently across the parking stoc
Understanding the explanatory factors leading to variability in charity collection bank yields: implications for bank placement and logistics strategy
No full textOxfam runs a network of approximately 570 textile donation banks across the UK for second-hand textiles and books to raise revenue for good causes around the world. These banks are placed in a variety of public places, such as car parks (public and supermarket) and recycling centres. Of real interest is the impact the underlying population characteristics have on the yield volume and stock quality at the site, and whether a better understanding of this relationship can be gained using historic fill levels over time, and quality audits of the stock donated. If a relationship exists and different postcodes can be shown to yield significantly different weights and quality of stock then banks can be targeted to certain areas, and the logistics optimised accordingly.Using a database of Monthly (April 2010 – March 2011) collection records (weights of donations collected per bank) for around 500 textile banks, this paper investigates the relative impacts of certain factors (season, location, proximity to services and levels of affluence) in influencing the variability in observed banks weights across Oxfam’s charity banks in England. It also presents a model which can be used to predict the weights of donations that should be generated by a bank given the profile of the region. For each factor, a weighting coefficient was calculated to generate predicted weights for each bank.Data for 2009-2010 have also been used for analysis to understand seasonal and longer term trends. Data regarding the key factors used within the model have been derived from a range of sources (eg. Office for National Statistics). In order to identify whether areas with different demographic, geographical and economic characteristics, yield significantly different volumes of saleable stock, a range of donation stock quality audits are currently being undertaken at a range of locations around the country based on the outcomes of the analysis
The use of simulation in the design of a road transport incident detection algorithm
No full textAutomatic incident detection is becoming one of the core tools of urban traffic management, enabling more rapid identification and response to traffic incidents and congestion. Existing traffic detection infrastructure within urban areas (often installed for traffic signal optimization) provides urban traffic control systems with a near continuous stream of data on the state of traffic within the network. The creation of a simulation to replicate such a data stream therefore provides a facility for the development of accurate congestion detection and warning algorithms. This paper describes firstly the augmentation of a commercial traffic model to provide an urban traffic control simulation platform and secondly the development of a new incident detection system (RAID-Remote Automatic Incident Detection), with the facility to use the simulation platform as an integral part of the design and calibration process. A brief description of a practical implementation of RAID is included along with summary evaluation results
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
