Real-time electric mobility simulation in metropolitan areas. A case study: Newcastle-Gateshead

This paper discusses the potential of emerging digital representations of built environments coupled with agent-based modelling (ABM). A new set of urban transportation data is provided as an input which is the electric vehicles (EVs) population of one of the UK metropolitan areas. The study is a part of a PhD research that focuses on investigating computer-aided software to develop a virtual route for electric mobility in the North Sea Region. An overview of agent-based simulation platforms is discussed. Electric mobility system has particular paradigms that differ from conventional urban transport systems; a comparison is presented followed by the recommended approach of integrating the two techniques (visualization and simulation). Finally, the architecture of agents’ algorithm within the EVs network is presented through a case study of virtual Newcastle-Gateshead model.

[1]  Margaret Horne,et al.  Virtual City Models: Avoidance of Obsolescence , 2012, eCAADe proceedings.

[2]  Sean Luke,et al.  MASON : A Multi-Agent Simulation Environment , 2008 .

[3]  P. Torrens,et al.  Geographic Automata Systems : A New Paradigm for Integrating GIS and Geographic Simulation , 2003 .

[4]  Martin Bell,et al.  Forecasting the pattern of urban growth with PUP: a web-based model interfaced with GIS and 3D animation , 2000 .

[5]  Dickson K. W. Chiu,et al.  A Multi-Modal Agent Based Mobile Route Advisory System for Public Transport Network , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[6]  Jillian Anable,et al.  Electric Vehicles: Will consumers get charged up? , 2011 .

[7]  C. Carneiro.  Communication and Visualization of 3D Urban Spatial Data According to User Requirements: Case Study of Geneva , 2008 .

[8]  R. Dalton,et al.  A heuristic approach for investigating the integration of electric mobility charging infrastructure in metropolitan areas: An agent-based modeling simulation , 2012, 2012 2nd International Symposium On Environment Friendly Energies And Applications.

[9]  A. Borshchev,et al.  From System Dynamics and Discrete Event to Practical Agent Based Modeling : Reasons , Techniques , Tools , 2004 .

[10]  Kamalakar Karlapalem,et al.  Multi agent simulation of unorganized traffic , 2002, AAMAS '02.

[11]  J. C. Brezet,et al.  Delft University of Technology Charging stations for urban settings the design of a product platform for electric vehicle infrastructure in Dutch cities , 2018 .

[12]  Klaus G. Troitzsch,et al.  Social Science Simulation — Origins, Prospects, Purposes , 1997 .

[13]  Massimiliano Petri,et al.  Multi agent systems: three behavioural frameworks integrated into a GIS , 2005 .

[14]  Steven L. Lytinen,et al.  Agent-based Simulation Platforms: Review and Development Recommendations , 2006, Simul..

[15]  T. H. Kolbe,et al.  CityGML: Interoperable Access to 3D City Models , 2005 .

[16]  Ian D. Bishop,et al.  Management of Recreational Areas: GIS, Autonomous Agents, and Virtual Reality , 2000 .

[17]  Michael Batty,et al.  Ucl Centre for Advanced Spatial Analysis Working Papers Series Key Challenges in Agent-based Modelling for Geo-spatial Simulation Paper 121 -sept 07 Key Challenges in Agent-based Modelling for Geo-spatial Simulation , 2022 .

[18]  Margaret Horne,et al.  Traffic Simulation in 3D World , 2009 .

[19]  Kay W. Axhausen,et al.  Agent-based simulation of travel demand: Structure and computational performance of MATSim-T , 2008 .

[20]  P. Haan,et al.  How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars—Part I: Model structure, simulation of bounded rationality, and model validation , 2009 .

[21]  Xinhao Wang,et al.  Integrating GIS, simulation models, and visualization in traffic impact analysis , 2005, Comput. Environ. Urban Syst..

[22]  Colin Ware,et al.  Information Visualization: Perception for Design , 2000 .

[23]  Dirk Helbing,et al.  How to Do Agent-Based Simulations in the Future: From Modeling Social Mechanisms to Emergent Phenomena and Interactive Systems Design , 2013 .

[24]  Charles M. Macal,et al.  Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation , 2007 .

[25]  Susan M Pietsch.  Computer Visualisation in the Design Control of Urban Environments: A Literature Review , 2000 .

[26]  Chris T. Kiranoudis,et al.  A GIS-based decision support system for planning urban transportation policies , 2004, Eur. J. Oper. Res..

[27]  F. Hall.  TRAFFIC STREAM CHARACTERISTICS , 1997 .

[28]  Bernard Moulin,et al.  Coupling Multiagent Geosimulation and Spatial OLAP for Better Geosimulation Data Analysis , 2007 .

[29]  Lars Åberg,et al.  Driver Behaviour in Intersections: Formal and Informal Traffic Rules , 2005 .

[30]  Bin Jiang,et al.  AGENT-BASED APPROACH TO MODELLING ENVIRONMENTAL AND URBAN SYSTEMS WITHIN GIS , 2000 .

[31]  Margaret Horne,et al.  An overview of virtual city modelling : emerging organisational issues , 2007 .

[32]  Charles Abraham,et al.  Mainstream consumers driving plug-in battery-electric and plug-in hybrid electric cars: A qualitative analysis of responses and evaluations , 2012 .

[33]  David Strahan.  Dump the pump , 2012 .

[34]  Dirk Helbing,et al.  Simulating dynamical features of escape panic , 2000, Nature.

[35]  Wilco Burghout,et al.  Hybrid microscopic-mesoscopic traffic simulation , 2004 .

[36]  Chunlian Jin,et al.  Impact Assessment of Plug-in Hybrid Vehicles on the U.S. Power Grid , 2010 .

[37]  J. Thøgersen,et al.  Marketing of electric vehicles , 1999 .

[38]  Mordechai Haklay,et al.  STREETS: an agent-based pedestrian model , 1999 .

[39]  K. Maat,et al.  Improving Sustainability in Urban Areas: Discussing the Potential for Transforming Conventional Car-based Travel into Electric Mobility , 2012 .

[40]  Margaret Horne,et al.  Diversity in virtual reality landscape modelling , 2006 .

[41]  Eric Bonabeau,et al.  Agent-based modeling: Methods and techniques for simulating human systems , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[42]  Yee Ming Chen,et al.  Towards Participatory Design of Multi-agent Approach to Transport Demands , 2009, ArXiv.

[43]  Ana L. C. Bazzan,et al.  A Distributed Approach for Coordination of Traffic Signal Agents , 2004, Autonomous Agents and Multi-Agent Systems.

[44]  Peter Vortisch,et al.  Microscopic Traffic Flow Simulator VISSIM , 2010 .