Abstract

This paper presents the Simulator of Intelligent Transportation Systems (SITS). The SITS is based on a microscopic simulation approach to reproduce real traffic conditions in an urban or non-urban network and considers different type of vehicles, drivers and roads. A dynamical analysis of several traffic phenomena is then addressed. The results of using classical system theory tools point out that it is possible to study traffic systems, taking advantage on the knowledge gathered with automatic control algorithms. In this line of thought, it was also presented a new modelling formalism based on the embedding of statistics and Fourier transform. info:eu-repo/semantics/publishedVersion

Abstract

Due to recent advanced communication possibilities between traffic infrastructure, vehicles and drivers, the optimization of traffic lights control can be approached in novel ways. At the same time, this may introduce new unexpected dynamics in transportation systems. The authors' research aims to determine how drivers and traffic lights systems interact and influence each other when they are informed one about another's behaviour. In order to study this, the authors developed an agent based model to simulate transportation systems with static and dynamic traffic lights and drivers using information about the traffic lights behaviour. Experiments reveal that the system's performance improves when a bigger share of drivers receive information for both static and dynamic traffic lights systems. This performance improvement is due to drivers managing to avoid stopping at red light rather them adapting their speed to different distances to the traffic lights systems. Additionally, it is demonstrated that the duration of the fixed phases also influences the performance when drivers use speed recommendations. Moreover, the results show that dynamic traffic lights can produce positive effects for roads with high speed limits and high traffic intensity, while in the rest of the cases static control is better. The findings can be used for building more efficient traffic lights systems. Document type: Article

Abstract

The Macroscopic Fundamental Diagram (MFD) describes the relation between accumulation and speed in a zone. While theoretically expected, empirical validations have been done with limited numbers of floating car (e.g., taxi) data, and loop detectors. This paper will verify existence, shape and crispness of the MFD using Floating Car Data (FCD) from Google. Due to the large amount of users (i.e., high penetration rate), this unique data-set contains traffic information with a high spatial resolution, a high spatial scope and high reliability. We use the data for 3 purposes. First, an MFD for the city of Amsterdam is constructed, revealing a strong relationship between the average density and the average flow. It also shows that the urban road network never reaches its capacity. Secondly, inhomogeneity is analysed. Traffic is well spread over the network, hence inhomogeneity is low. Moreover, if present, the inhomogeneity has only a minor effect on the flow. Also traffic in different directions is homogeneous. Thirdly, for the first time, an MFD is created for a whole country, which turned out to be very crisp as well. This suggests that small areas or a directional split are not needed to create crisp MFDs. That, in turn, implies that a crisp MFD is not a sufficient condition to apply control without considering internal dynamics. "br