Zustandsschätzung von Lichtsignalanlagen mittels niederfrequenter Floating Car Data

In this thesis, a novel methodology for the traffic signal state prediction based on real-world Floating Car Data (FCD) has been developed. In order to understand the characteristics of a real-world, commercially available FCD source, a one year dataset obtained from the ADAC (General German Automobile Club) is analyzed at two major intersections in Munich (Germany). Motivated by sparse and likewise low-frequently sampled trajectory volumes, this work developed a comprehensive methodology that covers all aspects of the data processing to infer hourly estimates of the signal timing parameters, such as the cycle length and the green intervals typically used on workdays or weekends. These parameters allow the prediction of future traffic signal states with respect to different constraints. The thesis describes a novel hypothesis-based cycle length estimation procedure that estimates the typical cycle length for an hour by analyzing vehicle stop bar crossing events. These events are projected into the time scale of potential cycle length candidates by the help of a modulo operation. Only the correct cycle length causes a concentration of crossing events within the cycle time, which is exploited by the hypothesis test. The concept has been analyzed for a fixed-time controlled intersection by means of a Monte-Carlo-Simulation. The thesis describes moreover the development of a green interval estimation methodology that is capable to deduce the green interval by exploiting sparse crossing events as well as stopped vehicles. The concept relies on an iterative classification procedure that infers the green interval by analyzing the number of counted crossing events per cycle second. A rule-based and iterative self-verification process checks the consistency of the green interval, which makes the method robust when working with small samples sizes. In addition, the thesis closed the gap of a missing green interval verification that checks overlapping green intervals of conflicting movements, caused by traffic actuation. As the developed concept requires ideally green interval estimates on all conflicting movements, the thesis developed also a novel cluster-based approach that tries to identify hours with very similar signal timing parameters. This time clustering allows the signal timing estimation even on movements with small trajectory samples sizes. Finally, the complete concept was calibrated and validated at four real-world intersections in Munich (Germany).In dieser Arbeit wurde eine neuartige Methode zur Schätzung von Signalzuständen an Lichtsignalanlagen (LSA) auf Basis realer Floating Car Data (FCD) entwickelt. Um die Beschaffenheit einer realen, kommerziell verfügbaren FCD-Quelle zu verstehen, wurde ein jährlicher FC-Datensatz des ADAC (Allgemeiner Deutscher Automobil-Club) an zwei Knotenpunkten in München analysiert. Motiviert durch das geringe Trajektorienaufkommen, wurde eine durchgängige Methodik zur Verarbeitung weniger Trajektorien mit zeitlich niedriger Auflösung entwickelt. Das Verfahren ermöglicht die Schätzung werktäglicher, typischer Umlauf- und Freigabezeiten für einzelne Stunden im Tagesgang. Die Parameter können unter Randbedingungen zur Schätzung zukünftiger Signalzustände verwendet werden. Die Methodik basiert im Kern auf der Auswertung von Querungsvorgänge an der Haltlinie. Die beobachtenden Querungen werden mittels Modulo Operator in den Zeitstrahl einer hypothetischen Umlaufzeit projiziert. Lediglich die Verwendung der korrekten Umlaufzeit führt zu einer Konzentration der Querungsvorgänge innerhalb der Umlaufzeit. Dieser Effekt kann mittels Hypothesentest zur Identifikation der wahren Umlaufzeit ausgenutzt werden. Das Verfahren wurde mit einer Monte-Carlo-Simulation analysiert. Ein weiteres Ziel war die Schätzung von Freigabezeiten an einzelnen Fahrströmen. Hierzu werden neben Querungsvorgängen auch die Anzahl wartender Fahrzeuge über die Umlaufzeit ausgewertet. Mittels eines iterativen Klassifikationsprozesses werden einzelne Umlaufsekunden in Abhängigkeit des Datenaufkommens zu einer zeitlich konsistenten Freigabezeit verarbeitet. Zur Plausibilisierung der Ergebnisse setzt die Methodik auf einen iterativen Selbstprüfungsprozess, bei dem daten- und zeitspezifische Randbedingungen eingehalten werden müssen. Darüber hinaus beschreibt die Arbeit ein Verfahren zur Plausibilisierung von Freigabezeiten an Konfliktströmen. Voraussetzung für diese Methodik ist das Vorhandensein von Freigabezeitschätzungen auf vielen Konfliktströmen des Knotenpunktes. Zur Erreichung dieser Anforderung wurde ein Clusterverfahren zur Erkennung von Stunden mit ähnlichen Signalprogrammparameter entwickelt. Die Clusterung ermöglicht damit auch die Berechnung von Freigabezeiten auf Fahrströmen mit geringem FCD Aufkommen. Die gesamte Methodik wurde an vier ausgewählten LSA in München kalibriert und validiert. Die Qualität der Zustandsschätzung wurde mittels statistischer Indikatoren bewertet

Mode choice and ride-pooling simulation: A comparison of mobiTopp, Fleetpy, and MATSim

On-demand ride-pooling systems have gained a lot of attraction in the past years as they promise to reduce traffic and vehicle fleets compared to private vehicles. Transport simulations show that automation of vehicles and resulting fare reductions enable large-scale ride-pooling systems to have a high potential to drastically change urban transportation. For a realistic simulation of the new transport mode it is essential to model the interplay of ride-pooling demand and supply. Hence, these simulations should incorporate (1) a mode choice model to measure demand levels and (2) a dynamic model of the on-demand ride-pooling system to measure the service level and fleet performance. We compare two different simulation frameworks that both incorporate both aspects and compare their results with an identical input. It is shown that both systems are capable of generating realistic results and assessing mode choice and ride-pooling schemes. Commonalities and differences are identified and discussed

The age of the Galactic thin disk from Th/Eu nucleocosmochronology I. Determination of [Th/Eu] abundance ratios

The purpose of this work is to resume investigation of Galactic thin disk dating using nucleocosmochronology with Th/Eu stellar abundance ratios, a theme absent from the literature since 1990. A stellar sample of 20 disk dwarfs/subgiants of F5 to G8 spectral types with -0.8 <= [Fe/H] <= +0.3 was selected. In stars with such spectral types and luminosity classes, spectral synthesis techniques must be employed if we wish to achieve acceptably accurate results. A homogeneous, self-consistent set of atmospheric parameters was determined. Effective temperatures were determined from photometric calibrations and H-alpha profile fitting; surface gravities were obtained from Teff, stellar masses and luminosities; microturbulence velocities and metallicities were obtained from detailed, differential spectroscopic analysis, relative to the Sun, using equivalent widths of Fe I and Fe II lines. Chemical abundances of the elements that contaminate the Th and Eu spectral regions (Ti, V, Cr, Mn, Co, Ni, Ce, Nd, and Sm) were determined through spectroscopic analysis. Abundance uncertainties were thoroughly scrutinised, their average value - (0.10 +/- 0.02) dex - being found to be satisfactorily low. Eu and Th abundances were determined by spectral synthesis of one Eu II line (4129.72 A) and one Th II line (4019.13 A), taking into account the detailed hyperfine structures of contaminating Co lines, as well as the hyperfine structure and isotope shift of the Eu line. Comparison of our abundances with literature data shows that our results exhibit a similar behaviour, but a considerably lower scatter (36% lower for Eu, and 61% lower for Th). The [Th/Eu] abundance ratios thus obtained were used, in the second paper of this series, to determine the age of the Galactic disk.Comment: 27 pages, 22 Postscript figures, accepted for publication in Astronomy & Astrophysics, final versio

Flow-inflated selective sampling: Efficient agent-based dynamic ride-sharing simulations

Agent-based simulations have become a popular and powerful tool for simulating emergent mobil- ity modes. Often times, the memory and computing requirements are daunting. Scaling down agent populations by simulating only a fraction of all agents is a frequently used option to reduce these burdens. However, recent studies have pointed out the difficulty of scaling ride-sharing simulations as these rely heavily on demand density and do not scale linearly. In this study, we introduce a simple yet effective methodology for simulating dynamic ride-sharing services, which we call flow-inflated selective sampling (FISS). The basic operation is that, similar to scaling agent-based populations, only a fraction of the actual agents are explicitly assigned. However, here only trips of private car transport are sampled, while public transport as well as ride-sharing vehicles are fully represented. In contrast to scaling in previous studies, the network capacity is not adjusted. Rather, the capacity consumption of the cars is scaled up to obtain realistic traffic flows. We implement this approach in the MATSim simulation environment for a large scenario in the region of Munich, Germany and show that our approach preserves traffic flows while keeping key performance indicators of a ride-sharing service stable and mostly unbiased. Mode choice decisions based on this approach also remain stable. By introducing our approach, the run-times of the actual assignment can be almost halved

Navigation of blind and visually impaired people

The mobility of the blind and visually impaired is associated with many barriers and risks. To secure crossings, signalized intersections are partially equipped with acoustic or tactile indicators. However, environmental conditions might interfere with the acoustic identification of the green time. Furthermore, information such as intersection topology, bicycle traffic or the curb structure is not accessible to visually impaired road users. Therefore, most trips are limited to trained routes. Within the research project InMoBS (intra-urban mobility support for the blind and visually impaired) a prototype of a route planning and navigation system has been developed and evaluated in an exploratory manner

Mode choice and ride-pooling simulation: A comparison of mobiTopp, Fleetpy, and MATSim

On-demand ride-pooling systems have gained a lot of attraction in the past years as they promise to reduce traffic and vehicle fleets compared to private vehicles. Transport simulations show that automation of vehicles and resulting fare reductions enable large-scale ride-pooling systems to have a high potential to drastically change urban transportation. For a realistic simulation of the new transport mode it is essential to model the interplay of ride-pooling demand and supply. Hence, these simulations should incorporate (1) a mode choice model to measure demand levels and (2) a dynamic model of the on-demand ride-pooling system to measure the service level and fleet performance. We compare two different simulation frameworks that both incorporate both aspects and compare their results with an identical input. It is shown that both systems are capable of generating realistic results and assessing mode choice and ride-pooling schemes. Commonalities and differences are identified and discussed.ISSN:1877-050