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.

In this work, we present a routing approach avoiding relatively dangerous areas within a city. The information of how dangerous some urban areas are is derived using volunteered geographic information (VGI), governmental open data for detecting properties and functionalities of the urban infrastructure and historical crime data from police departments for detecting crime hot spots. Therefore, we present the basics of crime mapping and analysis with GIS, the practical use of VGI for routing and describe our contribution within the field of routing solutions. Afterwards, we explore our test data in detail. For the practical use, we simplify all the urban infrastructure information and propose a safety index, which represents the relative safety in the investigation area. Additionally, historical crime hot spots are detected and used as routing obstacles. The arcs in the road network are weighted by our safety index and the historical crime hot spots are introduced as obstacle polygons. We test our safety-aware routing design on Los Angeles (LA) and assume its use during night times. In this regard, from two relatively far away situated origin and destination points, we calculate the least dangerous path and compare it with the calculated shortest path. Vehicle drivers without knowledge about the dangerous areas in the city may use the least dangerous path, which is based on our calculated safety index. Finally, we discuss the effectiveness of our method and consider further extensions using freely available geodata.

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.

Personalized navigation and way-finding are prominent research areas of location-based service LBSs. This includes innovative concepts for car navigation. Within this paper, we investigate the idea of providing drivers a routing suggestion which avoids ‘complicated crossings’ in urban areas. Inexperienced drivers include persons who have a driver’s license but, for whatever reason, feel uncomfortable to drive in a city environment. Situations where the inexperienced driver has to depend on a navigation device and reach a destination in an unfamiliar territory may be difficult. Preferences of inexperienced drivers are investigated. ‘Fears’ include driving into ‘complicated crossings’. Therefore, the definition and spatial characteristics of ‘complicated crossings’ are investigated. We use OpenStreetMap as a road dataset for the routing network. Based on the topological characteristics of the dataset, measured by the number of nodes, we identify crossings that are ‘complicated’. The user can choose to compute an alternative route that avoids these complicated crossings. This methodology is one step in building a full ‘inexperienced drivers’ routing system, which includes additional preferences from the user group, for example, as avoiding left turns where no traffic light is present.

The ongoing increase of bicycle traffic in urban areas forces transport authorities to reconsider the space allocation for different transport modes. Transport policies favor the introduction of high-quality bicycle infrastructure along urban corridors to improve the traffic quality and safety for bicyclists but more importantly to increase the attractiveness of bicycling and over vehicular modes. Especially in urban areas with an already established high and steadily increasing share of bicyclists, the introduction of bicycle highways is considered to further alleviate saturated interurban public transport and motor vehicle connections and increase the average traveled distance by non-motorized modes. Due to the expensive implementation costs and the space restrictions in already built-up urban environments, there should be an extensive planning phase for defining the expected changes in traffic efficiency and safety. However, the effects of urban bicycle highways on traffic performance metrics of bicyclists as well as other road users are not thoroughly studied. This paper aims to quantify and assess the potential effects of urban bicycle highway on road users. The study considers a possible inner-city pilot route in the city of Munich, where the present bicycle infrastructure is planned to be upgraded to a bicycle highway. A simulation model is designed using traffic data from field observations and future estimates for the traffic composition. Through microscopic traffic simulation, the potential effects of the introduced infrastructure on road users are determined for different study scenarios. Results show that traffic quality thresholds for bicycle highways, as defined in official guidelines, can only be fulfilled through the implementation of special bicycle traffic control measures such as bicycle coordination or bicycle passage time extension. Finally, unidirectional bicycle highways together with bicycle passage time extension provided the best overall traffic performance for bicycle traffic and motor vehicle traffic.

Urban environments often imply complex transportation infrastructures with manifold different traffic participant using various modes of transport. These traffic participants interact with each other in different ways, often in specific patterns of communication. One option for understanding these interactions may come from microscopic traffic flow simulations. Simulated traffic on modelled urban transportation infrastructures may deliver insights on general traffic-related problems or show specific locations of high risk of accidents or of low traffic quality. Besides having a general view on microscopic traffic flow simulation results, we propose one option for experiencing these simulations from a first-person perspective visualization as one interacting traffic participant on a non-moving physical bicycle. We introduce a procedure for implementing a bicycle simulator for testing various scenarios in three-dimensional environments. By including individual realtime bicycle movements of test subjects into ongoing traffic simulations, we are able to derive individual behavioral strategies to cope with the modelled transportation infrastructure and with simulated vehicle drivers, bicyclists and pedestrians from the point of view of an urban bicyclist. We aim to introduce a novel technique for (1) analyzing present problems of traffic and built infrastructural elements, and, (2) inspecting planned scenarios with variations in traffic compositions (participants and modes) and built infrastructure (inclusion of new design elements). One first test scenario is implemented for gaining first insights on the usefulness of the presented device.