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Application of Complex Networks Theory in Urban Traffic Network Researches

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Abstract

Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urban traffic network studies have been fruitful, but have suffered from the lack of a systematic cognitive and integration framework. This paper reviews complex network theory related knowledge and discusses its applications in urban traffic network studies in several directions. This includes network representation methods, topological and geographical related studies, network communities mining, network robustness and vulnerability, big-data-based research, network optimization, co-evolution research and multilayer network theory related studies. Finally, new research directions are pointed out. With these efforts, this physics-based concept will be more easily and widely accepted by urban traffic network planners, designers, and other related scholars.

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References

  • Ahuja RK, Magnanti TL, Orlin JB (1993) Network flows: theory, algorithms, and applications

  • Albert R, Albert I, Nakarado GL (2004) Structural vulnerability of the North American power grid. Phys Rev E 69(2):025103

    Google Scholar 

  • Albert R, Barabási A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys 74(1):47

    Google Scholar 

  • Albert R, Jeong H, Barabási A-L (2000) Error and attack tolerance of complex networks. Nature 406(6794):378–382

    Google Scholar 

  • Albert S-R, Sergio G, Alex A (2016) Congestion induced by the structure of multiplex networks. Phys Rev Lett 116(10):108701

    Google Scholar 

  • Aleta A, Meloni S, Moreno Y (2016) A multilayer perspective for the analysis of urban transportation systems. arXiv preprint arXiv:1607.00072

  • Andersson C, Frenken K, Hellervik A (2006) A complex network approach to urban growth. Environ Plan A 38(10):1941–1964

    Google Scholar 

  • Angeloudis P, Fisk D (2006) Large subway systems as complex networks. Physica A: Statistical Mechanics and its Applications 367:553–558

    Google Scholar 

  • Balijepalli C, Oppong O (2014) Measuring vulnerability of road network considering the extent of serviceability of critical road links in urban areas. J Transp Geogr 39:145–155

    Google Scholar 

  • Barabasi A-L, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512

    Google Scholar 

  • Barthelemy M (2011) Spatial networks. Phys Rep 499(1-3):1–101. https://doi.org/10.1016/j.physrep.2010.11.002

    Article  Google Scholar 

  • Barthelemy M (2018) Morphogenesis of spatial networks. Berlin, Germany: Springer International Publishing

    Google Scholar 

  • Barthelemy M, Flammini A (2006) Optimal traffic networks. Journal of Statistical Mechanics: Theory and Experiment 2006(07):L07002

    Google Scholar 

  • Barthelemy M, Flammini A (2008) Modeling urban street patterns. Phys Rev Lett 100(13):138702

    Google Scholar 

  • Barthelemy M, Flammini A (2009) Co-evolution of density and topology in a simple model of city formation. Netw Spat Econ 9(3):401–425

    Google Scholar 

  • Batty, M. (2007). Cities and complexity: understanding cities with cellular automata, agent-based models, and fractals: The MIT press, Cambridge

  • Batty M (2012) Building a science of cities. Cities 29:S9–S16. https://doi.org/10.1016/j.cities.2011.11.008

    Article  Google Scholar 

  • Batty M (2013) The new science of cities: MIT Press, Cambridge

  • Berge C (1962) The theory of graphs and its applications. Bulletin of Mathematical Biophysics 24(4):441–443

    Google Scholar 

  • Boccaletti S, Bianconi G, Criado R, del Genio CI, Gómez-Gardeñes J, Romance M et al (2014) The structure and dynamics of multilayer networks. Phys Rep 544(1):1–122. https://doi.org/10.1016/j.physrep.2014.07.001

    Article  Google Scholar 

  • Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D (2006) Complex networks: Structure and dynamics. Phys Rep 424(4-5):175–308. https://doi.org/10.1016/j.physrep.2005.10.009

    Article  Google Scholar 

  • Boeing G (2017) A multi-scale analysis of 27,000 urban street networks

  • Bracey HE (1956) A rural component of centrality applied to six southern counties in the United Kingdom. Econ Geogr 32(1):38–50

    Google Scholar 

  • Buhl J, Gautrais J, Reeves N, Solé R, Valverde S, Kuntz P, Theraulaz G (2006) Topological patterns in street networks of self-organized urban settlements. The European Physical Journal B-Condensed Matter and Complex Systems 49(4):513–522

    Google Scholar 

  • Buldyrev SV, Parshani R, Paul G, Stanley HE, Havlin S (2010) Catastrophic cascade of failures in interdependent networks. Nature 464(7291):1025–1028

    Google Scholar 

  • Cao X-B, Hong C, Du W-B, Zhang J (2013) Improving the network robustness against cascading failures by adding links. Chaos, Solitons Fractals 57:35–40

    Google Scholar 

  • Chan J (2007) Rail transit OD matrix estimation and journey time reliability metrics using automated fare data. Massachusetts Institute of Technology, Cambridge

    Google Scholar 

  • Chen A, Kim J, Lee S, Kim Y (2010) Stochastic multi-objective models for network design problem. Expert Syst Appl 37(2):1608–1619

    Google Scholar 

  • Chen J, Chang Z (2015) Rethinking urban green space accessibility: Evaluating and optimizing public transportation system through social network analysis in megacities. Landsc Urban Plan 143:150–159

    Google Scholar 

  • Chen D, Huang X, Wang D, Jia L (2014) Public transit hubs identification based on complex networks theory. IETE Technical Review 31(6):440–451

  • Chen J, Yang D (2013) Estimating Smart Card Commuters Origin-Destination Distribution Based on APTS Data. Journal of Transportation Systems Engineering & Information Technology 13(4):47–53

    Google Scholar 

  • Chorley, R. J. H. (1967). Models in geography

    Google Scholar 

  • Crucitti P, Latora V, Marchiori M (2004a) Model for cascading failures in complex networks. Phys Rev E 69(4):045104

    Google Scholar 

  • Crucitti P, Latora V, Marchiori M, Rapisarda A (2003) Efficiency of scale-free networks: error and attack tolerance. Physica A: Statistical Mechanics and its Applications 320:622–642

    Google Scholar 

  • Crucitti P, Latora V, Marchiori M, Rapisarda A (2004b) Error and attack tolerance of complex networks. Physica A: Statistical Mechanics and its Applications 340(1-3):388–394. https://doi.org/10.1016/j.physa.2004.04.031

    Article  Google Scholar 

  • Crucitti P, Latora V, Porta S (2006) Centrality in networks of urban streets. Chaos: An Interdisciplinary Journal of Nonlinear Science 16(1):015113

    Google Scholar 

  • Curtis C, Scheurer J (2009) Network city activity centres Developing an Analysis, Conception and Communication Tool for Integrated Land Use and Transport Planning in the Perth Metropolitan Area. Department of Planning and Infrastructure (DPI) and Curtin University of Technology, Perth

    Google Scholar 

  • Curtis C, Scheurer J (2010) Planning for sustainable accessibility: Developing tools to aid discussion and decision-making. Prog Plan 74(2):53–106

    Google Scholar 

  • Daganzo CF (2010) Structure of competitive transit networks. Transp Res B Methodol 44(4):434–446

    Google Scholar 

  • de Arruda HF, Comin CH, da Fontoura Costa L (2016) Minimal paths between communities induced by geographical networks. Journal of Statistical Mechanics: Theory and Experiment 2016(2):023403

    Google Scholar 

  • Derrible S (2012) Network centrality of metro systems. PLoS One 7(7):e40575

    Google Scholar 

  • Derrible S, Kennedy C (2010a) Characterizing metro networks: state, form, and structure. Transportation 37(2):275–297

    Google Scholar 

  • Derrible S, Kennedy C (2010b) Evaluating, Comparing, and Improving Metro Networks: Application to Plans for Toronto, Canada. Transportation Research Record: Journal of the Transportation Research Board 2146:43–51

    Google Scholar 

  • Derrible S, Kennedy C (2011) Applications of graph theory and network science to transit network design. Transp Rev 31(4):495–519

    Google Scholar 

  • Ding R, Ujang N, Bin Hamid H, Manan MSA, He Y, Li R, Wu J (2018) Detecting the urban traffic network structure dynamics through the growth and analysis of multi-layer networks. Physica A: Statistical Mechanics and its Applications 503:800–817

    Google Scholar 

  • Ding R, Ujang N, Bin Hamid H, Manan MSA, Li R, Wu J (2017) Heuristic urban transportation network design method, a multilayer coevolution approach. Physica A: Statistical Mechanics and its Applications 479:71–83

    Google Scholar 

  • Ding R, Ujang N, Bin Hamid H, Wu J (2015) Complex Network Theory Applied to the Growth of Kuala Lumpur’s Public Urban Rail Transit Network. PLoS One 10(10):e0139961

    Google Scholar 

  • Dolev S, Elovici Y, Puzis R (2010) Routing betweenness centrality. Journal of the ACM (JACM) 57(4):25

    Google Scholar 

  • Domenech A (2009) A topological phase transition between small-worlds and fractal scaling in urban railway transportation networks? Physica A: Statistical Mechanics and its Applications 388(21):4658–4668

    Google Scholar 

  • Donetti L (2004) Detecting network communities: a new systematic and efficient algorithm. Journal of Statistical Mechanics: Theory and Experiment 2004(10):P10012

    Google Scholar 

  • Du W-B, Zhou X-L, Chen Z, Cai K-Q, Cao X-B (2014) Traffic dynamics on coupled spatial networks. Chaos, Solitons Fractals 68:72–77

    Google Scholar 

  • Du W-B, Zhou X-L, Jusup M, Wang Z (2016) Physics of transportation: Towards optimal capacity using the multilayer network framework. Sci Rep 6:19059

    Google Scholar 

  • Ducruet C, Beauguitte L (2014) Spatial science and network science: review and outcomes of a complex relationship. Netw Spat Econ 14(3-4):297–316

    Google Scholar 

  • Ducruet C, Lugo I (2013) Cities and Transport Networks in Shipping and Logistics Research. Asian Journal of Shipping & Logistics 29(2):145–166

    Google Scholar 

  • Dwivedi A, Yu X (2013) A maximum-flow-based complex network approach for power system vulnerability analysis. IEEE Transactions on Industrial Informatics 9(1):81–88

    Google Scholar 

  • Dwivedi A, Yu X, Sokolowski P (2010) Analyzing power network vulnerability with maximum flow based centrality approach. Paper presented at the 2010 8th IEEE International Conference on Industrial Informatics

  • Eisenstat D (2011) Random Road Networks: The Quadtree Model. Paper presented at the ANALCO

  • Eladaway I (2014) Analyzing traffic layout using dynamic social network analysis. Traffic Congestion

  • Erath A, Löchl M, Axhausen KW (2009) Graph-theoretical analysis of the Swiss road and railway networks over time. Netw Spat Econ 9(3):379–400

    Google Scholar 

  • Erdos P, Renyi A (1960) On the evolution of random graphs. Publ Math Inst Hung Acad Sci 5(17-61):43

    Google Scholar 

  • Expert P, Evans TS, Blondel VD, Lambiotte R (2011) Uncovering space-independent communities in spatial networks. Proc Natl Acad Sci 108(19):7663–7668

    Google Scholar 

  • Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry:35–41. https://doi.org/10.2307/3033543

    Google Scholar 

  • Frumin M, Zhao J (2012) Analyzing passenger incidence behavior in heterogeneous transit services using smartcard data and schedule-based assignment. Transportation Research Record: Journal of the Transportation Research Board 2274:52–60

    Google Scholar 

  • Gallotti R, Bazzani A, Rambaldi S, Barthelemy M (2015) How transportation hierarchy shapes human mobility. arXiv preprint arXiv:1509.03752

  • Gao S, Wang Y, Gao Y, Liu Y (2013) Understanding urban traffic-flow characteristics: a rethinking of betweenness centrality. Environment and Planning B: Planning and design 40(1):135–153

    Google Scholar 

  • Gao Z, Wu J, Sun H (2005) Solution algorithm for the bi-level discrete network design problem. Transp Res B Methodol 39(6):479–495. https://doi.org/10.1016/j.trb.2004.06.004

    Article  Google Scholar 

  • Gao Z, Zhao X, Huang H-J, Mao B (2006) Research on problems related to complex networks and urban traffic systems. Journal of Transportation Systems Engineering and Information Technology 6(3):41–47

    Google Scholar 

  • Garrison WL (1960) Connectivity of the interstate highway system. Pap Reg Sci 6(1):121–137

    Google Scholar 

  • Garrison WL, Marble DF (1961) The structure of transportation networks. Transportation Center at Northwestern University, Newport News

    Google Scholar 

  • Garrison WL, Marble DF (1964) Factor-analytic study of the connkctivity of a transportation network*. Pap Reg Sci 12(1):231–238. https://doi.org/10.1111/j.1435-5597.1964.tb01269.x

    Article  Google Scholar 

  • Gastner MT, Newman ME (2006) The spatial structure of networks. The European Physical Journal B-Condensed Matter and Complex Systems 49(2):247–252

    Google Scholar 

  • Gattuso D, Miriello E (2005) Compared analysis of metro networks supported by graph theory. Netw Spat Econ 5(4):395–414

    Google Scholar 

  • Gleyze J-F (2013) Topological clustering for geographical networks Methods for Multilevel Analysis and Visualisation of Geographical Networks (pp. 33-53), Springer

  • Gong H, He K, Qu Y, Wang P (2016) Analysis and improvement of vehicle information sharing networks. Physica A: Statistical Mechanics and its Applications 452:106–112

    Google Scholar 

  • Gu C-G, Zou S-R, Xu X-L, Qu Y-Q, Jiang Y-M, Liu H-K, Zhou T (2011) Onset of cooperation between layered networks. Phys Rev E 84(2):026101

    Google Scholar 

  • Gutierrez-Jarpa G, Laporte G, Marianov V, Moccia L (2017) Multi-objective rapid transit network design with modal competition: The case of Concepción, Chile. Comput Oper Res 78:27–43

    Google Scholar 

  • Gutierrez-Jarpa G, Obreque C, Laporte G, Marianov V (2013) Rapid transit network design for optimal cost and origin–destination demand capture. Comput Oper Res 40(12):3000–3009

    Google Scholar 

  • Haggett P, Chorley RJ (1969) Network analysis in geography. Edward Arnold, London

    Google Scholar 

  • Haggett P, Cliff AD, Frey A (1977) Locational analysis in human geography. Tijdschr Econ Soc Geogr 68(6)

  • Hillier B (2007) Space is the machine: a configurational theory of architecture

  • Hillier B, Iida S (2005) Network and psychological effects in urban movement. Paper presented at the International Conference on Spatial Information Theory

  • Hillier B, Leaman A, Stansall P, Bedford M (1976) Space syntax. Environment and Planning B: Planning and design 3(2):147–185

    Google Scholar 

  • Holme P (2003) Congestion and centrality in traffic flow on complex networks. Advances in Complex Systems 6(02):163–176

    Google Scholar 

  • Holme P, Kim BJ, Yoon CN, Han SK (2002) Attack vulnerability of complex networks. Phys Rev E 65(5):056109

    Google Scholar 

  • Hu K, Liu C, Hu T, Tang Y (2010) Enhancing traffic capacity for scale-free networks by the one-way links. J Phys A Math Theor 43(17):175101

    Google Scholar 

  • Hu M-B, Jiang R, Wu Y-H, Wang W-X, Wu Q-S (2008) Urban traffic from the perspective of dual graph. The European Physical Journal B 63(1):127–133

    Google Scholar 

  • Huang W, Chow TW (2010) Effective strategy of adding nodes and links for maximizing the traffic capacity of scale-free network. Chaos: an interdisciplinary journal of nonlinear science 20(3):033123

    Google Scholar 

  • Iacono M, Levinson D, El-Geneidy A (2008) Models of transportation and land use change: a guide to the territory. J Plan Lit 22(4):323–340

    Google Scholar 

  • Jiang B (2007) A topological pattern of urban street networks: universality and peculiarity. Physica A: Statistical Mechanics and its Applications 384(2):647–655

    Google Scholar 

  • Jiang B, Claramunt C (2004a) A structural approach to the model generalization of an urban street network. GeoInformatica 8(2):157–171

    Google Scholar 

  • Jiang B, Claramunt C (2004b) Topological analysis of urban street networks. Environment and Planning B: Planning and design 31(1):151–162

    Google Scholar 

  • Jiang Z-Y (2014) An incremental optimal routing strategy for scale-free networks. International Journal of Modern Physics C 25(09):1450044

    Google Scholar 

  • Jiang Z-Y, Liang M-G, Zhang S, Zhou W, Jin H (2013) Enhancing Traffic Capacity of Two-Layer Complex Networks. International Journal of Modern Physics C 24(08):1350051

    Google Scholar 

  • Jozefowiez N, Semet F, Talbi E-G (2008) Multi-objective vehicle routing problems. Eur J Oper Res 189(2):293–309

    Google Scholar 

  • Kansky KJ (1963) Structure of transportation networks: relationships between network geometry and regional characteristics. Ph.D. Thesis, University of Chicago

  • Kermanshah A, Derrible S, Berkelhammer M (2017) Using climate models to estimate urban vulnerability to flash floods. Journal of Applied Meteorology and Climatology (2017)

  • Kleinberg J (2000) The small-world phenomenon: An algorithmic perspective. Paper presented at the Proceedings of the thirty-second annual ACM symposium on Theory of computing

  • Kurant M, Thiran P (2006) Layered complex networks. Phys Rev Lett 96(13):138701

    Google Scholar 

  • Lammer S, Gehlsen B, Helbing D (2006) Scaling laws in the spatial structure of urban road networks. Physica A: Statistical Mechanics and its Applications 363(1):89–95

    Google Scholar 

  • Latora V, Marchiori M (2002) Is the Boston subway a small-world network? Physica A: Statistical Mechanics and its Applications 314(1):109–113

    Google Scholar 

  • Latora V, Marchiori M (2003) Economic small-world behavior in weighted networks. The European Physical Journal B-Condensed Matter and Complex Systems 32(2):249–263

    Google Scholar 

  • Levinson D (2007) Density and dispersion: the co-development of land use and rail in London. Journal of Economic Geography, lbm038

  • Levinson D, Xie F, Zhu S (2007) The co-evolution of land use and road networks. Transportation and Traffic Theory:839–859

  • Levinson D, Yerra B (2005) How land use shapes the evolution of road networks. Available at SSRN 1736160

  • Levinson D, Yerra B (2006) Self-organization of surface transportation networks. Transp Sci 40(2):179–188

    Google Scholar 

  • Li G, Reis S, Moreira A, Havlin S, Stanley H, Andrade J Jr (2010) Towards design principles for optimal transport networks. Phys Rev Lett 104(1):018701

    Google Scholar 

  • Li T, Wu J, Sun H, Gao Z (2015) Integrated co-evolution model of land use and traffic network design. Networks and Spatial Economics, 1-25

  • Lin G, Chen X, Liang Y (2018) The location of retail stores and street centrality in Guangzhou, China. Appl Geogr 100:12–20

    Google Scholar 

  • Liu C (2001) Advanced traffic planning. People Traffic Publication, Beijing

    Google Scholar 

  • Liu C (2003) Study on traffic network design model and algorithm. Journal of Highway and Transportation Research and Development 20(2):57–62

    Google Scholar 

  • Liu Y-Y, Slotine J-J, Barabási A-L (2011) Controllability of complex networks. Nature 473(7346):167–173

    Google Scholar 

  • Liu Y, Sui Z, Kang C, Gao Y (2014) Uncovering patterns of inter-urban trip and spatial interaction from social media check-in data. PLoS One 9(1):e86026

    Google Scholar 

  • Liu Y, Wang H, Jiao L, Liu Y, He J, Ai T (2015) Road centrality and landscape spatial patterns in Wuhan Metropolitan Area, China. Chin Geogr Sci 25(4):511–522

    Google Scholar 

  • Liu Z, Hu M-B, Jiang R, Wang W-X, Wu Q-S (2007) Method to enhance traffic capacity for scale-free networks. Phys Rev E 76(3):037101

    Google Scholar 

  • Ma J, Han W, Guo Q, Wang Z (2016a) Traffic dynamics on two-layer complex networks with limited delivering capacity. Physica A: Statistical Mechanics and its Applications 456:281–287

    Google Scholar 

  • Ma J, Han W, Guo Q, Zhang S (2016b) Enhancing traffic capacity of scale-free networks by link-directed strategy. International Journal of Modern Physics C 27(03):1650028

    Google Scholar 

  • Ma J, Han W, Guo Q, Zhang S, Wang J, Wang Z (2015) Improved efficient routing strategy on two-layer complex networks. International Journal of Modern Physics C 27(4):1650044

    Google Scholar 

  • Magnanti TL, Wong RT (1984) Network design and transportation planning: Models and algorithms. Transp Sci 18(1):1–55

    Google Scholar 

  • Manley E, Dennett A, Batty M (2015) Using mobile phone traces to understand activity and mobility in Dakar, Senegal

  • Marchiori M, Latora V (2000) Harmony in the small-world. Physica A: Statistical Mechanics and its Applications 285(3):539–546

    Google Scholar 

  • Masucci AP, Smith D, Crooks A, Batty M (2009) Random planar graphs and the London street network. The European Physical Journal B 71(2):259–271

    Google Scholar 

  • Masucci AP, Stanilov K, Batty M (2014) Exploring the evolution of London's street network in the information space: A dual approach. Phys Rev E 89(1):012805

    Google Scholar 

  • Masud A, Ravindran A, Ravindran A (2008) Operations research and management science handbook: CRC Press, chapter Multi Criteria Decision Making

  • Mattsson L-G, Jenelius E (2015) Vulnerability and resilience of transport systems–A discussion of recent research. Transp Res A Policy Pract 81:16–34

    Google Scholar 

  • Meignan D, Simonin O, Koukam A (2007) Simulation and evaluation of urban bus-networks using a multiagent approach. Simul Model Pract Theory 15(6):659–671

    Google Scholar 

  • Min J, Park J, Oh S, Sohn M (2013) Finding a real passenger path in a complex transit network using a smart card record. Paper presented at the International Conference on Railway Technology: Research, Development and Maintenance

  • Morris RG, Barthelemy M (2012) Transport on coupled spatial networks. Phys Rev Lett 109(12):128703

    Google Scholar 

  • Motter AE, Lai Y-C (2002) Cascade-based attacks on complex networks. Phys Rev E 66(6):065102

    Google Scholar 

  • Motter AE, Toroczkai Z (2007) Introduction: Optimization in networks. Chaos: An Interdisciplinary Journal of Nonlinear Science 17(2):026101

    Google Scholar 

  • Neal ZP (2012) The connected city: How networks are shaping the modern metropolis. Routledge, London

    Google Scholar 

  • Newman ME (2002) Assortative mixing in networks. Phys Rev Lett 89(20):208701

    Google Scholar 

  • Newman ME (2008) The mathematics of networks. The New Palgrave Encyclopedia of Economics 2(2008):1–12

    Google Scholar 

  • Newman ME (2012) Communities, modules and large-scale structure in networks. Nat Phys 8(1):25–31

    Google Scholar 

  • Newman ME, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):026113

    Google Scholar 

  • Oliveira CL, Morais PA, Moreira AA, Andrade JS Jr (2014) Enhanced Flow in Small-World Networks. Phys Rev Lett 112(14):148701

    Google Scholar 

  • Ore O (1963) Hamilton connected graphs. J Math Pures Appl 42(9):21–27

    Google Scholar 

  • Othman NB, Legara EF, Selvam V, Monterola C (2014) Simulating Congestion Dynamics of Train Rapid Transit Using Smart Card Data. Procedia Computer Science 29:1610–1620

    Google Scholar 

  • Porta S, Crucitti P, Latora V (2006a) The network analysis of urban streets: a dual approach. Physica A: Statistical Mechanics and its Applications 369(2):853–866

    Google Scholar 

  • Porta S, Crucitti P, Latora V (2006b) The network analysis of urban streets: a primal approach. Environment and Planning B: Planning and design 33(5):705–725

    Google Scholar 

  • Porta S, Crucitti P, Latora V (2008) Multiple centrality assessment in Parma: a network analysis of paths and open spaces. urban design. International 13(1):41–50

    Google Scholar 

  • Porta S, Latora V (2007) 11 Multiple centrality assessment: mapping centrality in networks of urban spaces. Urban Sustainability Through Environmental Design: Approaches to Time-People-Place Responsive Urban Spaces, 101

  • Porta S, Latora V, Wang F, Rueda S, Strano E, Scellato S et al (2012) Street centrality and the location of economic activities in Barcelona. Urban Stud 49(7):1471–1488

    Google Scholar 

  • Porta S, Strano E, Iacoviello V, Messora R, Latora V, Cardillo A et al (2009) Street centrality and densities of retail and services in Bologna, Italy. Environment and Planning B: Planning and Design 36(3):450–465

    Google Scholar 

  • Porter MA, Onnela J-P, Mucha PJ (2009) Communities in networks. Notices of the AMS 56(9):1082–1097

    Google Scholar 

  • Quintero-Cano L (2011) Graph theory based transit indicators applied to ridership and safety models. University of British Columbia, Vancouver

    Google Scholar 

  • Quintero L, Sayed T, Wahba MM (2013) Safety models incorporating graph theory based transit indicators. Accid Anal Prev 50:635–644. https://doi.org/10.1016/j.aap.2012.06.012

    Article  Google Scholar 

  • Rodrigue J-P, Comtois C, Slack B (2013) The geography of transport systems. Routledge, London

    Google Scholar 

  • Rodriguez-Nunez E, Garcia-Palomares JC (2014) Measuring the vulnerability of public transport networks. J Transp Geogr 35:50–63

    Google Scholar 

  • Rui Y (2013) Urban growth modeling based on land-use changes and road network expansion. (Ph.D. thesis), KTH Royal Institute of Technology, Stockholm

  • Rui Y, Ban Y (2011) Urban growth modeling with road network expansion and land use development Advances in Cartography and GIScience. Volume 2 (pp. 399-412), Springer

  • Scellato S, Cardillo A, Latora V, Porta S (2006) The backbone of a city. The European Physical Journal B-Condensed Matter and Complex Systems 50(1-2):221–225

    Google Scholar 

  • Scheurer J, Curtis C, Porta S (2008) Spatial network analysis of multimodal transport systems: developing a strategic planning tool to assess the congruence of movement and urban structure: a case study of Perth before and after the Perth-to-Mandurah Railway: GAMUT, Australasian Centre for the Governance and Management of Urban Transport, University of Melbourne

  • Schweitzer F, Ebeling W, Rose H, Weiss O (1997) Optimization of road networks using evolutionary strategies. Evol Comput 5(4):419–438

    Google Scholar 

  • Sen P, Dasgupta S, Chatterjee A, Sreeram P, Mukherjee G, Manna S (2003) Small-world properties of the Indian railway network. Phys Rev E 67(3):036106

    Google Scholar 

  • Sevtsuk A, Mekonnen M (2012) Urban network analysis. Revue internationale de géomatique–n 287:305

    Google Scholar 

  • Sheffi Y (1985) Urban transportation networks. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Singha MR, Kalita B (2013) Mapping Mobile Phone Network onto Urban Traffic Network. Lecture Notes in Engineering & Computer Science 2202(1):245–250

    Google Scholar 

  • Smailes AE (1946) The urban mesh of England and Wales. Trans Pap (Institute of British Geographers) 11:87–101

    Google Scholar 

  • Soh H, Lim S, Zhang T, Fu X, Lee GKK, Hung TGG et al (2010) Weighted complex network analysis of travel routes on the Singapore public transportation system. Physica A Statistical Mechanics & Its Applications 389(24):5852–5863

    Google Scholar 

  • Solé-Ribalta A, Gómez S, Arenas A (2016a) Congestion induced by the structure of multiplex networks. Phys Rev Lett 116(10):108701

    Google Scholar 

  • Solé-Ribalta A, Gómez S, Arenas A (2016b) Decongestion of urban areas with hotspot-pricing. arXiv preprint arXiv:1604.07729

  • Solé-Ribalta A, Gómez S, Arenas A (2016c) A model to identify urban traffic congestion hotspots in complex networks. arXiv preprint arXiv:1604.07728

  • Strano E, Shai S, Dobson S, Barthelemy M (2015) Multiplex networks in metropolitan areas: generic features and local effects. J R Soc Interface 12(111):20150651. https://doi.org/10.1098/rsif.2015.0651

    Article  Google Scholar 

  • Sun DJ, Zhao Y, Lu Q-C (2015a) Vulnerability analysis of urban rail transit networks: a case study of Shanghai, China. Sustainability 7(6):6919–6936

    Google Scholar 

  • Sun H, Gao Z, Wu J (2008a) A bi-level programming model and solution algorithm for the location of logistics distribution centers. Appl Math Model 32(4):610–616. https://doi.org/10.1016/j.apm.2007.02.007

    Article  Google Scholar 

  • Sun H, Wu J (2005) Urban traffic congestion spreading in small world networks. International Journal of Modern Physics B 19(28):4239–4246

    Google Scholar 

  • Sun HJ, Zhao H, Wu JJ (2008b) A robust matching model of capacity to defense cascading failure on complex networks. Physica A: Statistical Mechanics and its Applications 387(25):6431–6435. https://doi.org/10.1016/j.physa.2008.07.028

    Article  Google Scholar 

  • Sun L, Jin JG (2015) Modeling Temporal Flow Assignment in Metro Networks Using Smart Card Data. Paper presented at the IEEE International Conference on Intelligent Transportation Systems

  • Sun, L., Lu, Y., & Lee, D.-H. (2015b). Understanding the Structure of Urban Bus Networks: The C-Space Representation Approach. Paper presented at the 15th COTA International Conference of Transportation Professionals

  • Sun Y, Xu R (2012) Rail transit travel time reliability and estimation of passenger route choice behavior: Analysis using automatic fare collection data. Transportation Research Record: Journal of the Transportation Research Board 2275:58–67

    Google Scholar 

  • Tang J, Wang Y, Wang H, Zhang S, Liu F (2014) Dynamic analysis of traffic time series at different temporal scales: A complex networks approach. Physica A: Statistical Mechanics and its Applications 405:303–315. https://doi.org/10.1016/j.physa.2014.03.038

    Article  Google Scholar 

  • Tao L, Ceder AA (2015) Predictive Public-Transport Vehicle Control for Synchronized Transfers in Schedule-based Networks

  • Taylor MA (2008) Critical Transport Infrastructure in Urban Areas: Impacts of Traffic Incidents Assessed Using Accessibility-Based Network Vulnerability Analysis. Growth Chang 39(4):593–616

    Google Scholar 

  • Taylor MA, Sekhar SV, D'Este GM (2006) Application of accessibility based methods for vulnerability analysis of strategic road networks. Netw Spat Econ 6(3-4):267–291

    Google Scholar 

  • Ulungu EL, Teghem J (1994) Multi-objective combinatorial optimization problems: A survey. J Multi-Criteria Decis Anal 3(2):83–104

    Google Scholar 

  • Vragović I, Louis E, Diaz-Guilera A (2005) Efficiency of informational transfer in regular and complex networks. Phys Rev E 71(3):036122

    Google Scholar 

  • Wang F, Antipova A, Porta S (2011) Street centrality and land use intensity in Baton Rouge, Louisiana. J Transp Geogr 19(2):285–293

    Google Scholar 

  • Wang P, Hunter T, Bayen AM, Schechtner K, González MC (2012) Understanding road usage patterns in urban areas. Sci Rep 2:1001

    Google Scholar 

  • Wang S, Yu D, Lin C, Shang Q, Lin Y (2018) How to connect with each other between roads? An empirical study of urban road connection properties. Physica A: Statistical Mechanics and its Applications 512:775–787

    Google Scholar 

  • Wang S, Zheng L, Yu D (2017) The improved degree of urban road traffic network: A case study of Xiamen, China. Physica A: Statistical Mechanics and its Applications 469:256–264

    Google Scholar 

  • Watts DJ (2002) A simple model of global cascades on random networks. Proc Natl Acad Sci 99(9):5766–5771

    Google Scholar 

  • Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):440–442. https://doi.org/10.1038/30918

    Article  Google Scholar 

  • Widhalm P, Yang Y, Ulm M, Athavale S, González MC (2015) Discovering urban activity patterns in cell phone data. Transportation 42(4):597–623

    Google Scholar 

  • Wu J-J, Gao Z-Y, Sun H-J (2006a) Cascade and breakdown in scale-free networks with community structure. Phys Rev E 74(6):066111. https://doi.org/10.1103/PhysRevE.74.066111

    Article  Google Scholar 

  • Wu J, Gao Z, Sun H (2004a) Simulation of traffic congestion with SIR model. Modern Physics Letters B 18(30):1537–1542

    Google Scholar 

  • Wu J, Gao Z, Sun H (2007a) Effects of the cascading failures on scale-free traffic networks. Physica A: Statistical Mechanics and its Applications 378(2):505–511. https://doi.org/10.1016/j.physa.2006.12.003

    Article  Google Scholar 

  • Wu J, Gao Z, Sun H (2008a) Optimal traffic networks topology: A complex networks perspective. Physica A: Statistical Mechanics and its Applications 387(4):1025–1032. https://doi.org/10.1016/j.physa.2007.10.014

    Article  Google Scholar 

  • Wu J, Gao Z, Sun H (2008b) Statistical Properties of Individual Choice Behaviors on Urban Traffic Networks. Journal of Transportation Systems Engineering and Information Technology 8(2):69–74. https://doi.org/10.1016/s1570-6672(08)60019-7

    Article  Google Scholar 

  • Wu J, Gao Z, Sun H, Huang H (2004b) Urban transit system as a scale-free network. Modern Physics Letters B 18(19n20):1043–1049

    Google Scholar 

  • Wu J, Gao Z, Sun H, Huang H (2006b) Congestion in different topologies of traffic networks. EPL (Europhysics Letters) 74(3):560

    Google Scholar 

  • Wu J, Li R, Ding R, Li T, Sun H (2016) City expansion model based on population diffusion and road growth. Applied Mathematical Modelling

  • Wu J, Liu M, Sun H, Li T, Gao Z, Wang DZ (2015) Equity-based timetable synchronization optimization in urban subway network. Transportation Research Part C: Emerging Technologies 51:1–18

    Google Scholar 

  • Wu J, Sun H, Gao Z (2007b) Cascading failures on weighted urban traffic equilibrium networks. Physica A: Statistical Mechanics and its Applications 386(1):407–413. https://doi.org/10.1016/j.physa.2007.08.034

    Article  Google Scholar 

  • Wu J, Xu M, Gao Z (2013) Coevolution dynamics model of road surface and urban traffic structure. Nonlinear Dynamics 73(3):1327–1334

    Google Scholar 

  • Wu J, Xu M, Gao Z (2014) Modeling The Coevolution Of Road Expansion And Urban Traffic Growth. Advances in Complex Systems 17(01):1450005

    Google Scholar 

  • Xie F, Levinson D (2007) Measuring the structure of road networks. Geogr Anal 39(3):336–356

    Google Scholar 

  • Xie F, Levinson D (2009a) Modeling the growth of transportation networks: a comprehensive review. Netw Spat Econ 9(3):291–307

    Google Scholar 

  • Xie F, Levinson D (2009b) Topological evolution of surface transportation networks. Comput Environ Urban Syst 33(3):211–223. https://doi.org/10.1016/j.compenvurbsys.2008.09.009

    Article  Google Scholar 

  • Xing Y, Lu J, Chen S (2016) Weighted complex network analysis of shanghai rail transit system. Discrete Dynamics in Nature and Society, 2016

  • Xu X, Hu J, Liu F, Liu L (2007) Scaling and correlations in three bus-transport networks of China. Physica A: Statistical Mechanics and its Applications 374(1):441–448

    Google Scholar 

  • Yang X-H, Wang B, Chen S-Y, Wang W-L (2012) Epidemic dynamics behavior in some bus transport networks. Physica A: Statistical Mechanics and its Applications 391(3):917–924

    Google Scholar 

  • Yang Y, Liu Y, Zhou M, Li F, Sun C (2015) Robustness assessment of urban rail transit based on complex network theory: A case study of the Beijing Subway. Saf Sci 79:149–162

    Google Scholar 

  • Yang Y, Tian L, Yeh AGO, Li QQ (2014) Zooming into individuals to understand the collective: A review of trajectory-based travel behaviour studies. Travel Behav Soc 1(2):69–78

    Google Scholar 

  • Yerra BM, Levinson DM (2005) The emergence of hierarchy in transportation networks. Ann Reg Sci 39(3):541–553

    Google Scholar 

  • Yin H-Y, Xu L-Q (2010) Measuring the structural vulnerability of road network: A network efficiency perspective. Journal of Shanghai Jiaotong University (Science) 15:736–742

    Google Scholar 

  • Zeydan E, Bastug E, Bennis M, Kader MA, Karatepe IA, Er AS, Debbah M (2016) Big data caching for networking: moving from cloud to edge. IEEE Commun Mag 54(9):36–42

    Google Scholar 

  • Zhang G-Q, Wang D, Li G-J (2007) Enhancing the transmission efficiency by edge deletion in scale-free networks. Phys Rev E 76(1):017101

    Google Scholar 

  • Zhang J, Zhao M, Liu H, Xu X (2013) Networked characteristics of the urban rail transit networks. Physica A: Statistical Mechanics and its Applications 392(6):1538–1546. https://doi.org/10.1016/j.physa.2012.11.036

    Google Scholar 

  • Zhang H, Jiang Z-Y, He X, Zhang S (2015) Exploring highly-efficient routing strategy on scale-free networks with limited and diverse node capacity. Modern Physics Letters B 29(17):1550085

    Google Scholar 

  • Zhang J, Wang S, Wang X (2018) Comparison analysis on vulnerability of metro networks based on complex network. Physica A: Statistical Mechanics and its Applications 496:72–78

    Google Scholar 

  • Zhang S, Liang M-G, Jiang Z-Y, Wu J-J (2014a) Effective strategy of adding links for improving network transport efficiency on complex networks. International Journal of Modern Physics C 25(06):1450014

    Google Scholar 

  • Zhang S, Liang M-G, Li H-J (2014b) Method to enhance traffic capacity for two-layer complex networks. Can J Phys 92(12):1599–1605

    Google Scholar 

  • Zhao F, Sun H, Wu J, Gao Z (2014) Urban Road Network Evolution to Maximize the Capacity. Procedia Soc Behav Sci 138:251–258. https://doi.org/10.1016/j.sbspro.2014.07.202

    Article  Google Scholar 

  • Zhao F, Sun H, Wu J, Gao Z, Liu R (2016a) Analysis of road network pattern considering population distribution and central business district. PLoS One 11(3):e0151676

    Google Scholar 

  • Zhao F, Wu J, Sun H, Gao Z, Liu R (2015) Population-driven Urban Road Evolution Dynamic Model. Netw Spat Econ:1–22

  • Zhao J, Zhang F, Tu L, Xu C, Shen D, Tian C et al (2016b) Estimation of Passenger Route Choice Pattern Using Smart Card Data for Complex Metro Systems. IEEE Trans Intell Transp Syst 18(4):790–801

    Google Scholar 

  • Zheng J-F, Gao Z-Y, Zhao X-M (2007) Properties of transportation dynamics on scale-free networks. Physica A: Statistical Mechanics and its Applications 373:837–844

    Google Scholar 

  • Zhong C, Arisona SM, Huang X, Batty M, Schmitt G (2014) Detecting the dynamics of urban structure through spatial network analysis. Int J Geogr Inf Sci 28(11):2178–2199

    Google Scholar 

  • Zhou J, Xu W, Guo X, Ma X (2015) Railway faults spreading model based on dynamics of complex network. International Journal of Modern Physics B 29(06):1550038

    Google Scholar 

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Acknowledgements

This paper is supported by the National Natural Science Foundation of China (NSFC): 71890972/71890970, 71525002, 71621001, Beijing Municipal Natural Science Foundation (No. L181008), and Putra Group Initiative Grant (GP-IPB) UPM: 9413000.

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Table 3 The complex network theory related applications in urban traffic network research

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Ding, R., Ujang, N., Hamid, H.B. et al. Application of Complex Networks Theory in Urban Traffic Network Researches. Netw Spat Econ 19, 1281–1317 (2019). https://doi.org/10.1007/s11067-019-09466-5

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