Hartwig H. Hochmair

Influence of estimation errors on wayfinding-decisions in unknownstreet networks – analyzing the least-angle strategy

The least-angle strategy is a common wayfinding method that can be applied in unknown environments if the target direction is known. The strategy is based on the navigators heuristic to select the street segment at an intersection which is most in line with the target direction. To use this strategy, the navigator needs to know the angles between the target direction and the street segments leading out from the intersection. If the direct view to the target is blocked and the target vector cannot be perceived, the target direction that is needed for the decision process is based on the agents believed position and orientation (estimated through path integration). The agents believed position and target direction are distorted by human errors in estimation of distances and directions, mainly affecting the path integration process. In this paper we examine how human estimation errors of distance and rotation influence the decision behavior in the wayfinding process in an unknown street environment. To demonstrate the geometrical consequences for a specific test case, we use a simulated software agent which navigates in a simulated street environment.

Assessing the Effect of Data Imports on the Completeness of OpenStreetMap – A United States Case Study

The assessment of OpenStreetMap (OSM) data quality has become an interdisciplinary research area over the recent years. The question of whether the OSM road network should be updated through periodic data imports from public domain data, or whether the currency of OSM data should rather rely on more traditional data collection efforts by active contributors, has led to perpetual debates within the OSM community. A US Census TIGER/Line 2005 import into OSM was accomplished in early 2008, which generated a road network foundation for the active community members in the US. In this study we perform a longitudinal analysis of road data for the US by comparing the development of OSM and TIGER/Line data since the initial TIGER/Line import. The analysis is performed for the 50 US states and the District of Columbia, and 70 Urbanized Areas. In almost all tested states and Urbanized Areas, OSM misses roads for motorized traffic when compared with TIGER/Line street data, while significant contri- butions could be observed in pedestrian related network data in OSM compared with corresponding TIGER/Line data. We conclude that the quality of OSM road data could be improved through new OSM editor tools allowing contributors to trace current TIGER/Line data.

Comparative Study of Pedestrian Accessibility to Transit Stations Using Free and Proprietary Network Data

Availability of a transit service is a key factor in a travelers choice of transportation mode. Transit service is a realistic option only if the service is available at or near locations when a person plans to travel. Whereas various measures exist for transit availability such as service frequency, the focus of this study was on the spatial aspect of pedestrian accessibility to transit stations, that is, on service coverage. Service areas are commonly used to visualize accessibility for pedestrians to transit systems and to analyze the potential ridership. Because the service area for a station is defined over the maximum network walking distance from a transit station, a complete street network that includes pedestrian segments, that is, shortcuts, is highly important for a realistic assessment of service areas. Whereas most proprietary geodata providers concentrate solely on car-related geodata, public domain street data and volunteered geographic information, such as OpenStreetMap, provide a potential valuable source for pedestrian data. The authors compared the amount of pedestrian-related data between freely available sources (OpenStreetMap or TIGER or both) and proprietary providers (Tele Atlas or NAVTEQ or both). The effect on modeling transit accessibility for pedestrians was analyzed for five U.S. and four German cities, and differences between these two countries were identified.

Towards a Classification of Route Selection Criteria for Route Planning Tools

Route planners are tools that support the navigator in selecting the best route between two locations. Solving a route choice problem involves sorting and ranking of alternatives according to underlying evaluation criteria and decision rules. Using an appropriate classification of route selection criteria in the user interface is an important ingredient for user friendly route planners. The paper presents a method for assessing a hierarchical structure of route selection criteria for bicycle route planning tasks along with data from two empirical studies. The first study investigates route selection criteria that are relevant for bicycle navigation in urban environments. The second study reveals preferred classification schemata for these criteria. The presented methodology can be adopted for other transportation domains, such as car or pedestrian navigation.

Positional accuracy analysis of Flickr and Panoramio images for selected world regions

Flickr and Panoramio are fast-growing photo-sharing services that contain millions of geotagged images contributed by Web users from all over the world. This study analyses the positional accuracy of 1433 images for 45 areas in four selected world regions by comparing the geotagged position of photos to the manually corrected camera position based on the image content. The analysis reveals a better positional accuracy for Panoramio than for Flickr images, and some effects of image category and world region on positional accuracy. These findings can be helpful when considering Flickr and Panoramio images as data sources for future geo-applications and services.

A Conceptual Model for Analyzing Contribution Patterns in the Context of VGI

The chapter proposes a conceptual model as foundation for analyzing user contributions in the context of VGI. The conceptual model is based on a set of action and domain concepts, which are combined to a task-model describing typical tasks of volunteered geographic information contribution. As a proof-of-concept, the model is applied to two sample data sets that are extracted from the OpenStreetMap (OSM) change history. OSM data samples provide a proof-of-concept concerning the applicability of the model for crowd activity analysis. The resulting “contribution graph”, which is a graph-like structure of linked editing actions, can be used as foundation for analyzing complex contribution patterns.

Network structure and travel time perception.

The purpose of this research is to test the systematic variation in the perception of travel time among travelers and relate the variation to the underlying street network structure. Travel survey data from the Twin Cities metropolitan area (which includes the cities of Minneapolis and St. Paul) is used for the analysis. Travelers are classified into two groups based on the ratio of perceived and estimated commute travel time. The measures of network structure are estimated using the street network along the identified commute route. T-test comparisons are conducted to identify statistically significant differences in estimated network measures between the two traveler groups. The combined effect of these estimated network measures on travel time is then analyzed using regression models. The results from the t-test and regression analyses confirm the influence of the underlying network structure on the perception of travel time.

Using Free and Proprietary Data to Compare Shortest-Path Lengths for Effective Pedestrian Routing in Street Networks

Ubiquitous mobile devices, such as smartphones, led to an increased popularity of pedestrian-related routing applications over the past few years. Because pedestrians typically aim to minimize their walking distance, especially in nonrecreational and multimodal trips, pedestrian routing systems will be fully used only if they can find the correct shortest path and thus help to avoid unnecessary detours. The standard equipment of car navigation systems based on the Global Positioning System several years ago led to the availability of accurate street network data for car-based routing applications. However, pedestrian routing applications should consider pedestrian-related network segments besides those used by motorized traffic, including footpaths and pedestrian bridges. The authors of this paper performed a shortest-path analysis of pedestrian routes for cities in Germany and the United States. For a set of 1,000 randomly generated origin–destination pairs, the authors compared the lengths of pedestrian routes that were computed by different freely available network sources, such as OpenStreetMap and TIGER/Line data, and proprietary data sets, such as TomTom, NAVTEQ, and ATKIS. The results showed that freely available data sources such as OpenStreetMap provided a relatively comprehensive option for cities in which commercial pedestrian data sets were not yet available.

Network Structure and Spatial Separation

This research aims to identify the role of network architecture in influencing individual travel behavior using travel survey data from Minneapolis-Saint Paul and Florida (Fort Lauderdale and Miami). Various measures of network structure, compiled from existing sources, are used to quantify roadway networks, and to capture the arrangement and connectivity of nodes and links in the networks and the spatial variations that exist among and within networks. The regression models show that travel behavior is correlated with network design.

Assessing the Completeness of Bicycle Trail and Lane Features in OpenStreetMap for the United States

This article assesses the completeness of bicycle trail and on-street lane features in OpenStreetMap (OSM). Comparing OSM cycling features with reference data from local planning agencies for selected US Urbanized Areas shows that OSM bicycle trails tend to be more completely mapped than bicycle lanes. Manual evaluation of mapped cycling features in OSM and Google Maps for selected test areas within the Central Business Districts of Portland (OR) and Miami (FL) through comparison with governmental datasets, satellite imagery, and Google Street View, shows that the Bicycle layer in Google Maps can help to identify some missing or erroneously mapped OSM cycling links. However, Google Maps was also found to have some gaps in its data layers, suggesting that consultation of current trail and lane data from local planning authorities, if available, should be considered as an additional data source for bicycle related planning projects.