RT Conference Proceedings
T1 Making more flexible ATISMART+ model for traffic simulations using a CAS
A1 Ramírez, Manuel
A1 Gavilán, José Manuel
A1 Aguilera-Venegas, Gabriel
A1 Galán-García, José Luis
A1 Galán-García, María Ángeles
A1 Rodríguez-Cielos, Pedro
K1 Tráfico - Simulación por ordenador
AB Traffic simulations usually require the search of a path to join two differentpoints. Dijkstra’s algorithm [1] is one of the most commonly used for this task dueto its easiness and quickness. In [2, 3] we developed an accelerated time simulationof car traffic in a smart city using Dijkstra’s algorithm to compute the paths.Dijkstra’s algorithm provides a shortest path between two different points butthis is not a realistic situation for simulations.  For example, in a car traffic situa-tion, the driver may not know the shortest path to follow.  This ignorance can beproduced, among others, because one of the following two facts:  the driver maynot know the exact length of the lanes, or, even knowing the exact length, the drivermay not know how to find the shortest path. Even more, in many cases, a mixtureof both facts occurs.A more realistic simulation should therefore consider these kind of facts.  Thealgorithm used to compute the path from one point to another in a traffic simulationmight consider the possibility of not using the shortest path.In this talk, we use a new probabilistic extension of Dijkstra’s algorithm whichcovers the above two situations. For this matter, two different modifications in Di-jkstra’s algorithm have been introduced:  using non-exact length in lanes, and thechoice of a non-shortest path between two different points. Both modifications areused in a non-deterministic way by means of using probability distributions (classi-cal distributions such as Normal or Poisson distributions or even "ad hoc" ones). Aprecise, fast, natural and elegant way of working with such probability distributionsis the use of a CAS in order to deal with exact and explicit computations.As an example of use of this extension of Dijkstra’s algorithm, we will showthe ATISMART+ model. This model provides more realistic accelerated time sim-ulations of car traffics in a smart city and was first introduced in [4] and extendedin [5].  This model was developed combining JAVAfor the GUI and MAXIMAforthe mathematical core of the algorithm.The studies developed in the above mentioned works, dealt with Poisson, Ex-ponential,  Uniform and Normal distributions.   In this talk we will introduce,  asa novelty, the possibility of using other continuous probability distributions suchas:  Lognormal,  Weibul,  Gamma,  Beta,  Chi-Square,  Student’s  t,  Z,  Pareto,  Lo-gistic, Cauchy or Irwin-Hall, and other discrete distributions such as:  Bernouille,Rademacher, Binomial, Geometric, Negative Binomial or Hypergeometric.  Even1more, this new version allows to deal with any “ad-hoc” continuous, discrete ormixed user’s distributions. This fact improves the flexibility of ATISMART+ model.
YR 2015
FD 2015-07-28
LK http://hdl.handle.net/10630/10173
UL http://hdl.handle.net/10630/10173
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026