Towards an Integrated Approach for Sustainability

GBEN 2006: Global Built Environment: Towards an Integrated Approach for Sustainability

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9 781847 283962

Monjur Mourshed

ISBN 978-1-84728-396-2

GBEN 2006 International Conference on

Global Built Environment: Towards an Integrated Approach for Sustainability 11-12 September 2006 University of Central Lancashire Preston, Lancashire, United Kingdom

Edited by

Monjur Mourshed

Global Built Environment Network www.gben.org

Published by Global Built Environment Network c/o Department of Built Environment University of Central Lancashire Corporation Street, Preston, PR1 2HE United Kingdom Distributed by Lulu, Inc. 860 Aviation Parkway Suite 300, Morrisville NC 27560, USA.

Proceedings of the GBEN 2006 Conference

GLOBAL BUILT ENVIRONMENT: TOWARDS AN INTEGRATED APPROACH FOR SUSTAINABILITY Conference dates: 11-12 September 2006 Conference location: Preston, Lancashire, United Kingdom. GBEN 2006 is organised jointly by the Department of Built Environment, University of Central Lancashire; International Centre for Development and Environmental Studies, Edge Hill University and Department of Civil and Environmental Engineering, National University of Ireland, Cork, Ireland. Copyright © 2006 Monjur Mourshed. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the copyright holder. ISBN 978-1-84728-396-2 (pbk) Printed in the UK.

Introduction Integrated approaches are required to achieve built environment sustainability. However, there is little evidence of research into integration for sustainability, in particular the technology and the process of integration in a multidisciplinary setting. Questions may be asked as to the need for integration: is it a response to the inadequacies of stand-alone approaches or merely a diversion from the poorly implemented single sector policies. Sustainability has traditionally been looked as a way of satisfying certain indicators linked with performance criteria; be it environmental, economic or social. Such ‘satisfaction efforts’ usually overlook the process of achieving sustainability; hence affect the success of a policy or a project. This international conference aimed to bring together sustainability stakeholders from a wide variety of disciplines and sectors into a platform for discussions on integrated approaches for sustainability. 24 contributed papers and 1 keynote paper that discuss the various approaches for enhancing sustainability in the built environment are presented in this collection. Contributed papers were selected through a double-blind refereeing process, aimed at identifying novel approaches. In total, 61 papers have been submitted for review; among which 25 were recommended for publication by the scientific committee. The ratio of submitted to accepted papers was higher than 2:1. Papers published in this volume represent current trends in sustainability research. 3 papers deal with sustainable regeneration; ranging from multilevel pedestrian movements in public spaces to landscape stability and city centre regeneration. Issues related to the development of skills for sustainability are presented in 4 papers. Multidisciplinary approaches to sustainability pedagogy dominate the discussions in these papers. Sustainable planning is looked at in 4 papers. Inclusive environment, public participation in planning in developing countries and the mapping of knowledge for effective decision making is discussed in 3 papers. The fourth paper describes the development of a visual map of urban sustainability aimed at the decision making process. 3 papers discuss various approaches for performance based design/evaluation of buildings for sustainability. Sustainable construction is discussed in 4 papers, 2 of which deal with the legal aspects of sustainability/environment. 3 papers from integrated decision making track discuss various approaches for resource management, water management and data integration. Materials and deconstruction is looked at in 3 papers.

Acknowledgement The editor wishes to thank all of the GBEN 2006 committee members, reviewers and advisors for their support. Special thanks go to Fahmida Khandokar for helping the editor in copy editing and formatting the proceedings. Andrea Pye and Gail Simpson at UCLAN deserve a special mention for their support during the organisation of the conference. The sponsorship received from the Construction Knowledge Exchange is gratefully acknowledged.

Monjur Mourshed

Conference Co-Chair, GBEN 2006 Editor, Conference Proceedings

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Conference organization CONFERENCE CHAIRS Monjur Mourshed Conference Co-Chair University of Central Lancashire Preston, UK

Tasleem Shakur Conference Co-Chair Edge Hill University Ormskirk, UK

Hojjat Adeli Honorary Co-Chair Ohio State University Columbus, Ohio, USA

INTERNATIONAL SCIENTIFIC COMMITTEE Mike Clark University of Central Lancashire UK

Jenny Crawford Royal Town Planning Institute UK

Dee Davenport University of Central Lancashire UK

Bob Giddings Northumbria University UK

Donald Grierson University of Waterloo Canada

Marcus Keane National University of Ireland Cork, Ireland

Denis Kelliher National University of Ireland Cork, Ireland

Omar Khattab Kuwait University Kuwait

Yu Li Cardiff University UK

Peter Love Edith Cowan University Australia

Maria Murray-Carmichael University of Central Lancashire UK

Graham Paterson Robert Gordon University UK

Andrew Platten Elevate East Lancashire UK

Yaqub Rafiq University of Plymouth UK

Mahbub Rahman North South University Bangladesh

Ashraf Salama KFUPM Saudi Arabia

Ronald Smith University of Central Lancashire UK

QM Mahtab-Uz Zaman BRAC University Bangladesh

ORGANISED JOINTLY BY

SPONSORED BY

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Table of Contents

Keynote paper Novel Computational Methods for Intelligent Transportation Systems Hojjat Adeli

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Contributed papers Theme: Sustainable Regeneration Multilevel Pedestrian Movement: Does Configuration Make Any Difference? Afroza Parvin, Ye Arlen Min and Jia Beisi

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On Improving City Centres’ Sustainability: Going Beyond Technical Solutions Naima Chabbi-Chemrouk and Ouassim Chemrouk

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The Evaluation of Human Impact on Landscape’s Stability in Czech Republic Adam Vokurka

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Theme: Pedagogy for Sustainability Earth House: Nurturing a Creative Response to Sustainability Issues - a Live Project Ian Standen and Rachel Grainger

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Development of a Distance-learning based Post-Graduate Programme on Sustainable Architecture Monjur Mourshed

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Experts in Team: Teaching Sustainability in an Interdisciplinary Setting Annemie Wyckmans, Anne Grete Hestnes and Anne Sigrid Nordby

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A Multi-Disciplinary Approach to the Pedagogy of Sustainability: Architecture, Landscape and Building Management Professionals Julie Gwilliam, Paola Sassi, David Skidmore, Derek Jones and Val Wynne

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Theme: Sustainable Planning Public Participation in Planning in Developing Countries: the Example of Akure, Ondo State, Nigeria Afolabi Aribigbola

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Inclusive Environment and Public Housing Design for Senior Citizens in Hong Kong Faruk Mohammad, Alexandre Amato and Richard Frewer

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Mapping Knowledge For Effective Decision Making and in Bringing About Change in the Provision of Sustainable Urban Environment Solutions Charles Egbu

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Development of a Visual Map of Urban Sustainability Mohamed El-Haram, Jonathan Walton, Francis Edum-Fotwe, Malcolm Horner, Cliff Hardcastle, Andrew Price and Deborah Maxwell

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Theme: Sustainable Construction Sustainable Construction in New Zealand? ‘Regulation and Policy Lessons from Europe’ Ailsa Ceri Warnock

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Ecotropy: Developing Sustainable Construction Strategies Don Krug and Madalina Wierzbicki Neagu

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Remember – Reveal - Construct Sally Stone

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Green Procurement - Competition and State Aid Dee Davenport

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Theme: Integrated Decision Making Resource Management in New Zealand - Decision-making for Sustainability Kenneth Palmer

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Support for Integrative Decision Making in More Sustainable Urban Water Management Louise Hurley, Stephen Mounce and Richard Ashley

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Sustainable Building Futures - Current Practice and Possibilities for Data Interaction Between Disciplines and Across Software Platforms during Preliminary and Detail Design Tahar Kouider, Graham Paterson and Jonathan Scott

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Theme: Materials and Deconstruction Lifetime and Demountability of Building Materials Anne Sigrid Nordby, Anne Grete Hestnes and Bjørn Berge

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Revitalisation of Existing Buildings through Sustainable Non-Destructive Floor Space Relocation Thorsten M. Lömker

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Light Steel Framing: Improving the Integral Design Aitor Amundarain, José L. Torero, Asif Usmani and Ahmad M. Al-Remal

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Theme: Performance Based Design Thermal Modelling, Performance Analysis of Building Fabric Options and Climate Change Impact Haşim Altan and Ian Ward

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Measured Indoor Environments Compared to Accepted Standards: A Case Study in Clerkenwell, London Mohamed Refaee, Steve Sharples, Gemma Moore, Mags Adams, Ben Croxford and Trevor Cox

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Optimised Building Form for Environmental Sustainability Monjur Mourshed, Denis Kelliher and Marcus Keane

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Novel Computational Models for Intelligent Transportation Systems Keynote paper Hojjat Adeli * Department of Civil and Environmental Engineering and Geodetic Science, The Ohio State University, 470 Hitchcock Hall 2070 Neil Avenue, Columbus, Ohio 43210, USA.

ABSTRACT Intelligent transportation systems (ITS) provide solutions for alleviating the increasing freeway congestion problems through the optimum use of existing freeway network rather than adding more freeways or lanes to the existing freeways with its associated destruction of the environment. As such, they are instrumental in the quest towards a more sustainable environment. In this Keynote Lecture, an overview of the research performed in the area of intelligent transportation systems by the author and his associates in recent years is presented. The focus is on development of novel computational models through adroit integration of computational intelligence techniques such as neural networks and fuzzy logic with wavelets.

Keywords Fuzzy logic, incident detection, intelligent freeways, intelligent transportation systems, ITS, neural networks, sensors, wavelets.

INTRODUCTION There has been a steady increase in both rural and urban freeway traffic in recent years resulting in congestion in many freeway systems. The freeway traffic congestion can no longer be dealt with simply by extending more highways for economical and environmental reasons. Intelligent transportation systems (ITS) provide solutions for alleviating the increasing congestion problems through optimum use of existing freeway network to manage the traffic congestion. As such, they are instrumental in the quest towards a more sustainable environment (Adeli and Karim 2005). In recent years computational intelligence approaches including neurocomputing, evolutionary computing, and fuzzy logic have been employed successfully to solve complex or mathematically intractable problems. The author and his associates have advocated and advanced a multi-paradigm computational intelligence problem solving approach to solve increasingly complicated real-life problems accurately and efficiently (Adeli and Hung 1995; Adeli 1998; Adeli and Kumar 1999). In this Keynote Lecture, an overview of the research performed in the area of intelligent transportation systems by the author and his associates in recent years is presented. The focus is on development of novel computational models through adroit integration of computational intelligence techniques such as neural networks and fuzzy logic with wavelets (Daubechies 1992; Mallat 1989). It is also demonstrated how wavelets can be used to enhance computational intelligence for chaotic and complex pattern recognition problems. *Corresponding author. Email address: [email protected] Copyright © 2006 Global Built Environment Network. All rights reserved.

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Novel Computational Models for Intelligent Transportation Systems

TRAFFIC INCIDENT DETECTION Reliable automatic detection of traffic incidents is required in intelligent freeway systems. The traffic incident detection problem can be viewed as recognizing incident patterns from the incident-free patterns. Samant and Adeli (2000) present a robust traffic feature extraction model using discrete wavelet transform (DWT) and linear discriminant analysis (LDA). The DWT is first applied to raw traffic data and the finest resolution coefficients representing the random fluctuations of traffic are discarded. Next, LDA is employed to the filtered signal for further feature extraction and reducing the dimensionality of the problem. Adeli and Samant (2000) present a computational model for automatic traffic incident detection using discrete wavelet transform, linear discriminant analysis, and neural networks. The traffic flow is viewed as a signal, with traffic incidents as well as other traffic patterns such as traffic bottleneck or compression wave having different time-space properties. Wavelet transform and linear discriminant analysis are used for feature extraction, de-noising, and effective preprocessing of data before the adaptive conjugate gradient neural network (ACGNN) model of Adeli and Hung (1994) is used to make the traffic incident detection. Simulated as well as actual traffic data are used to test the model. It is shown that use of the wavelets to de-noise the chaotic traffic data increases the incident detection rate, reduces the false alarm rate and the incident detection time, and improves the convergence of the neural network training algorithm substantially. Researchers have presented freeway traffic incident detection algorithms by combining the adaptive learning capability of neural networks with imprecision modeling capability of fuzzy logic (Zadeh 1978). Samant and Adeli (2001) show that the performance of a fuzzy neural network algorithm can be improved through preprocessing of data using a wavelet based feature extraction model. In particular, the discrete wavelet transform (DWT) de-noising and feature extraction model proposed by Samant and Adeli (2000) is combined with the fuzzyneural network approach presented by Hsiao et al. (1994). It is shown that substantial improvement can be achieved using the data filtered by DWT. Use of the wavelet theory to denoise the traffic data increases the incident detection rate, reduces the false alarm rate and the incident detection time, and improves the convergence of the neural network training algorithm substantially. Adeli and Karim (2000) present a new multi-paradigm intelligent system approach to the solution of the freeway traffic incident detection employing advanced signal processing, pattern recognition, and classification techniques. The methodology effectively integrates fuzzy, wavelet, and neural computing techniques to improve reliability and robustness. A waveletbased de-noising technique is employed to eliminate undesirable fluctuations in observed data from traffic sensors. Fuzzy c-mean clustering is used to extract significant information from the observed data and to reduce its dimensionality. A radial basis function neural network is developed to classify the de-noised and clustered observed data. The new model produced excellent incident detection rate with no false alarms when tested using both real and simulated data. The performance of the new fuzzy-wavelet radial basis function neural network (RBFNN) freeway incident detection model is evaluated and compared with the benchmark California algorithm #8 using both real and simulated data (Karim and Adeli 2002a). The evaluation is based on three quantitative measures of detection rate, false alarm rate, and detection time, and the qualitative measure of algorithm portability. The new algorithm outperformed the California algorithm consistently under various scenarios. False alarms are a major hindrance to the widespread implementation of automatic freeway incident detection algorithms. The false alarm rate ranges from 0 to 0.07 % for the new algorithm and 0.53 to 3.82% for the California algorithm. The new fuzzy-wavelet RBFNN freeway incident detection model is a single-station pattern-based algorithm that is computationally efficient and requires

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no re-calibration. The new model can be readily transferred without re-training and without any performance deterioration. Karim and Adeli (2002b) also present a new two-stage single-station freeway incident detection model based on advanced wavelet analysis and pattern recognition techniques. An energy representation of the traffic pattern in the wavelet domain is found to best characterize incident and non-incident traffic conditions. False alarm during recurrent congestion and compression waves is eliminated by normalization of a sufficiently long time-series pattern. The model is tested under several traffic flow scenarios including compression wave conditions. It produced excellent detection and false alarms characteristics. The model is computationally efficient and can readily be implemented on-line in any Advanced Traveler Management System (ATMS) without any need for re-calibration.

FREEWAY WORK ZONE CAPACITY AND QUEUE ESTIMATION Karim and Adeli (2003) present an adaptive computational model for estimating the work zone capacity and queue length and delay taking into account the following factors: number of lanes, number of open lanes, work zone layout, length, lane width, percentage trucks, grade, speed, work intensity, darkness factor, and proximity of ramps. The model integrates judiciously the mathematical rigor of traffic flow theory with the adaptability of neural network analysis. A radial-basis function neural network model is developed to learn the mapping from quantifiable and non-quantifiable factors describing the work zone traffic control problem to the associated work zone capacity. This model exhibits good generalization properties from small set of training data, a specially attractive feature for estimating the work zone capacity where only limited data is available. Queue delays and lengths are computed using a deterministic traffic flow model based on the estimated work zone capacity. The result of this research was used to develop an intelligent decision support system to help work zone engineers perform scenario analysis and create traffic management plans consistently, reliably, and efficiently (Jiang and Adeli 2004).

MESOSCOPIC-WAVELET FREEWAY WORK ZONE FLOW AND CONGESTION MODEL Adeli and Ghosh-Dastidar (2004) present a new mesoscopic-wavelet model for simulating freeway traffic flow patterns and extracting congestion characteristics. A traffic speed-density relationship is introduced with a lane drop factor to take into account lane closures in freeway work zones. Patterns of multiple parameters are inputted to a congestion feature extraction algorithm. An approximate solution for this equation is found by space-time discretization. The high frequency fluctuations of the signal are not recognizable at normal resolutions. To overcome this problem, a multi-resolution wavelet filter is introduced in the proposed model to enhance traffic features and extract congestion characteristics from the traffic data. Fourthorder Coifman wavelets are used for filtering because of their good approximation for highresolution scaling. Recently, Ghosh-Dastidar and Adeli (2006) developed a new neural network-wavelet microsimulation model to track the travel time of each individual vehicle for traffic delay and queue length estimation at work zones. The model incorporates the dynamics of a single vehicle in changing traffic flow conditions. The extracted congestion characteristics obtained from the mesoscopic-wavelet model are used in a Levenberg-Marquardt backpropagation (BP) neural network for classifying the traffic flow as free flow, transitional flow, and congested flow with stationary queue. The neural network model is trained using simulated data and tested using both simulated and real data. The computational model presented is applied to five examples of freeways with two and three lanes and one lane closure with varying entry flow or demand

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patterns. The new micro-simulation model is more accurate than macroscopic models and substantially more efficient than microscopic models.

TRAFFIC FLOW FORECASTING Accurate and timely forecasting of traffic flow is of paramount importance for effective management of traffic congestion in ITS. Over the past decade, a number of papers have been published on the application of neural network models for forecasting traffic flow taking advantage of their ability to capture the indeterministic and complex nonlinearity of time series. However, the existing neural network-based approaches have their inherent shortcomings such as lack of an efficient constructive model (for example, requiring arbitrary selection of the number of hidden nodes), slow convergence rate resulting in excessive computation time, and entrapment in a local minimum. Besides, these methods do not incorporate the characteristics of traffic flow, resulting in poor reliability of traffic flow forecasting model. Recently, Jiang and Adeli (2005) developed a novel nonparametric dynamic time-delay recurrent wavelet neural network (WNN) model for forecasting traffic flow. The discrete wavelet packet transform (DWPT) is employed for analysis of traffic flow time series and determining their self-similar, singular, and fractal properties discovered in the denoised traffic flow. The model incorporates both the time of the day and the day of the week of the prediction time. This research advances the conventional neural network significantly by presenting a dynamic wavelet neural network model as a powerful approach for capturing the dynamics of the traffic flow and for pattern recognition with enhanced feature detection capability. The proposed methodology provides a powerful tool in identifying singularities in the traffic flow, removing the noise, and forecasting the traffic flow effectively. The methodology can be used for longterm traffic flow forecasting in addition to short-term forecasting. Short-term traffic flow forecasting is of great interest in on-line ITS applications and long-term forecasting is of great interest in transportation planning applications.

ACKNOWLEDGMENT This presentation is based on the research sponsored by Ohio Department of Transportation and Federal Highway Administration.

REFERENCES Adeli, H. and Ghosh-Dastidar, S. (2004). Mesoscopic-Wavelet Freeway Work Zone Flow and Congestion Feature Extraction Model. Journal of Transportation Engineering, ASCE, 130(1), 94-103. Adeli, H. and Hung, S.L. (1994). An adaptive conjugate gradient algorithm for efficient training of neural networks. Applied Mathematics and Computation, 62, 81-102. Adeli, H. and Hung, S.L. (1995). Machine Learning - Neural Networks, Genetic Algorithms, and Fuzzy System. New York: John Wiley. Adeli, H. and Karim, A. (2000). Fuzzy-Wavelet RBFNN Model for Freeway Incident Detection. Journal of Transportation Engineering, ASCE, 126(6), 464-471. Adeli, H. and Karim, A. (2005). Wavelets in Intelligent Transportation Systems. New Jersey: Hoboken. Adeli, H. and Kumar, S. (1999). Distributed Computer-Aided Engineering. Boca Raton, Florida: CRC Press. Adeli, H. and Park, H.S. (1998). Neurocomputing in Design Automation. Boca Raton, Florida: CRC Press.

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Adeli, H. and Samant, A.M. (2000). An Adaptive Conjugate Gradient Neural Network Wavelet Model for Traffic Incident Detection. Computer-Aided Civil and Infrastructure Engineering, 15(4), 251-260. Daubechies, I (1992). Ten Lectures on Wavelets. Philadelphia, PA: SIAM. Ghosh-Dastidar, S. and Adeli, H. (2006). Neural Network-Wavelet Micro-Simulation Model for Delay and Queue Length Estimation at Freeway Work Zones. Journal of Transportation Engineering, ASCE, 132(4), 331-341. Hsiao, C.H., Lin, C.T., and Cassidy, M. (1994). Application of fuzzy logic and neural networks to automatically detect freeway traffic incidents. Journal of Transportation Engineering, 120(5), 753-771. Jiang, X. and Adeli, H. (2004). Object-Oriented Model for Freeway Work Zone Capacity and Queue Delay Estimation. Computer-Aided Civil and Infrastructure Engineering, 19(2), 144156. Jiang, X. and Adeli, H. (2005). Dynamic Wavelet Neural Network Model for Traffic Flow Forecasting. Journal of Transportation Engineering, ASCE, 131(10), 771-779. Karim, A. and Adeli, H. (2002a). Comparison of the Fuzzy – Wavelet RBFNN Freeway Incident Detection Model with the California Algorithm. Journal of Transportation Engineering, ASCE, 128(1), 21-30. Karim, A. and Adeli, H. (2002b). Incident Detection Algorithm Using Wavelet Energy Representation of Traffic Patterns. Journal of Transportation Engineering, ASCE, 128(3), 232-242. Karim, A. and Adeli, H. (2003). Radial Basis Function Neural Network for Work Zone Capacity and Queue Estimation. Journal of Transportation Engineering, ASCE, 129(5), 494-503. Mallat, S.G. (1989). A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Transaction on Pattern Analysis and Machine Intelligence, 11(7), 674-693. Samant, A. and Adeli, H. (2000). Feature Extraction for Traffic Incident Detection using Wavelet Transform and Linear Discriminant Analysis. Computer-Aided Civil and Infrastructure Engineering, 15(4), 241-250. Samant, A. and Adeli, H. (2001). Enhancing Neural Network Incident Detection Algorithms using Wavelets. Computer-Aided Civil and Infrastructure Engineering, 16(4), 239-245. Wu, M. and Adeli, H. (2001). Wavelet-Neural Network Model for Automatic Traffic Incident Detection. Mathematical & Computational Applications, 6(2), 85-96. Zadeh, L. (1978). Fuzzy Set as a Basis for a Theory of Possibility. Fuzzy Sets and Systems, 1(1), 3-28.

BIO SKETCH OF THE AUTHOR Hojjat Adeli is Professor of Civil and Environmental Engineering and Geodetic Science, and the holder of Lichtenstein Professorship. He has authored over 410 research and scientific publications in various fields of computer science, engineering, and applied mathematics since 1976 when he received his Ph.D. from Stanford University at the age of 26. His wide-ranging research has been published in 72 different journals. He has authored ten books including Machine Learning - Neural Networks, Genetic Algorithms, and Fuzzy Systems, Wiley, 1995, Neurocomputing for Design Automation, CRC Press, 1998, Distributed Computer-Aided Engineering, CRC Press, 1999, Control, Optimization, and Smart Structures - HighPerformance Bridges and Buildings of the Future, Wiley, 1999, and most recently Wavelets in Intelligent Transportation Systems, Wiley, 2005. He has also edited twelve books including Knowledge Engineering - Vol. I - Fundamentals and Vol. II -Applications, McGraw-Hill, 1990, Intelligent Information Systems, IEEE Computer Society, 1997. He is the Founder and Editor5


in-Chief of the international research journals Computer-Aided Civil and Infrastructure Engineering, now in 21st year of publication and Integrated Computer-Aided Engineering, now in 14th year of publication. He is also the Editor-in-Chief of International Journal of Neural Systems. In 1998 he received the Distinguished Scholar Award from The Ohio State University “in recognition of extraordinary accomplishment in research and scholarship.” In 2005, he was elected Honorary Member, American Society of Civil Engineers (ASCE) “for wide-ranging, exceptional, and pioneering contributions to computing in many civil engineering disciplines and extraordinary leadership in advancing the use of computing and information technologies in civil engineering throughout the world.” In 2006 he received the ASCE Construction Management Award “For development of ingenious computational and mathematical models in the areas of construction scheduling, resource scheduling, and cost estimation.”

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Multilevel Pedestrian Movement: Does Configuration Make Any Difference? Afroza Parvin*, Ye Arlen Min, Jia Beisi Department of Architecture, The University of Hong Kong, Hong Kong.

ABSTRACT Hong Kong’s built environment is characterized by compact urban form with extreme high-density and verticality where the multilevel pedestrian movement takes place in the complex multilevel spatial structure (MSS). Using a computerbased technique known as “space syntax” this study investigates the configuration of the MSS to understand its impact upon the patterns of multilevel pedestrian movement. Owing to the sheer complexity of high-density built environment an integrated multilevel movement model (IMMM) that includes both spatial properties and urban design variables is developed to describe observed patterns of movement in two case study areas. In addition to the conventional axial mapping the study includes analysis of ‘node map’ as the basis of the integrated model. Preliminary results from the case study suggest notwithstanding the effects of urban design parameters spatial configuration has significant effects on the patterns of pedestrian movement. Towards an efficient space system, the study concludes with some strategic urban design guidelines for the high-density built environment.

Keywords

High-density, Pedestrian Movement, Configuration, Space Syntax, Hong Kong.

INTRODUCTION Cities are large physical objects animated and driven by human behavior (Hillier 2005b). In Hong Kong, the multilevel spatial system is more than an artifact that has its impact on the spatial behavior of the people (Parvin et al. 2006b). Spatial movement in such settings is strongly biased by the local design factors and their interactions (Chang and Penn 1998). In Hong Kong, the urban design parameters like presence of Mass Transit Railway (MTR) station; location and type of vertical transitional spaces; grade separated multiple levels; internal rout structure directly connected to the MTR station; and presence of mixed land uses have strong influence on the way people use the spaces (Parvin et al. 2006a). Regarding the urban form of Hong Kong, it has been cited in several occasions (Jenks and Buegess 2000; Zhang 2000; Zaman et al. 2000; Lam 2002; Lee 1979) as an indication of what contemporary urban critics are advocating for. But little is done about the ways in which strategic architectural decision that results in particular configuration may have social consequences (Hillier et al. 1993). Empirical research shows, in the compact built environment accessibility to well connected mixed land use contributes to the vitality of the urban life (Coorey and Lau 2005; Parvin et al. 2006c). However, in the first instance, it should be reckoned that the urban spatial form constitutes the ‘material base’ (Harvey 1989) for sustaining process of human interaction and normative development (Chui 2003). To achieve the aspired ‘material base’, the understanding of how people’s spatial behavior and spatial *Corresponding author. Email address: [email protected] Copyright © 2006 Global Built Environment Network. All rights reserved.

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Multilevel Pedestrian Movement: Does Configuration Make Any Difference?

elements are embedded in the specific relational patterns is crucial. To this end, the study focuses on two important issues - firstly, what is topological character of the configuration; and secondly, what is the impact of the configuration on the pedestrian behavior of the people. It is hypothesized that in high density multilevel urban complexes the spatial configuration has significant impact on the patterns of pedestrian movement. In order to test the research hypothesis the study applies a computer-based technique known as “space syntax” for the spatial analysis of a case study area and develops an ‘integrated multilevel movement model’ (IMMM). It investigates the public circulation spaces both indoor and outdoor. It also involves the study of movement of people in terms of density of people using the spaces.

METHODOLOGICAL CONSIDERATIONS To study a large multilevel complex, the study applies the spatial modeling and observational techniques of the space syntax, developed by Hillier and Hanson (1984)1. To the description multilevel movement, the study develops an integrated multilevel movement model (IMMM) that includes both configurational properties and urban design variable in one statistical model. In edition to the conventional syntactic properties the study includes depth properties of node map. The configurational properties included in the IMMM are Two interrelated depth properties (SHP) (To include the effect of public transportations both depth are calculated from the MTR); Comparative integration values, and Global interaction value. The urban design variables included in the IMMM are grade separation; and vertical transitional spaces. The mathematical model is: M IMMM = minimum [a (H + ln(P) + L)] + G + ln(T)

(1)

Where, a is the comparative integration value; H is the horizontal depth; P is the point depth; L is the level value; G is the global interaction space between MTR and peripheral routs; and T is the value of transitional space (sum of the scores)2. To test the predictability or goodness of fit of the IMMM model in terms of the strength of correlation (value of r2) simple regression and correlation analysis is conducted. Due to the similar nature of research problem, the conceptual framework of the methodology is developed in light of the methodology proposed by Chang and Penn (1998)3 while the analytical framework; modifications of syntactic properties; and urban design parameters are derived from the context of the study.

Field observation In order to reveal the pattern of movement field observations are carried out. The observation rout includes fair sample of spaces within the axial spaces or segments of axial spaces representing both indoor and outdoor public circulation spaces; and major and minor pedestrian streets. The movement data is obtained using the ‘gate’4 method of observation, in which a stationary observer counts all people with respect to crossing a notional gate across the survey segment. The data is gathered at five different period of a day (8:00-9:00am; 12:001:00am; 2:00-3:00pm; 5:00-6:00pm; and 7:00-8:00pm) for a total of 25 minutes (five minutes observations of five time periods through one week day). The data is expressed in terms of people per hour in the axial map of the case study area (Figure 3).

The study areas Two multilevel urban complexes 1) Metro City; and 2) Telford Gardens/Telford Plazas have been studied. Figure 1a and Figure 1b show the survey map of the study areas and their immediate surroundings. Both the case study areas are large multilevel complex, with predominantly higher density5; multilevel spatial system; primacy of pedestrian movement; and mainly residential development with mixture of various types of land uses. The land uses 8

Parvin, A., Min, Y.A. and Beisi, J.

are systematically arranged in different levels in terms of shopping complex, major government institution or community (GIC) are provided in the podium while apartment blocks start from the podium level above the shopping plazas. In both complexes MTR station is the focal point of the whole development and acts as the major generator of movement.

MTR Station

Area of observation

Surroundings area

b

a

Figure 1: (a) Survey map showing the Metro City and its surrounding Po Lam area, (b) Survey map of Telford Gardens/Telford Plazas.

PATTERNS OF MOVEMENT AND SPATIAL CONFIGURATION OF THE STUDY AREAS Distribution of movement density The field observation reveals6, in the both complexes the MTR station acts as the main generator of movement. In the Metro City, major circulation takes place on the major circulation spine along the Mau Yip road at ground level (1374 person per hour) that is directly connected to the MTR station and stretches along the commercial land use areas; and in two footbridges (5598 person per hour) those connect the MTR station to shopping plazas at level two. Field observation in the Telford Gardens/Telford Plazas shows (Figure 3), major circulation takes place along the Boulevard on the upper ground level (9774 person per hour); and the transitional space (around 8944 person per hour) between the commercial Plaza connecting the MTR Station to the surrounding and to the commercial areas respectively. In general, in both complexes, highest movement density includes mostly resident people and some visitors coming from the MTR station. The spaces around the commercial retail outlets and MTR station are found with higher density while space around the residential or GIC facilities only are found with lower density. Vertical transitional spaces (mostly escalators) directly connecting the levels with commercial use to the MTR exits are found with maximum density of movement. The movement density changes dramatically in different times of the day particularly in the early morning and in the evening it is found higher. As a whole, the movement pattern implies strong influence of MTR station; mixture of different land uses; and type and location of vertical transitional spaces. Apart from these, the footbridges connecting the complex to its surrounding areas also influence the movement patterns.

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Spatial analysis The syntactic analysis reveals similar patterns of axial integration in both the case study areas. Figure 2a and 2b show the screen output7 of the composite axial integration maps of the Metro City and Telford Gardens/Telford Plazas respectively, where different levels are ‘unlinked’ and connected only by the axial lines that represent the vertical transitional spaces. For the Metro City area the integration map clearly shows the main structure of integration in which the major circulation spine at ground level (that stretches from the commercial areas up to the residential estates); and at level 2 spaces connecting the MTR exits and commercial Plazas, and the atrium space of Plaza Two are picked up as the main focus of integration in the area. Level 1 and 3 appear relatively segregated with lower connectivity to the integration core. Telford Gardens Level 3

Boulevard Plaza II

Level 1

Ground level

Plaza I MTR Station

Level 2

b

a

Figure 2: (a) Global integration map of the Metro City, (b) Local integration map of Telford. For the Telford Gardens/Telford Plazas, the integration map clearly shows the main structure of integration in which the pedestrian spaces in front of the commercial Plazas; space along the Boulevard; circulation spaces connecting the Plazas; and the major circulation spine of commercial Plazas that connects the atriums on the third floor are picked up as the main focus of integration in the area. Unlike the Metro city upper floors of the Plazas (third to sixth floor) appear to be segregated while the MTR Station occupies the most segregated part. The correlation analysis between the spatial properties shows different patterns of spatial configuration in the study areas. In metro City the system reveals a moderate local global correlation (r2 = 0.33), relatively weak accessibility (r2 = 0.06), and poor intelligibility (r2 = 0.18) while in Telford Gardens/Telford Plazas, the system shows a strong local global correlation (r2 = 0.52), very good accessibility (r2=0.81)8, and moderate intelligibility (r2=0.27). However, as a whole the configuration of the Telford Gardens/Telford Plazas appears to better integrated with a shallow integration core with better connectivity to the to whole space system while the Metro City appears to be less integrated with lack of connectivity to the centrally concentrated integration core that results in a broken interface between the global and local spaces that leads the movement to a pure origin destination movement pattern (Hillier, 1996, p. 178).

Relation between configuration and movement: Emerging Hypothesis Comparing the figures of patterns of movement in terms of the most dense areas (shown in 10


bold lines) (Figure 3a for Metro City and 4a for Telford Gardens/Telford plazas) and the pattern of spatial integration in terms of 10% integration core (Figure 3b for Metro City and 4b for Telford Gardens/Telford plazas), it is found that, in both cases the distribution of movement density does not fully conform to the to the patterns of axial integration. The scattergrams (Figure 5a and 5b) plotting observed density of movement against integration values reveal a weak correlation of r2 = 0.191 for Metro City and r2 = 0.189 for Telford Gardens/Telford Plazas. It implies, the configuration alone is not significant enough to describe the patterns of movement in high-density multilevel space system. Level 3

Level 3 Level 1

Level 1

Ground level

Ground Level Level 2

Level 2

b

a

Figure 3: (a) Movement density in Metro city, (b) 10% integration core of Metro city.

b

a

Figure 4: (a) Daily mean movement rate per hour, (b) 10% Integration Global Core. From the empirical observation it is found that access to the spaces in the upper levels is confined to the transitional spaces. As the conventional spatial modelling does not take into account the prominence of MTR, grade separation and vertical transition in analyzing the accessibility or intelligibility of the system, in the preliminary analysis it appears to be in less conformation to the real situation found from the field observation. However, from this initial findings it is hypothesized that, in high-density the multilevel spatial structure the effect of configuration on space use is influenced by the multiple interacting urban design parameters. Furthermore, the weak correlation between integration and observed movement patterns suggests that, to the description of multilevel movement syntactic analysis needs to calibrate taking the multiple interacting effects of these urban 11


design variables into account.

a

Slope = 3.0535731 Intercept = 4.6793254 RSquare = 0.189734 Mean = 7.421552 Global Integ Mean = 0.98132468

9

log_mov

8 7 6 5

b

4 .4

.5

.6

.7

.8

.9

1

1.1 1.2

1.3

global_integ Figure 5: (a) Result of Space Syntax analysis for Metro City (b) Result of Space Syntax analysis for Telford.

EFFECT OF CONFIGURATION: AN INTEGRATED MULTILEVEL MOVEMENT MODEL In order to test the emerging hypothesis the integrated multilevel movement model includes both configurational properties and the urban design parameters in a single statistical model9. The whole model shows, inclusion of the sum of two depth properties (SHP) shows significant increase in correlation coefficient in both cases. It suggests the dependence of movement pattern on the topological distance and intersections. Inclusion of comparative integration value (a) results in dramatic increase in the correlation coefficient of SaHP in Metro City while it remains the same in Telford Gardens/Telford Plazas. 12


Table 1: Development of the IMMM Model Category of variables

Variables

Formula

r2 Metro City

r2 Telford

P value

Configurational variables only

R2

R = 2(d-1)/k-2

0.19

0.19

-

SHP

min(H+lnP)

0.33

0.29