[Representation of Cycling Behaviour in Microscopic Traffic Simulation Models]

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Literature Review

Introduction

Simulation is a process based on building a computer model that suitably represents a real or proposed system which enables to extract valid inferences on the behavior of the modeled system, from the outcomes of the computer experiments conducted on its model(Baruya, 2009: 136). Simulation has become in recent years one of the most used and powerful tools for systems analysis and design, by its proven ability to answer “what if” questions helping the system designer to find solutions for building new systems, or assess the impact of proposed changes on an already existing system(Kosonen, 2011: 363-387). A simulation model is always a simplified representation of a system that addresses specifically those aspects of the studied system relevant for the purposes of the analysis from the point of view of the system analyst(Michaelis , 2008: 208-209). A simulation model is therefore specific, both for the problem and for whoever tries to use the model for finding solutions to the problem. A simulation study has usually the objective of helping to get a better understanding on how a system behaves, evaluating the impact of changes in the system, or in values of the parameters governing the system, or of decisions on the policies controlling the system(Rumar, 2010: 408-411). The described general role of Simulation as systems analysis tool is also true when Simulation is applied to the study of traffic and transportation systems. The development of new telematic applications to that domain, and the requirements for assessing the impact either of these new telematic applications, or of traffic management decisions, on scenarios in which physical experimentation is not possible has led Simulation to a key position as a tool for traffic system analysis(Archer, 2010: 105).

Mathematical modeling of traffic flow behavior is a prerequisite for a number of important tasks including transportation planning, traffic surveillance and monitoring, incident detection, systematic control strategy design, simulation, forecasting and, last but not least, more recently in evaluating energy consumed by transportation systems, environmental impacts due to transportation systems, and in assessing vehicle guidance systems(Matsuhashi 2009: 929-944).

Among the main modeling approaches proposed so far two of the most commonly used are: Aggregated macroscopic approaches in which traffic flows are regarded in an aggregated way as a fluid, without considering the individual particles, that is to say the vehicles, and microscopic approaches in which we try to understand the behavior of the system by modeling individually that of the vehicles composing the traffic flow(Cascetta , 2011: 697-711).

Macroscopic traffic flow models providing a dynamic insight on flow behavior are based on a hydrodynamic analogy by regarding traffic flow as a particular fluid process whose state is characterized by aggregate macroscopic variables such as traffic density (in veh/Km), traffic volume (in veh/h), and mean speed (in Km/h) (Carsten, 2011: 108).

Microscopic Traffic Simulation Models

Traffic microsimulation describes the process of creating a virtual model of a city's transportation infrastructure in order to simulate the interactions of road traffic, and other forms ...