Towards detecting, characterizing and rating of road class errors in crowd-sourced road network databases

OpenStreetMap (OSM), with its global coverage and Open Database License, has recently gained popularity. Its quality is adequate for many applications, but since it is crowd-sourced, errors remain an issue. Errors in associated tags of the road network, for example, are impacting routing applications. Particularly road classification errors often lead to false assumptions about capacity, maximum speed, or road quality which could then result in detours for routing applications. This study aims at finding potential classification errors automatically, which can then be checked and corrected by a human expert. We develop a novel approach to detect road classification errors in OSM by searching for disconnected parts and gaps in different levels of a hierarchical road network. Different parameters are identified that indicate gaps in road networks. These parameters are then combined in a rating system to obtain an error probability in order to suggest possible misclassifications to a human user. The methodology is applied exemplarily for the state of New South Wales in Australia. The results demonstrate that (1) more classification errors are found at gaps than at disconnected parts and (2) the gap search enables the user to find classification errors quickly using the developed rating system that indicates an error probability. In future work, the methodology can be extended to include available tags in OSM for the rating system. The source code of the implementation is available via GitHub

Enhancing OpenStreetMap for the Assessment of Critical Road Infrastructure in a Disaster Context

Die Häufigkeit von Naturkatastrophen nimmt weltweit zu, was zu immensen Schäden an kritischer Straßeninfrastruktur und deren Funktionalität führen kann. Daher ist es von entscheidender Bedeutung, die Funktionalität kritischer Straßeninfrastruktur vor, während und nach einer Katastrophe zu beurteilen. Dazu werden globale Straßendaten benötigt, die für die Routenplanung nutzbar sind. OpenStreetMap (OSM) stellt globale Straßennetzdaten zur Verfügung, die kostenlos und frei zugänglich sind. Allerdings ist die Verwendung der OSM Straßendaten für Routenplanungsanwendungen oft eine Herausforderung. Das übergeordnete Ziel dieser Arbeit ist die Entwicklung eines generischen, mehrskaligen Konzepts zur Analyse kritischer Straßeninfrastrukturen im Kontext von Naturgefahren unter Verwendung von OSM Daten. Dafür werden zwei aufeinander folgende Forschungsziele aufgestellt: (i) die Verbesserung der Routingfähigkeit von OSM Daten und (ii) die Bewertung kritischer Straßeninfrastruktur im Kontext von Naturgefahren. Daraus resultiert die Gliederung dieser Arbeit in zwei Hauptteile, die jeweils den Forschungszielen entsprechen. Im ersten Teil dieser Arbeit wird die Nutzbarkeit von OSM Daten für Routing Anwendungen verbessert. Zunächst wird dafür die Qualität des OSM Straßennetzwerks im Detail analysiert. Dabei werden zwei große Herausforderungen im Bereich der Anwendbarkeit von OSM Daten für die Routenplanung identifiziert: fehlende Geschwindigkeitsangaben und Fehler in der Straßenklassifizierung. Um die erste Herausforderung zu bewältigen, wird ein FuzzyFramework zur Geschwindigkeitsschätzung (Fuzzy-FSE) entwickelt, welches eine Fuzzy Regelung zur Schätzung der Durchschnittsgeschwindigkeit einsetzt. Diese Fuzzy Regelung basiert auf den Parametern Straßenklasse, Straßenneigung, Straßenoberfläche und Straßenlänge einsetzt. Das Fuzzy-FSE besteht aus zwei Teilen: einer Regel- und Wissensbasis, die über die Zugehörigkeitsfunktionen für den Ausgangsparameter Geschwindigkeit entscheidet, und mehrere Fuzzy-Regelsysteme, welche die resultierende Durchschnittsgeschwindigkeit berechnen. Die Ergebnisse zeigen, dass das Fuzzy-FSE auch bei ausschließlicher Verwendung von OSM Daten eine bessere Leistung erbringt als bestehende Methoden. Die Herausforderung der fehlerhaften Straßenklassifizierung wird durch die Entwicklung eines neuartigen Ansatzes zur Erkennung von Klassifizierungfehlern in OSM angegangen. Dabei wird sowohl nach nicht verbundenen Netzwerkteilen als auch nach Lücken im Straßennetzwerk gesucht. Verschiedene Parameter werden in einem Bewertungssystem kombiniert, um eine Fehlerwahrscheinlichkeit zu erhalten. Auf Basis der Fehlerwahrscheinlichkeit kann ein menschlicher Nutzer diese Fehler überprüfen und korrigieren. Die Ergebnisse deuten einerseits darauf hin, dass an Lücken mehr Klassifizierungsfehler gefunden werden als an nicht verbundenen Netzwerkteilen. Andererseits zeigen sie, dass das entwickelte Bewertungssystem bei einer benutzergesteuerten Suche nach Lücken zu einem schnellen Aufdecken von Klassifizierungsfehlern verwendet werden kann. Aus dem ersten Teil dieser Arbeit ergibt sich somit ein erweiterter OSM Datensatz mit verbesserter Routingfähigkeit. Im zweiten Teil dieser Arbeit werden die erweiterten OSM Daten zur Bewertung der kritischen Straßeninfrastruktur im Katastrophenkontext verwendet. Dazu wird der zweite Teil des generischen, mehrskaligen Konzepts entwickelt, das aus mehreren, miteinander verbundenen Modulen besteht. Ein Modul implementiert zwei Erreichbarkeitsindizes, welche verschiedene Aspekte der Erreichbarkeit im Straßennetzwerk hervorheben. In einem weiteren Modul wird ein grundlegendes Modell der Verkehrsnachfrage entwickelt, welches den täglichen interstädtischen Verkehr ausschließlich auf der Grundlage von OSM Daten schätzt. Ein drittes Modul verwendet die oben beschriebenen Module zur Schätzung verschiedener Arten von Auswirkungen von Naturkatastrophen auf das Straßennetzwerk. Schließlich wird in einem vierten Modul die Vulnerabilität des Straßennetzes gegenüber weiteren Schäden bei Langzeitkatastrophen analysiert. Das generische Konzept mit allen Modulen wird exemplarisch in zwei verschiedenen Regionen für zwei Waldbrandszenarien angewendet. Die Ergebnisse der Fallstudien zeigen, dass das Konzept ein wertvolles, flexibles und global anwendbares Instrument für Regionalplaner und Katastrophenmanagement darstellt, das länder- bzw. regionenspezifische Anpassungen ermöglicht und gleichzeitig wenig Daten benötigt

Understanding Urban Mobility and Pedestrian Movement

Urban environments continue to expand and mutate, both in terms of size of urban area and number of people commuting daily as well as the number of options for personal mobility. City layouts and infrastructure also change constantly, subject to both short-term and long-term imperatives. Transportation networks have attracted particular attention in recent years, due to efforts to incorporate “green” options, enabling positive lifestyle choices such as walking or cycling commutes. In this chapter we explore the pedestrian viewpoint, aids to familiarity with and ease of navigation in the urban environment, and the impact of novel modes of individual transport (as options such as smart urban bicycles and electric scooters increasingly become the norm). We discuss principal factors influencing rapid transit to daily and leisure destinations, such as schools, offices, parks, and entertainment venues, but also those which facilitate rapid evacuation and movement of large crowds from these locations, characterized by high occupation density or throughput. The focus of the chapter is on understanding and representing pedestrian behavior through the agent-based modeling paradigm, allowing both large numbers of individual actions with active awareness of the environment to be simulated and pedestrian group movements to be modeled on real urban networks, together with congestion and evacuation pattern visualization

Urban Modality:

This thesis proposes a framework for evaluating the mobility potential and performance of urban areas in the city region, as an instrument to support urban development that contributes positively to regional sustainable mobility objectives. The research takes a quantitative approach, modelling and measuring the characteristics of a city-region and of its individual urban areas, in terms of travel patterns and socioeconomic characteristics of the resident population, and in terms of built environment characteristics. It then explores how the built environment defines the affordances of urban areas for travelling by particular modes of transport, i.e. its walk-ability, cycleability, drive-ability and transit-ability, by developing a typology of what I call their ‘urban modality’. And finally the work combines this typology with the socio-economic characteristics of urban areas to determine their sustainable mobility potential and performance. It focuses on the case of the Randstad region of the Netherlands and its VINEX neighbourhoods, which are an emblematic example of new urban areas created under a policy programme with sustainable mobility objectives. A key stance in this work is the understanding that the location of an urban area in the region can be indicative of its population’s travel patterns, because the built environment (infrastructural) and socio-economic characteristics are interrelated and present strong regional spatial patterns. What types of urban areas support sustainable travel patterns, and what are their spatial characteristics? How do new neighbourhoods compare to the best performing urban areas, and to other areas of the same ‘modality’ type? These are some of the questions addressed in this study. There are two main contributions of this research: the methods for building and analysing integrated multimodal network models, and the framework for contextual performance evaluation using urban area typologies. The integrated multimodal network model combines the various mobility infrastructure networks and the buildings’ land use to create a detailed description of the region, using open spatial data and open source Geographic Information Systems (GIS) technologies. The network model’s spatial analysis covers local urban form indicators, such as street layout, network density and land use mix, as well as regional indicators of multimodal accessibility and network configuration (its structure), to give a holistic profile of urban areas across modes and scales of travel. The analysis results go through exploratory data mining and classification procedures to identify urban form typologies of urban areas. It is shown that there is a relation between this ‘urban modality’ of urban areas and the travel patterns of their residents, measured as a set of sustainable mobility indicators related to mode share and distance travelled. For this reason, ‘urban modality’ offers the possibility for ex-ante evaluation of sustainable mobility potential of planned urban areas. Furthermore, when combined with the socio-economic profile of the resident population, ‘urban modality’ defines a context for the ex-post evaluation of sustainable mobility performance of existing urban areas. The evaluation of suburban areas together with the more central historical urban areas gives invariably a high score in sustainable travel to the central areas, and rates the suburban areas negatively. On the other hand, the evaluation of sustainable mobility performance in the context of suburban areas of the same type allows the finer distinction of underperformers that have scope for improvement, and overachievers that provide examples of (relative) success. This contextual evaluation can become a decision support instrument for “hard” and “soft” planning measures involving sustainable mobility targets. Applying this method to the set of VINEX neighbourhoods of the Randstad leads to the conclusion that despite being planned following the same policy objectives, the neighbourhoods have different types of ‘urban modality’, thus present different levels of sustainable mobility potential. Neighbourhoods identified as underperformers within their context can be targeted for soft measures related to transport services, technology and individual attitudes to travel, to fulfil the potential of their ‘urban modality’ type. However, if this potential is not deemed satisfactory or if they already overachieve, only by retrofitting a set of infrastructure and land use characteristics will lead to a different ‘urban modality’ type, and a change in potential. Such a change can be lengthy, costly and sometimes impossible to implement ex-post. The thesis is based on a collection of published articles in peer-reviewed academic publications, with the first and last chapters providing an overview of the research and of its findings, and defining the main narrative thread

Urban Modality

This thesis proposes a framework for evaluating the mobility potential and performance of urban areas in the city region, as an instrument to support urban development that contributes positively to regional sustainable mobility objectives. The research takes a quantitative approach, modelling and measuring the characteristics of a city-region and of its individual urban areas, in terms of travel patterns and socioeconomic characteristics of the resident population, and in terms of built environment characteristics. It then explores how the built environment defines the affordances of urban areas for travelling by particular modes of transport, i.e. its walk-ability, cycleability, drive-ability and transit-ability, by developing a typology of what I call their ‘urban modality’. And finally the work combines this typology with the socio-economic characteristics of urban areas to determine their sustainable mobility potential and performance. It focuses on the case of the Randstad region of the Netherlands and its VINEX neighbourhoods, which are an emblematic example of new urban areas created under a policy programme with sustainable mobility objectives. A key stance in this work is the understanding that the location of an urban area in the region can be indicative of its population’s travel patterns, because the built environment (infrastructural) and socio-economic characteristics are interrelated and present strong regional spatial patterns. What types of urban areas support sustainable travel patterns, and what are their spatial characteristics? How do new neighbourhoods compare to the best performing urban areas, and to other areas of the same ‘modality’ type? These are some of the questions addressed in this study. There are two main contributions of this research: the methods for building and analysing integrated multimodal network models, and the framework for contextual performance evaluation using urban area typologies. The integrated multimodal network model combines the various mobility infrastructure networks and the buildings’ land use to create a detailed description of the region, using open spatial data and open source Geographic Information Systems (GIS) technologies. The network model’s spatial analysis covers local urban form indicators, such as street layout, network density and land use mix, as well as regional indicators of multimodal accessibility and network configuration (its structure), to give a holistic profile of urban areas across modes and scales of travel. The analysis results go through exploratory data mining and classification procedures to identify urban form typologies of urban areas. It is shown that there is a relation between this ‘urban modality’ of urban areas and the travel patterns of their residents, measured as a set of sustainable mobility indicators related to mode share and distance travelled. For this reason, ‘urban modality’ offers the possibility for ex-ante evaluation of sustainable mobility potential of planned urban areas. Furthermore, when combined with the socio-economic profile of the resident population, ‘urban modality’ defines a context for the ex-post evaluation of sustainable mobility performance of existing urban areas. The evaluation of suburban areas together with the more central historical urban areas gives invariably a high score in sustainable travel to the central areas, and rates the suburban areas negatively. On the other hand, the evaluation of sustainable mobility performance in the context of suburban areas of the same type allows the finer distinction of underperformers that have scope for improvement, and overachievers that provide examples of (relative) success. This contextual evaluation can become a decision support instrument for “hard” and “soft” planning measures involving sustainable mobility targets. Applying this method to the set of VINEX neighbourhoods of the Randstad leads to the conclusion that despite being planned following the same policy objectives, the neighbourhoods have different types of ‘urban modality’, thus present different levels of sustainable mobility potential. Neighbourhoods identified as underperformers within their context can be targeted for soft measures related to transport services, technology and individual attitudes to travel, to fulfil the potential of their ‘urban modality’ type. However, if this potential is not deemed satisfactory or if they already overachieve, only by retrofitting a set of infrastructure and land use characteristics will lead to a different ‘urban modality’ type, and a change in potential. Such a change can be lengthy, costly and sometimes impossible to implement ex-post. The thesis is based on a collection of published articles in peer-reviewed academic publications, with the first and last chapters providing an overview of the research and of its findings, and defining the main narrative thread

Multi-scale Pedestrian Navigation and Movement in Urban Areas

Sustainable transport planning highlights the importance of walking to low-carbon and healthy urban transport systems. Studies have identified multiple ways in which vehicle traffic can negatively impact pedestrians and inhibit walking intentions. However, pedestrian-vehicle interactions are underrepresented in models of pedestrian mobility. This omission limits the ability of transport simulations to support pedestrian-centric street design. Pedestrian navigation decisions take place simultaneously at multiple spatial scales. Yet most models of pedestrian behaviour focus either on local physical interactions or optimisation of routes across a road network. This thesis presents a novel hierarchical pedestrian route choice framework that integrates dynamic, perceptual decisions at the street level with abstract, network based decisions at the neighbourhood level. The framework is based on Construal Level Theory which states that decision makers construe decisions based on their psychological distance from the object of the decision. The route choice framework is implemented in a spatial agent-based simulation in which pedestrian and vehicle agents complete trips in an urban environment. Global sensitivity analysis is used to explore the behaviour produced by the multi-scale pedestrian route choice model. Finally, simulation experiments are used to explore the impacts of restrictions to pedestrian movement. The results demonstrate the potential insights that can be gained by linking street scale movement and interactions with neighbourhood level mobility patterns