Computational Urban Issues

Abstract

This chapter defines a Discrete-Time and Continuous-Time Markov Chain Process oriented to the flow of people from one point to another in a region or city, from their transit in different neighbourhoods. This is a current problem that affects more and more countries due to the growth of communication routes and means of transport, and that has been modeled under different mathematical approaches. On the other hand, it is a multifactorial problem. In discrete type modeling we have registered in the matrix of conditional probabilities the conditional probabilities to go from a region i to another region j. In the case of continuous type modeling we have considered the rate of pedestrian mobility between regions

Keywords: Neighbourhoods, Conditional Probabilities, Continuous-Time Markov Chain Process, Discrete-Time Markov Chain Process, Frequent Mobility Routes in the City, Initial State Vector, Steady-State Vector, Transition Matrix, Routes