Abstract

In traffic flow analysis several regimes are distinguished, such as congested and non-congested flow conditions. Indications exist that driving behavior differs by regime, and that it may change discontinuously between regimes. In contrast, most traffic flow models used today basically assume the same car-following behavior irrespective of the traffic flow regime. It is hypothesized that because of this deficiency, these models do not always perform satisfactorily. To clarify this issue, differences in car-following between congested and non-congested flow are analyzed with data from two sites on Dutch freeways. It is shown that, at the same speeds, passenger car drivers follow with smaller headways in non-congested flow than in congested flow. Car-following of truck drivers does not show differences between regimes. Microscopic distance gap - speed models are established for several road user classes, valid for each of the two flow regimes. To show the improvements resulting from these new microscopic relationships, the latter are implemented in a micro simulation model (FOSIM) with which macroscopic patterns in traffic flow are modeled. The macroscopic findings produced with the regime specific car-following rules show a considerable improvement in modeling performance.

Abstract

The road congestion problem in The Netherlands is addressed. Focus is on congestion development and congestion patterns on the Dutch motonA/ays. In order to understand the nature and extent of motorway congestion a description is given of the special features of the Dutch motorway network. Special attention is devoted to the design principles that explicitly take congestion into account. Figures are presented on the level, nature and extent of the congestion pattern using a variety of congestion indicators. Having described the symptoms an analysis is presented of the main factors causing congestion in the past decades and in the future. This forms the stepping stone for a presentation of Dutch transport policy towards curbing congestion and improved traffic flow quality. This presentation focusses on the target group approach and on dynamic traffic management including congestion pricing. The conclusions try to give an assessment of the possibilities to achieve improvements.

Abstract

Motivated by the desire to explore future traffic flows that will consist of a mixture of classical vehicles and vehicles equipped with advanced driver assistance systems, new mathematical theories and models are developed. The basis for this theory was borrowed from the kinetic description of gas flows, where we replaced the behaviour of the molecules by typical human driving behaviour. From a methodological point of view, this 'human-kinetic' traffic flow theory provides two major improvements with respect to existing theory. Firstly, the model builds exclusively on a mathematical description of individual driver behaviour, whereas traditionally field measurements of traffic flow variables like flow rate and average speed of the flow are needed. This is of major importance for the exploration of future traffic flows with vehicles and equipment that are not yet on the market, and for which at best individual test results from driving simulator experiments or small scale field trials are available. Secondly, the model accounts for the more refined aspects of individual driver behaviour by considering the 'internal' state of the driver (active/passive, aware/unaware,...) and the variations of driving strategy that occur during driving. This is important when the ambition is to capture refined congestion patterns like the occurrence of stop-and-go waves, oscillating congestion and long jams, where the driving strategy may depend for instance on the motivation of the driver to follow closely. This new theory links together the worlds of traffic engineers and behavioural scientists. As such, it is a promising tool that increases the insight in the human behaviour as a basis of various dynamic congestion patterns, and it facilitates the design and evaluation of electronic systems in the vehicle that assist the driver to behave safer, more comfortable and more efficient in busy traffic flows. Herewith, the results of this research are relevant, both for the theoretical interest of the TRAIL research school, and for the more practically oriented work of TNO, who provided financing for this research in the joint T3 research program.

Abstract

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2013 Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2013 Bu çalışmada, ilk olarak simülasyon ve kontrol stratejilerinin temelini oluşturan trafik akım teorileri makro ölçekli olarak anlatılmıştır. Ardından hidrolik modellerden türetilen trafik değişkenleri tanıtılmış ve bunların aralarındaki ilişkiler gösterilmiştir. Trafik sıkışıklığının ana sebebi olan şok dalgaları analitik olarak incelenmiştir. Daha sonra, bu modellere yapılan ana eleştiriler ve bu modele yapılan iyileştirmeler özetlenmiştir. Çalışmanın üçüncü kısmında makro-mikro-mezo ölçekli simülasyon modelleri anlatılmış ve ardından dördüncü bölümde trafik kontrol yaklaşımları anlatılmıştır. Çalışmanın uygulama kısmında, çalışma sahası tanıtılmıştır. RTMS ten (Remote Traffic Microwave Sensor-Uzaktan Trafik Mikrodalga Algılayıcısı) veri toplama yöntemi anlatılmış ve veri metodolojisi anlatılmıştır. Bununla birlikte, mikro ölçekli simülasyon programı PTV VISSIM tanıtılarak bu programın uzunlamasına ve yanal hareket modelleri anlatılmıştır. Kalibrasyon yöntemi anlatılarak simülasyonun geçerliliği sınanmıştır. Dinamik katılım konreol yaklaşımlarında ALINEA algoritmasının özel iki durumu sınanmış ve değişken hız yönetimi yaklaşımı için dört durum önerilmiştir. Katılım kontrolü için yeşil süre değişimleri, değişken hız yönetimi uygulamaları için hız limitlerinin değişimi ve yoğunluk profilleri çizdirilmiştir. Son olarak toplam seyahat süresi, taşıt başına ortalama gecikme süreleri, taşıt başına ortalama dur kalk sayıları gibi değişik performans ölçütleri için sonuçlar değerlendirilmiştir. In this thesis, Firstly traffic flow theories are mainly introduced in macroscale which forms the basis of the most of the simulation studies and control strategies. Then relationship between the traffic variables are demonstrated and the flow theories based on the hyraulic model are analyzed and the shockwaves which are the main reason of the traffic congestion shown analytically. Thereafter, main critisism about these models are discussed and improvements are summarized. In the third section of this study macro-micro-mesoscopic simulation models are described and later in the fourth section traffic control approaches are explained. In the application part of this study, the study field is introduced. Data collection methods from RTMS (Remote Traffic Microwave Sensor) are briefly explained and the data methodology is expressed. Moreover, the microsimulation program PTV VISSIM is described and longitudinal and lateral movement models are described. Calibration method is described which demonstrates the validation of the simulation. For dynamic ramp metering approach two cases of ALINEA algorithm are proposed and for VSL approaches four cases are proposed. The fluctuations of the green time for ramp metering and the speed limits for VSL is plotted. Also density profiles for each approach is selected. At the end, results are discussed for various performance indicators such as total travel time, average delay time per vehicle, average number of stops per vehicle, etc. Yüksek Lisans M.Sc.

Abstract

This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the microscopic level and the resulting traffic flow characteristics at the macroscopic level. The results give new insights into impacts of ADAS on traffic flow characteristics.

Abstract

This paper presents a continuous traffic-flow model for the explorative analysis of advanced driver-assistance systems (ADASs). Such systems use technology (sensors and intervehicle communication) to support the task of the driver, who retains full control over the vehicle. Based on a review of different traffic-flow modeling approaches and their suitability for exploring traffic-flow patterns in the presence of ADASs, kinetic traffic-flow models are selected because of their good representation on both the aggregate level (congestion dynamics) and the level of the individual vehicle (vehicular interactions either directly or through intervehicle communication). The human-kinetic modeling approach is presented. It is a multiclass variant of kinetic traffic-flow models that is strongly based on individual driver behavior, i.e., on fully continuous acceleration/deceleration behavior and explicit modeling of the activation level of the driver. The strength of this modeling approach is illustrated by application to a driver-assistance system that uses intervehicle communication. It warns drivers when approaching sharp decelerations in a queue tail. The explorative analysis shows that the system results in safer and smoother transition from free-flowing to congested traffic. It also avoids compression of the queue tail, thus preventing the emergence of stop-and-go congestion patterns.