Modeling vehicular traffic networks. Part I

被引:3
|
作者
Otero, Dino [1 ]
Galetti, DiOgenes [2 ]
Mizrahi, Salomon S. [3 ]
机构
[1] Univ Tecn Nacl, Fac Reg Gen Pacheco, RA-1617 Buenos Aires, DF, Argentina
[2] Univ Estadual Paulista UNESP, Inst Fis Teor, BR-01140070 Sao Paulo, SP, Brazil
[3] Univ Fed Sao Carlos UFSCar, CCET, Dept Fis, BR-13565905 Sao Carlos, SP, Brazil
关键词
Vehicular traffic; Network; Digraph theory; Stochastic matrix; Markov chain; Perron-Frobenius theory; Linear and nonlinear models; CAR-FOLLOWING MODEL; DYNAMICAL MODEL; FLOW; CONGESTION; EQUILIBRIA; OPTIMA;
D O I
10.1016/j.physa.2018.06.016
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We propose three models for the traffic of vehicles within a network formed by sites (cities, car-rental agencies, parking lots, etc.) and connected by two-way arteries (roads, highways), that allow forecasting the vehicular flux in a sequence of n consecutive steps, or units of time. An essential approach consists in using, as an a priori information, previous observations and measurements. The formal tools used in our analysis consists in: (1) associating a digraph to the network where the edges correspond to arteries and the vertices with loops represent the sites. (2) From a distribution of vehicles within the network, we construct a matrix from which we derive a stochastic matrix (SM). This matrix becomes the generator of the evolution of the traffic flow. And (3), we use the Perron-Frobenius theory for a formal analysis. We investigate three models: (a) a closed network with conserved number of vehicles; (b) to this network we add an influx and an outflux of vehicles to picture an open system. And (c), we construct a nonlinear model whose formal structure exhibits the existence of several (L) stationary states for the distribution of vehicles at each site, that alternate cyclically with time. Each state represents the traffic for L different moments. These models are hybridized and compared numerically to the effective vehicular traffic in a sector of the city of Tigre, localized in the province of Buenos Aires, Argentina. The empirical data and the traffic modelization are presented in a following paper, referred as Part II. (C) 2018 Published by Elsevier B.V.
引用
收藏
页码:97 / 110
页数:14
相关论文
共 50 条
  • [41] Traffic Aware Routing in Urban Vehicular Networks
    Cao, Ting
    Zhang, Xinchao
    Kong, Linghe
    Liu, Xiao-Yang
    Shu, Wei
    Wu, Min-You
    2013 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2013, : 2004 - 2009
  • [42] Vertex flow models for vehicular traffic on networks
    D'Apice, Ciro
    Piccoli, Benedetto
    MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES, 2008, 18 : 1299 - 1315
  • [43] Modeling Injury Severity of Vehicular Traffic Crashes
    Mujalli, Randa Oqab
    Lopez, Griselda
    Garach, Laura
    2017 INTERNATIONAL CONFERENCE ON AUTOMATION, CONTROL AND ROBOTS (ICACR 2017), 2015, : 51 - 55
  • [44] A swarm algorithm for collaborative traffic in vehicular networks
    Toutouh, Jamal
    Alba, Enrique
    VEHICULAR COMMUNICATIONS, 2018, 12 : 127 - 137
  • [45] On Microscopic, Macroscopic, and Kinetic Modeling of Vehicular Traffic
    Nugrahani, Endar
    MATEMATIKA, 2013, 29 (01) : 25 - 31
  • [46] Spatial Random Modeling of Vehicular Traffic in VANETs
    Liu, Yongyang
    Guo, Jingqiu
    Wang, Yibing
    2017 IEEE 20TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2017,
  • [47] ADMINISTRATION OF TRAFFIC FORECASTING FOR SPARSE RURAL TELEPHONE NETWORKS.
    Farr, J.P.
    Waldron, E.H.J.
    ATR, Australian Telecommunication Research, 1984, 18 (01): : 59 - 65
  • [48] LINEAR PROGRAMMING SUPPLY MODELS FOR MULTIHOUR TRAFFIC NETWORKS.
    Gribik, P.R.
    Kortanek, K.O.
    Lee, D.N.
    Polak, G.G.
    Modeling and Simulation, Proceedings of the Annual Pittsburgh Conference, 1979,
  • [49] A dynamic model of oligopoly with R&D externalities along networks. Part I.
    Bischi, Gian Italo
    Lamantia, Fabio
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2012, 84 : 51 - 65
  • [50] State-dependent stochastic networks. Part I: Approximations and applications with continuous diffusion limits
    Mandelbaum, A
    Pats, G
    ANNALS OF APPLIED PROBABILITY, 1998, 8 (02): : 569 - 646