Cellular Automata Models of Road Traffic

In this paper, we give an elaborate and understandable review of traffic cellular automata (TCA) models, which are a class of computationally efficient microscopic traffic flow models. TCA models arise from the physics discipline of statistical mechanics, having the goal of reproducing the correct macroscopic behaviour based on a minimal description of microscopic interactions. After giving an overview of cellular automata (CA) models, their background and physical setup, we introduce the mathematical notations, show how to perform measurements on a TCA model's lattice of cells, as well as how to convert these quantities into real-world units and vice versa. The majority of this paper then relays an extensive account of the behavioural aspects of several TCA models encountered in literature. Already, several reviews of TCA models exist, but none of them consider all the models exclusively from the behavioural point of view. In this respect, our overview fills this void, as it focusses on the behaviour of the TCA models, by means of time-space and phase-space diagrams, and histograms showing the distributions of vehicles' speeds, space, and time gaps. In the report, we subsequently give a concise overview of TCA models that are employed in a multi-lane setting, and some of the TCA models used to describe city traffic as a two-dimensional grid of cells, or as a road network with explicitly modelled intersections. The final part of the paper illustrates some of the more common analytical approximations to single-cell TCA models.Comment: Accepted for publication in "Physics Reports". A version of this paper with high-quality images can be found at: http://phdsven.dyns.cx (go to "Papers written"

A multiagent urban traffic simulation Part I: dealing with the ordinary

We describe in this article a multiagent urban traffic simulation, as we believe individual-based modeling is necessary to encompass the complex influence the actions of an individual vehicle can have on the overall flow of vehicles. We first describe how we build a graph description of the network from purely geometric data, ESRI shapefiles. We then explain how we include traffic related data to this graph. We go on after that with the model of the vehicle agents: origin and destination, driving behavior, multiple lanes, crossroads, and interactions with the other vehicles in day-to-day, ?ordinary? traffic. We conclude with the presentation of the resulting simulation of this model on the Rouen agglomeration

Cellular Automata Intersection Model

This paper introduces a cellular automaton design of intersections and defines rules to model traffic flow through them, so that urban traffic can be simulated. The model is able to simulate an intersection of up to four streets crossing. Each street can have a variable number of lanes. Furthermore, each lane can serve multiple purposes at the same time, like allowing vehicles to keep going straight or turn left and/or right. The model also allows the simulation of intersections with or without traffic lights and slip lanes. A comparison to multiple empirical intersection traffic data shows that the model is able to realistically reproduce traffic flow through an intersection. In particular, car following times in free flow and the required time value for drivers that turn within the intersection or go straight through it are reproduced. At the same time, important empirical jam characteristics are retained

Modelling of Driver and Pedestrian Behaviour – A Historical Review

Driver and pedestrian behaviour significantly affect the safety and the flow of traffic at the microscopic and macroscopic levels. The driver behaviour models describe the driver decisions made in different traffic flow conditions. Modelling the pedestrian behaviour plays an essential role in the analysis of pedestrian flows in the areas such as public transit terminals, pedestrian zones, evacuations, etc. Driver behaviour models, integrated into simulation tools, can be divided into car-following models and lane-changing models. The simulation tools are used to replicate traffic flows and infer certain regularities. Particular model parameters must be appropriately calibrated to approximate the realistic traffic flow conditions. This paper describes the existing car-following models, lane-changing models, and pedestrian behaviour models. Further, it underlines the importance of calibrating the parameters of microsimulation models to replicate realistic traffic flow conditions and sets the guidelines for future research related to the development of new models and the improvement of the existing ones.</p

CBPRS: A City Based Parking and Routing System

Navigational systems assist drivers in finding a route between two locations that is time optimal in theory but seldom in practice due to delaying circumstances the system is unaware of, such as traffic jams. Upon arrival at the destination the service of the system ends and the driver is forced to locate a parking place without further assistance. We propose a City Based Parking Routing System (CBPRS) that monitors and reserves parking places for CBPRS participants within a city. The CBPRS guides vehicles using an ant based distributed hierarchical routing algorithm to their reserved parking place. Through means of experiments in a simulation environment we found that reductions of travel times for participants were significant in comparison to a situation where vehicles relied on static routing information generated by the well known Dijkstra’s algorithm. Furthermore, we found that the CBPRS was able to increase city wide traffic flows and decrease the number and duration of traffic jams throughout the city once the number of participants increased.information systems;computer simulation;dynamic routing