Andreas Keler | Kyoto University (original) (raw)

Papers by Andreas Keler

31st Geographical Information Science Research UK (GISRUK) Conference (GISRUK), 2023

The Digital Twin Munich project (DZ-M) aims to depict complex urban environments through the use ... more The Digital Twin Munich project (DZ-M) aims to depict complex urban environments through the use of static and dynamic components, and their semantic relationships. The project focuses on the development of a street network model and urban mobility simulation, utilizing the open source microscopic traffic flow simulation software SUMO. The transport demand is provided by the VISUM model of the city of Munich, and the data structure developed is compatible with standards such as OpenStreetMap, OpenDrive, CityGML, and GTFS. The project also includes the use of physical VRU simulators for data collection purposes, and the integration of these simulations into a 3D VR environment in Unity.

SUMO Conference Proceedings, 2023

Travel demand is an essential input for the creation of traffic models. However, estimating trave... more Travel demand is an essential input for the creation of traffic models. However, estimating travel demand to accurately represent traffic behaviour usually requires the collection of extensive sets of data on traffic behaviour. Traffic counts are a comparably cost effective and reproducible source of information on travel demand. The utilisation of traffic counts to estimate demand is commonly found in the literature as the static and dynamic O-D estimation problem. A variety of approaches have been developed over recent decades to tackle this problem. Usually initial estimates of the O-D matrix are calibrated by utilising traffic counts and considering different assignment models. Other approaches for the estimation of travel demand solely based on traffic measurements can be found in the simulation software SUMO. The present work demonstrates the systematic development of a network model in SUMO in the inner city of Munich. In a sample network the estimation of travel demand through the tools flowrouter and routeSampler is tested by utilising flow measurements from induction loop detectors. The tests delivered unsatisfactory results, which is proven through observations of traffic flows in the resulting simulations as well as comparisons to historic traffic counts. The lack of sufficient detector data and the complexity of the sample network are discussed as the main reasons for the results. It is concluded that the applied tools should be tested in future studies with a more extensive dataset to perform a more comprehensive review of both tools. Therefore, we deliver specific requirements based on the network example of Munich.

SUMO User Conference 2023, 2023

Microscopic traffic flow simulations as tools for enabling detailed insights on traffic efficienc... more Microscopic traffic flow simulations as tools for enabling detailed insights on traffic efficiency and safety gained numerous popularity among transportation researchers, planners and engineers in the first to decades of the 21 st century. By implementing a test bed for simulation scenarios of complex urban transportation infrastructure it is possible to inspect specific effects of introducing small infrastructural changes related to the built environment and to the introduction of advanced traffic control strategies. The possibility of reproducing present problems or the transportation services, such as the ones of public bus services is a key motivation of this work. In this research, we reproduce the road network of the city of Kyoto for observing specific travel patterns of public buses such as the bus bunching phenomena. Therefore, a selection of currently available data sets is used for calibrating a cutout of the Kyoto road network of a relatively large extent. After introducing a method for geodata extraction and conversion, we approach the calibration by introducing virtual detectors representing present inductive loops and make use of historical traffic count records. Additionally, we introduce bus routes partially contributed by volunteer mappers (OSM project). First simulation outcomes show numerous familiar (local knowledge) flow patterns.

DSC 2021 - 20th Driving Simulation & Virtual Reality Conference (DSC 2021), 2021

In this research, we present an interconnected (static) simulator setup for inspecting potential ... more In this research, we present an interconnected (static) simulator setup for inspecting potential communication between two test subjects at an urban static bottleneck, depicted in a virtual environment. The virtual bottleneck is a construction site blocking the right lane and the two test subjects respectively cycle on a bicycle simulator or drive in a driving simulator in the same direction on the same lane one after another (motorist behind cyclist). After they meet in front of the static bottleneck, we intend to create a situation of experienced uncertainty, which starts the process of communication between the two test subjects. Our proof of concept shows several important factors limiting the virtual experience, as related to scenario design, used equipment (VR glasses and monitors), audio signals and visualization.

DSC 2021 - 20th Driving Simulation & Virtual Reality Conference (DSC 2021), 2021

In this research, we estimate the influence of different bicycle infrastructure on the severity o... more In this research, we estimate the influence of different bicycle infrastructure on the severity of motorist-cyclist conflicts via an interconnected simulator study. Our focus is a specific conflict type: motorist is turning at an intersection and the cyclist is going straight, crossing the intersection based on previous evaluations from literature. Additionally, we reason on previously-conducted bicycle simulator studies and adapt specific methodological components of investigation area depiction in VR and scenario definition. In the end, we present four scenarios of a case study based on a signalized intersection in Ingolstadt, Germany, where we inspect motorist-cyclist conflicts in an interconnected simulator environment. After every simulator run both test subjects will be teleported to specific starting positions.

2020 IEEE Intelligent Vehicles Symposium (IV), 2020

This work explains the possible inferable information from a long-term video acquisition with cam... more This work explains the possible inferable information from a long-term video acquisition with cameras installed in close proximity to pedestrian movements with an unobstructed view of the entire intersection. The main goal is detecting implicit and explicit gestures and understanding communication and interactions between different types of road users. After explaining the designs of different gesture classification approaches, we relate the qualitative approach with our classification scheme for the extracted skeletons. To this end, a sequence with selected moving entities is selected and compared with the manually annotated video sequence. Results show the limitations of the automated approach and indicate a level of subjectivity in the manual annotation procedure. Subsequently, we discuss possibilities and restrictions of our approach and reflect on the importance of the specific conditions of video acquisitions. Depending on the field of view and distance between installed video cameras and moving vulnerable road users (VRUs), we are able to define the restrictions of our approach. As a result, we are able to define a selection of suitable applications for our approach.

Sustainability, 2021

Detailed specifications of urban traffic from different perspectives and scales are crucial for u... more Detailed specifications of urban traffic from different perspectives and scales are crucial for understanding and predicting traffic situations from the view of an autonomous vehicle (AV). We suggest a data-driven specification scheme for maneuvers at different design elements of the built infrastructure and focus on urban roundabouts in Germany. Based on real observations, we define classes of maneuvers, interactions and driving strategies for cyclists, pedestrians and motorized vehicles and define a matrix for merging different maneuvers, resulting in more complex interactions. The sequences of these interactions, which partially consist of explicit communications, are extracted from real observations and adapted into microscopic traffic flow simulations. The simulated maneuver sequences are then visualized in 3D environments and experienced by bicycle simulator test subjects. Using trajectory segments (in fictional space) from two conducted simulator studies, we relate the recorded movement patterns of test subjects with observed cyclists in reality.

KN - Journal of Cartography and Geographic Information, 2021

Investigating traffic volume is essential in order to be able to determine the impact of current ... more Investigating traffic volume is essential in order to be able to determine the impact of current and future traffic on road networks. The present study examines the Annual Average Daily Traffic (AADT) and the Heavy Commercial Annual Average Daily Traffic (HCAADT) in the metropolitan area of Minneapolis-St. Paul in 1996 and 2016. In particular, the traffic volume data is visualized both two- and three-dimensionally using various visualisation techniques. Comparisons based on these 2D and 3D visualisations strongly indicate an overall increase in traffic volume from 1996 to 2016. Differences between the increase of AADT and HCAADT data as well as spatially differing patterns could also be identified. The paper documents initial findings on visualizing traffic volumes in a two and three-dimensional way.

Sustainability, 2021

This research addresses the phenomenon of varying bicycle friendliness in urban areas and conside... more This research addresses the phenomenon of varying bicycle friendliness in urban areas and considers which elements are necessary to design a city in a bike-friendly manner. It aims to provide a deeper understanding of the term bikeability, in relation to the established term walkability, and methods to create models that measure the degree of bikeability in urban areas. We explain different established models and compare their computational bases. The focus of this paper is to define a computational methodology built within a Geographic Information System (GIS) and a subsequent evaluation based on an investigation area in Munich, Germany. We introduce a bikeability index for specific investigation areas and geovisualize four selected factors of this index. The resulting map views show the road segments of the traffic network where the conditions for biking are adequate, but also those segments which need to be improved.

Sustainability, 2021

Car-following models are used in microscopic simulation tools to calculate the longitudinal accel... more Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic simulations by adjusting and calibrating behavior models developed for motor vehicle traffic. However, very little work has been carried out to examine the following behavior of bicyclists, calibrate following models to fit this observed behavior, and determine the validity of these calibrated models. In this paper, microscopic trajectory data collected in a bicycle simulator study are used to estimate the following parameters of the psycho-physical Wiedemann 99 car-following model implemented in PTV Vissim. The Wiedemann 99 model is selected due to the larger number of assessable parameters and the greater possibility to calibrate the model to fit observed behavior. The calibrated model is validated using the indicator average queue dissipation time at a traffic light on the facilities ranging in width between 1.5 m to 2.5 m. Results show that the parameter set derived from the microscopic trajectory data creates more realistic simulated bicycle traffic than a suggested parameter set. However, it was not possible to achieve the large variation in average queue dissipation times that was observed in the field with either of the tested parameter sets.

Abstracts of the ICA , 2019

Learning to drive a car is not easy. Therefore, in many countries, driving schools offer an educa... more Learning to drive a car is not easy. Therefore, in many countries, driving schools offer an education of how to drive a car. This is taught on a theoretical and practical level. Once a driving student has learned how to handle a car in real traffic, he / she will take a driving test exam. In Germany, for example, an authorized driving examiner telling the students to follow their instructions conducts the practical exam. Thereby the driving examiner guides the student to different situation (for example taking a highway, crossing a complicated intersection, backward parking etc.). The examiner selects the route according to the criteria set out in the test guidelines and incorporates the road and traffic conditions in his choice. The driver test guidelines include basic driving tasks (parking, danger braking, etc.), a route within closed villages, a route outside built-up areas and / or motorway sections and afterwards a feedback on student performance. The test is set for a period of 45 minutes (for driving class B). Currently mobile devices, which are able to record a number of parameters (location, speed etc.) are rarely used in these driving examinations. Additionally, the route the driving instructor follows can be somewhat arbitrary. Utilizing routing systems in these driving examinations may assist the driving examiner and may help to make the examination more transparent. How can utilize routing algorithms to support driving examinations? In general routing algorithms offer a number of different parameters that may provide users with different type of routes, including the shortest, fastest, safest, most beautiful, least fuel/energy consumption (Ranacher et al. 2016), male/female (Häusler et al. 2010), easiest (Duckham and Kulik 2003) or most difficult (to drive) route (Krisp, Keler, and Karrais 2014). As Krisp & Keler (2015) suggest, that may also include the 'most difficult to drive route', which might be useful for driver training purposes. Previous research (Krisp and Keler 2015) has investigated what is an "easy to drive" route? and "what are the traffic situations that could be avoided for inexperienced drivers and/or driving beginners?". A number of commercial vendors offer products that include pre-programmed routes to help driving students to "learn" particular situations. We investigate selected parameters relevant for a driving test, in particular complicated crossings. This requires examinations on specific situations and the complexity of the road infrastructure. In a wider context, we aim to provide suggestions for a routing system that will help driving instructors and driving examiners, use standardized routes and thereby make driving examinations more transparent. Initial research in this context has been conducted an online questionnaire at the University of Augsburg. This questionnaire includes about seventy-five participants, which are mainly students. About 89% do have a driving license longer those two years. About 25% do not use a car on a regular base. Within this online questionnaire, sixteen driving situations are described. The participants rate each driving situation by agreeing or disagreeing to statements on these situations. For example, to the statement "I have problems with complicated crossings", about 43 % of participants "strongly agreed" or "agreed". The questionnaire shows that the basis for what is in easy or difficult to drive route seems to vary, based on the individual driver. A starting point to investigate, within the large number of driving situations, are "complicated crossings" (Krisp and Keler 2015) and to consider interactions to vulnerable road users. Figures 1 illustrates the challenge of defining complicated crossings based on static measures and dynamic measures. Static measures include the number of nodes that can be extracted from a road database, based on Krisp & Keler (Krisp and Keler 2015). Dynamic measures, like the traffic density or interaction points (between the traffic participants) at urban crossings are acquired via analysis of extracted video trajectories from cameras. Figure 1. Illustration showing the challenge of defining complicated crossings based on static measures (based on nodes derived from Open-Street Map) and dynamic measures (based on near real-time traffic cameras)

Traffic congestion in urban environments has severe influences on the daily life of people. Due t... more Traffic congestion in urban environments has severe influences on the daily life of people. Due to typical recurrent mobility patterns of commuters and transport fleets, we can detect traffic congestion events on selected hours of the day, so called rush hours. Besides the mentioned recurrent traffic congestion, there are non-recurrent events that may be caused by accidents or newly established building sites. We want to inspect this appearance using a massive Floating Taxi Data (FTD) set of Shanghai from 2007. We introduce a simple method for detecting and extracting congestion events on selected rush hours and for distinguishing between their recurrence and non-recurrence. By preselecting of similar velocity and driving direction values of the nearby situated FTD points, we provide the first part for the Shared Nearest Neighbour (SNN) clustering method, which follows with a density-based clustering. After the definition of our traffic congestion clusters, we try to connect ongoing events by querying individual taxi identifications. The detected events are then represented by polylines that connect density core points of the clusters. By comparing the shapes of congestion propagation polylines of different days, we try to classify recurrent congestion events that follow similar patterns. In the end, we reason on the reasonability of our method and mention further steps of its extension.

Mobility in urban environments is complex due to numerous interacting components , with many of t... more Mobility in urban environments is complex due to numerous interacting components , with many of those that are difficult to specify. Examples include the presence of transport hubs, which connect different modes of transport, public and private. The properties of these locations include a temporally changing surface area of operational function that is heavily dependent on the complex and dynamically changing human mobility. Besides public transport services with specified stations, there are taxi services that can be associated with established transport hubs in the way of assigning spatiotemporal service hotspots. This work proposes a technique for relating taxi trip origins and destination hotspots for gaining knowledge on the spatial uncertainties of transport hubs, more precisely their movements within specific times. The case study in NYC focuses on the services of yellow taxi and boro taxi trip data on Saturdays in June 2015. The outcomes of applying the technique are matter of further investigation of spatial uncertainty perception, representation, and visualization. In the stages of the approach, the outcomes of transport hub movements are related with more general functional transport regions resulting from NYC public transport services.

Detecting and describing movement of vehicles in established transportation infrastructures is an... more Detecting and describing movement of vehicles in established transportation infrastructures is an important task. It helps to predict periodical traffic patterns for optimizing traffic regulations and extending the functions of established transportation infrastructures. The detection of traffic patterns consists not only of analyses of arrangement patterns of multiple vehicle trajectories, but also of the inspection of the embedded geographical context. In this paper, we introduce a method for intersecting vehicle trajectories and extracting their intersection points for selected rush hours in urban environments. Those vehicle trajectory intersection points (TIP) are frequently visited locations within urban road networks and are subsequently formed into density-connected clusters, which are then represented as polygons. For representing temporal variations of the created polygons, we enrich these with vehicle trajectories of other times of the day and additional road network information. In a case study, we test our approach on massive taxi Floating Car Data (FCD) from Shanghai and road network data from the OpenStreetMap (OSM) project. The first test results show strong correlations with periodical traffic events in Shanghai. Based on these results, we reason out the usefulness of polygons representing frequently visited locations for analyses in urban planning and traffic engineering.

Daily mobility patterns in highly populated urban environments rely on a well-functioning effecti... more Daily mobility patterns in highly populated urban environments rely on a well-functioning effective road network. Nevertheless, traffic bottlenecks are typical for urban environments with periodic traffic congestion. In this paper, we focus on the investigation of how traffic congestion is related with complicated crossings. First, we select an approach for the classification of the complexity of road partitions and the derivation of complicated crossings based on geodata from Open-StreetMap (OSM). Second, we calculate traffic congestions using Floating Taxi Data (FTD) from Shanghai in 2007. Then, we develop a matching technique to link the congestion and complicated crossings, and subsequently define the concept of traffic bottlenecks represented by polygons. The bottlenecks indicate locations where the transportation infrastructure is complex and traffic congestion appears periodically. Finally, we select suitable cartographic representations of traffic bottlenecks in potential thematic vehicle traffic maps.

Recent services for car navigation include selections for computing the shortest, fastest or most... more Recent services for car navigation include selections for computing the shortest, fastest or most economic route between origin and destination. Our idea is to compute the least complex route, which might be challenging, since there is no consistent definition of complexity. We focus on the complexity of road intersections, which is experienced by vehicle drivers with the turning motion itself in selected crossroads. Therefore, we define weights for different turning possibilities. In a case study in Le Havre, we compute the least complex path on the underlying road network. First results show differing routes comparing to shortest path based on Dijkstra’s Algorithm.

Floating Car Data (FCD) of taxis provides useful traffic information. Its handling needs effectiv... more Floating Car Data (FCD) of taxis provides useful traffic information. Its handling needs effective analysis steps, including Map Matching (MM) onto road segments. Another challenge is to compute realistic FCD-based travel times in complex urban road networks with different elevation levels. We propose a method for inferring travel time variations in intersections of these networks. Based on intersecting recorded taxi trajectories in Euclidean space, we assign average travel time differences. Additionally, the same technique allows distinguishing between elevated and non-elevated road intersections in complex urban environment. In the end we test and evaluate the method with taxi FCD from Shanghai.

Extended Abstract Tracked movement from numerous observed objects includes often large data size ... more Extended Abstract Tracked movement from numerous observed objects includes often large data size and is difficult to handle, especially in terms of visualization. In the following we describe the possibility of getting more insight into massive movement data. Our inspected data set consists of more than 7000 observed taxis in Shanghai and is referred to as Floating Car Data (FCD). With this term numerous approaches appeared in the last decades facing the problem of how to connect digitized road network with tracked positions of moving objects. The aim is often to improve the modelling of traffic in road networks. Since FCD sets of taxis have often large size not only problems of reasonable processing are appearing but as well advanced ideas of geovisualization. Established interactive traffic maps show one possible solution for the visual inspection. Other approaches use advanced techniques for the detection of interesting patterns, which may be connected with appearing events (e.g. congestion).

Analyzing large amounts of complex movement data requires appropriate visual and analytical metho... more Analyzing large amounts of complex movement data requires appropriate visual and analytical methods. This paper proposes a 2-D star-icon based visualization technique for the visual exploration of multivariate movement events in a space-time cube. To test the proposed method, we derive multivariate events from massive real-world floating car data and visually explore spatio-temporal patterns. The experimental results show that our proposed methods are helpful in identifying interesting locations or functional areas, and assist the understanding of dynamic patterns.

31st Geographical Information Science Research UK (GISRUK) Conference (GISRUK), 2023

The Digital Twin Munich project (DZ-M) aims to depict complex urban environments through the use ... more The Digital Twin Munich project (DZ-M) aims to depict complex urban environments through the use of static and dynamic components, and their semantic relationships. The project focuses on the development of a street network model and urban mobility simulation, utilizing the open source microscopic traffic flow simulation software SUMO. The transport demand is provided by the VISUM model of the city of Munich, and the data structure developed is compatible with standards such as OpenStreetMap, OpenDrive, CityGML, and GTFS. The project also includes the use of physical VRU simulators for data collection purposes, and the integration of these simulations into a 3D VR environment in Unity.

SUMO Conference Proceedings, 2023

Travel demand is an essential input for the creation of traffic models. However, estimating trave... more Travel demand is an essential input for the creation of traffic models. However, estimating travel demand to accurately represent traffic behaviour usually requires the collection of extensive sets of data on traffic behaviour. Traffic counts are a comparably cost effective and reproducible source of information on travel demand. The utilisation of traffic counts to estimate demand is commonly found in the literature as the static and dynamic O-D estimation problem. A variety of approaches have been developed over recent decades to tackle this problem. Usually initial estimates of the O-D matrix are calibrated by utilising traffic counts and considering different assignment models. Other approaches for the estimation of travel demand solely based on traffic measurements can be found in the simulation software SUMO. The present work demonstrates the systematic development of a network model in SUMO in the inner city of Munich. In a sample network the estimation of travel demand through the tools flowrouter and routeSampler is tested by utilising flow measurements from induction loop detectors. The tests delivered unsatisfactory results, which is proven through observations of traffic flows in the resulting simulations as well as comparisons to historic traffic counts. The lack of sufficient detector data and the complexity of the sample network are discussed as the main reasons for the results. It is concluded that the applied tools should be tested in future studies with a more extensive dataset to perform a more comprehensive review of both tools. Therefore, we deliver specific requirements based on the network example of Munich.

SUMO User Conference 2023, 2023

Microscopic traffic flow simulations as tools for enabling detailed insights on traffic efficienc... more Microscopic traffic flow simulations as tools for enabling detailed insights on traffic efficiency and safety gained numerous popularity among transportation researchers, planners and engineers in the first to decades of the 21 st century. By implementing a test bed for simulation scenarios of complex urban transportation infrastructure it is possible to inspect specific effects of introducing small infrastructural changes related to the built environment and to the introduction of advanced traffic control strategies. The possibility of reproducing present problems or the transportation services, such as the ones of public bus services is a key motivation of this work. In this research, we reproduce the road network of the city of Kyoto for observing specific travel patterns of public buses such as the bus bunching phenomena. Therefore, a selection of currently available data sets is used for calibrating a cutout of the Kyoto road network of a relatively large extent. After introducing a method for geodata extraction and conversion, we approach the calibration by introducing virtual detectors representing present inductive loops and make use of historical traffic count records. Additionally, we introduce bus routes partially contributed by volunteer mappers (OSM project). First simulation outcomes show numerous familiar (local knowledge) flow patterns.

DSC 2021 - 20th Driving Simulation & Virtual Reality Conference (DSC 2021), 2021

In this research, we present an interconnected (static) simulator setup for inspecting potential ... more In this research, we present an interconnected (static) simulator setup for inspecting potential communication between two test subjects at an urban static bottleneck, depicted in a virtual environment. The virtual bottleneck is a construction site blocking the right lane and the two test subjects respectively cycle on a bicycle simulator or drive in a driving simulator in the same direction on the same lane one after another (motorist behind cyclist). After they meet in front of the static bottleneck, we intend to create a situation of experienced uncertainty, which starts the process of communication between the two test subjects. Our proof of concept shows several important factors limiting the virtual experience, as related to scenario design, used equipment (VR glasses and monitors), audio signals and visualization.

DSC 2021 - 20th Driving Simulation & Virtual Reality Conference (DSC 2021), 2021

In this research, we estimate the influence of different bicycle infrastructure on the severity o... more In this research, we estimate the influence of different bicycle infrastructure on the severity of motorist-cyclist conflicts via an interconnected simulator study. Our focus is a specific conflict type: motorist is turning at an intersection and the cyclist is going straight, crossing the intersection based on previous evaluations from literature. Additionally, we reason on previously-conducted bicycle simulator studies and adapt specific methodological components of investigation area depiction in VR and scenario definition. In the end, we present four scenarios of a case study based on a signalized intersection in Ingolstadt, Germany, where we inspect motorist-cyclist conflicts in an interconnected simulator environment. After every simulator run both test subjects will be teleported to specific starting positions.

2020 IEEE Intelligent Vehicles Symposium (IV), 2020

This work explains the possible inferable information from a long-term video acquisition with cam... more This work explains the possible inferable information from a long-term video acquisition with cameras installed in close proximity to pedestrian movements with an unobstructed view of the entire intersection. The main goal is detecting implicit and explicit gestures and understanding communication and interactions between different types of road users. After explaining the designs of different gesture classification approaches, we relate the qualitative approach with our classification scheme for the extracted skeletons. To this end, a sequence with selected moving entities is selected and compared with the manually annotated video sequence. Results show the limitations of the automated approach and indicate a level of subjectivity in the manual annotation procedure. Subsequently, we discuss possibilities and restrictions of our approach and reflect on the importance of the specific conditions of video acquisitions. Depending on the field of view and distance between installed video cameras and moving vulnerable road users (VRUs), we are able to define the restrictions of our approach. As a result, we are able to define a selection of suitable applications for our approach.

Sustainability, 2021

Detailed specifications of urban traffic from different perspectives and scales are crucial for u... more Detailed specifications of urban traffic from different perspectives and scales are crucial for understanding and predicting traffic situations from the view of an autonomous vehicle (AV). We suggest a data-driven specification scheme for maneuvers at different design elements of the built infrastructure and focus on urban roundabouts in Germany. Based on real observations, we define classes of maneuvers, interactions and driving strategies for cyclists, pedestrians and motorized vehicles and define a matrix for merging different maneuvers, resulting in more complex interactions. The sequences of these interactions, which partially consist of explicit communications, are extracted from real observations and adapted into microscopic traffic flow simulations. The simulated maneuver sequences are then visualized in 3D environments and experienced by bicycle simulator test subjects. Using trajectory segments (in fictional space) from two conducted simulator studies, we relate the recorded movement patterns of test subjects with observed cyclists in reality.

KN - Journal of Cartography and Geographic Information, 2021

Investigating traffic volume is essential in order to be able to determine the impact of current ... more Investigating traffic volume is essential in order to be able to determine the impact of current and future traffic on road networks. The present study examines the Annual Average Daily Traffic (AADT) and the Heavy Commercial Annual Average Daily Traffic (HCAADT) in the metropolitan area of Minneapolis-St. Paul in 1996 and 2016. In particular, the traffic volume data is visualized both two- and three-dimensionally using various visualisation techniques. Comparisons based on these 2D and 3D visualisations strongly indicate an overall increase in traffic volume from 1996 to 2016. Differences between the increase of AADT and HCAADT data as well as spatially differing patterns could also be identified. The paper documents initial findings on visualizing traffic volumes in a two and three-dimensional way.

Sustainability, 2021

This research addresses the phenomenon of varying bicycle friendliness in urban areas and conside... more This research addresses the phenomenon of varying bicycle friendliness in urban areas and considers which elements are necessary to design a city in a bike-friendly manner. It aims to provide a deeper understanding of the term bikeability, in relation to the established term walkability, and methods to create models that measure the degree of bikeability in urban areas. We explain different established models and compare their computational bases. The focus of this paper is to define a computational methodology built within a Geographic Information System (GIS) and a subsequent evaluation based on an investigation area in Munich, Germany. We introduce a bikeability index for specific investigation areas and geovisualize four selected factors of this index. The resulting map views show the road segments of the traffic network where the conditions for biking are adequate, but also those segments which need to be improved.

Sustainability, 2021

Car-following models are used in microscopic simulation tools to calculate the longitudinal accel... more Car-following models are used in microscopic simulation tools to calculate the longitudinal acceleration of a vehicle based on the speed and position of a leading vehicle in the same lane. Bicycle traffic is usually included in microscopic traffic simulations by adjusting and calibrating behavior models developed for motor vehicle traffic. However, very little work has been carried out to examine the following behavior of bicyclists, calibrate following models to fit this observed behavior, and determine the validity of these calibrated models. In this paper, microscopic trajectory data collected in a bicycle simulator study are used to estimate the following parameters of the psycho-physical Wiedemann 99 car-following model implemented in PTV Vissim. The Wiedemann 99 model is selected due to the larger number of assessable parameters and the greater possibility to calibrate the model to fit observed behavior. The calibrated model is validated using the indicator average queue dissipation time at a traffic light on the facilities ranging in width between 1.5 m to 2.5 m. Results show that the parameter set derived from the microscopic trajectory data creates more realistic simulated bicycle traffic than a suggested parameter set. However, it was not possible to achieve the large variation in average queue dissipation times that was observed in the field with either of the tested parameter sets.

Abstracts of the ICA , 2019

Learning to drive a car is not easy. Therefore, in many countries, driving schools offer an educa... more Learning to drive a car is not easy. Therefore, in many countries, driving schools offer an education of how to drive a car. This is taught on a theoretical and practical level. Once a driving student has learned how to handle a car in real traffic, he / she will take a driving test exam. In Germany, for example, an authorized driving examiner telling the students to follow their instructions conducts the practical exam. Thereby the driving examiner guides the student to different situation (for example taking a highway, crossing a complicated intersection, backward parking etc.). The examiner selects the route according to the criteria set out in the test guidelines and incorporates the road and traffic conditions in his choice. The driver test guidelines include basic driving tasks (parking, danger braking, etc.), a route within closed villages, a route outside built-up areas and / or motorway sections and afterwards a feedback on student performance. The test is set for a period of 45 minutes (for driving class B). Currently mobile devices, which are able to record a number of parameters (location, speed etc.) are rarely used in these driving examinations. Additionally, the route the driving instructor follows can be somewhat arbitrary. Utilizing routing systems in these driving examinations may assist the driving examiner and may help to make the examination more transparent. How can utilize routing algorithms to support driving examinations? In general routing algorithms offer a number of different parameters that may provide users with different type of routes, including the shortest, fastest, safest, most beautiful, least fuel/energy consumption (Ranacher et al. 2016), male/female (Häusler et al. 2010), easiest (Duckham and Kulik 2003) or most difficult (to drive) route (Krisp, Keler, and Karrais 2014). As Krisp & Keler (2015) suggest, that may also include the 'most difficult to drive route', which might be useful for driver training purposes. Previous research (Krisp and Keler 2015) has investigated what is an "easy to drive" route? and "what are the traffic situations that could be avoided for inexperienced drivers and/or driving beginners?". A number of commercial vendors offer products that include pre-programmed routes to help driving students to "learn" particular situations. We investigate selected parameters relevant for a driving test, in particular complicated crossings. This requires examinations on specific situations and the complexity of the road infrastructure. In a wider context, we aim to provide suggestions for a routing system that will help driving instructors and driving examiners, use standardized routes and thereby make driving examinations more transparent. Initial research in this context has been conducted an online questionnaire at the University of Augsburg. This questionnaire includes about seventy-five participants, which are mainly students. About 89% do have a driving license longer those two years. About 25% do not use a car on a regular base. Within this online questionnaire, sixteen driving situations are described. The participants rate each driving situation by agreeing or disagreeing to statements on these situations. For example, to the statement "I have problems with complicated crossings", about 43 % of participants "strongly agreed" or "agreed". The questionnaire shows that the basis for what is in easy or difficult to drive route seems to vary, based on the individual driver. A starting point to investigate, within the large number of driving situations, are "complicated crossings" (Krisp and Keler 2015) and to consider interactions to vulnerable road users. Figures 1 illustrates the challenge of defining complicated crossings based on static measures and dynamic measures. Static measures include the number of nodes that can be extracted from a road database, based on Krisp & Keler (Krisp and Keler 2015). Dynamic measures, like the traffic density or interaction points (between the traffic participants) at urban crossings are acquired via analysis of extracted video trajectories from cameras. Figure 1. Illustration showing the challenge of defining complicated crossings based on static measures (based on nodes derived from Open-Street Map) and dynamic measures (based on near real-time traffic cameras)

Traffic congestion in urban environments has severe influences on the daily life of people. Due t... more Traffic congestion in urban environments has severe influences on the daily life of people. Due to typical recurrent mobility patterns of commuters and transport fleets, we can detect traffic congestion events on selected hours of the day, so called rush hours. Besides the mentioned recurrent traffic congestion, there are non-recurrent events that may be caused by accidents or newly established building sites. We want to inspect this appearance using a massive Floating Taxi Data (FTD) set of Shanghai from 2007. We introduce a simple method for detecting and extracting congestion events on selected rush hours and for distinguishing between their recurrence and non-recurrence. By preselecting of similar velocity and driving direction values of the nearby situated FTD points, we provide the first part for the Shared Nearest Neighbour (SNN) clustering method, which follows with a density-based clustering. After the definition of our traffic congestion clusters, we try to connect ongoing events by querying individual taxi identifications. The detected events are then represented by polylines that connect density core points of the clusters. By comparing the shapes of congestion propagation polylines of different days, we try to classify recurrent congestion events that follow similar patterns. In the end, we reason on the reasonability of our method and mention further steps of its extension.

Mobility in urban environments is complex due to numerous interacting components , with many of t... more Mobility in urban environments is complex due to numerous interacting components , with many of those that are difficult to specify. Examples include the presence of transport hubs, which connect different modes of transport, public and private. The properties of these locations include a temporally changing surface area of operational function that is heavily dependent on the complex and dynamically changing human mobility. Besides public transport services with specified stations, there are taxi services that can be associated with established transport hubs in the way of assigning spatiotemporal service hotspots. This work proposes a technique for relating taxi trip origins and destination hotspots for gaining knowledge on the spatial uncertainties of transport hubs, more precisely their movements within specific times. The case study in NYC focuses on the services of yellow taxi and boro taxi trip data on Saturdays in June 2015. The outcomes of applying the technique are matter of further investigation of spatial uncertainty perception, representation, and visualization. In the stages of the approach, the outcomes of transport hub movements are related with more general functional transport regions resulting from NYC public transport services.

Detecting and describing movement of vehicles in established transportation infrastructures is an... more Detecting and describing movement of vehicles in established transportation infrastructures is an important task. It helps to predict periodical traffic patterns for optimizing traffic regulations and extending the functions of established transportation infrastructures. The detection of traffic patterns consists not only of analyses of arrangement patterns of multiple vehicle trajectories, but also of the inspection of the embedded geographical context. In this paper, we introduce a method for intersecting vehicle trajectories and extracting their intersection points for selected rush hours in urban environments. Those vehicle trajectory intersection points (TIP) are frequently visited locations within urban road networks and are subsequently formed into density-connected clusters, which are then represented as polygons. For representing temporal variations of the created polygons, we enrich these with vehicle trajectories of other times of the day and additional road network information. In a case study, we test our approach on massive taxi Floating Car Data (FCD) from Shanghai and road network data from the OpenStreetMap (OSM) project. The first test results show strong correlations with periodical traffic events in Shanghai. Based on these results, we reason out the usefulness of polygons representing frequently visited locations for analyses in urban planning and traffic engineering.

Daily mobility patterns in highly populated urban environments rely on a well-functioning effecti... more Daily mobility patterns in highly populated urban environments rely on a well-functioning effective road network. Nevertheless, traffic bottlenecks are typical for urban environments with periodic traffic congestion. In this paper, we focus on the investigation of how traffic congestion is related with complicated crossings. First, we select an approach for the classification of the complexity of road partitions and the derivation of complicated crossings based on geodata from Open-StreetMap (OSM). Second, we calculate traffic congestions using Floating Taxi Data (FTD) from Shanghai in 2007. Then, we develop a matching technique to link the congestion and complicated crossings, and subsequently define the concept of traffic bottlenecks represented by polygons. The bottlenecks indicate locations where the transportation infrastructure is complex and traffic congestion appears periodically. Finally, we select suitable cartographic representations of traffic bottlenecks in potential thematic vehicle traffic maps.

Recent services for car navigation include selections for computing the shortest, fastest or most... more Recent services for car navigation include selections for computing the shortest, fastest or most economic route between origin and destination. Our idea is to compute the least complex route, which might be challenging, since there is no consistent definition of complexity. We focus on the complexity of road intersections, which is experienced by vehicle drivers with the turning motion itself in selected crossroads. Therefore, we define weights for different turning possibilities. In a case study in Le Havre, we compute the least complex path on the underlying road network. First results show differing routes comparing to shortest path based on Dijkstra’s Algorithm.

Floating Car Data (FCD) of taxis provides useful traffic information. Its handling needs effectiv... more Floating Car Data (FCD) of taxis provides useful traffic information. Its handling needs effective analysis steps, including Map Matching (MM) onto road segments. Another challenge is to compute realistic FCD-based travel times in complex urban road networks with different elevation levels. We propose a method for inferring travel time variations in intersections of these networks. Based on intersecting recorded taxi trajectories in Euclidean space, we assign average travel time differences. Additionally, the same technique allows distinguishing between elevated and non-elevated road intersections in complex urban environment. In the end we test and evaluate the method with taxi FCD from Shanghai.

Extended Abstract Tracked movement from numerous observed objects includes often large data size ... more Extended Abstract Tracked movement from numerous observed objects includes often large data size and is difficult to handle, especially in terms of visualization. In the following we describe the possibility of getting more insight into massive movement data. Our inspected data set consists of more than 7000 observed taxis in Shanghai and is referred to as Floating Car Data (FCD). With this term numerous approaches appeared in the last decades facing the problem of how to connect digitized road network with tracked positions of moving objects. The aim is often to improve the modelling of traffic in road networks. Since FCD sets of taxis have often large size not only problems of reasonable processing are appearing but as well advanced ideas of geovisualization. Established interactive traffic maps show one possible solution for the visual inspection. Other approaches use advanced techniques for the detection of interesting patterns, which may be connected with appearing events (e.g. congestion).

Analyzing large amounts of complex movement data requires appropriate visual and analytical metho... more Analyzing large amounts of complex movement data requires appropriate visual and analytical methods. This paper proposes a 2-D star-icon based visualization technique for the visual exploration of multivariate movement events in a space-time cube. To test the proposed method, we derive multivariate events from massive real-world floating car data and visually explore spatio-temporal patterns. The experimental results show that our proposed methods are helpful in identifying interesting locations or functional areas, and assist the understanding of dynamic patterns.