GeoCAM: A geovisual analytics workspace to contextualize and interpret statements about movement

This article focuses on integrating computational and visual methods in a system that supports analysts to identify extract map and relate linguistic accounts of movement. We address two objectives: (1) build the conceptual theoretical and empirical framework needed to represent and interpret human-generated directions; and (2) design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled computational methods to identify documents containing movement statements and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract interpret and map geographic movement references in context. Additionally analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface an analyst can explore the results provide feedback to improve those results pose queries against a database of route directions and interactively represent the route on a map

Shortest path or anchor-based route choice: a large-scale empirical analysis of minicab routing in London

Understanding and modelling route choice behaviour is central to predicting the formation and propagation of urban road congestion. Yet within conventional literature disagreements persist around the nature of route choice behaviour, and how it should be modelled. In this paper, both the shortest path and anchor-based perspectives on route choice behaviour are explored through an empirical analysis of nearly 700,000 minicab routes across London, United Kingdom. In the first set of analyses, the degree of similarity between observed routes and possible shortest paths is established. Shortest paths demonstrate poor performance in predicting both observed route choice and characteristics. The second stage of analysis explores the influence of specific urban features, named anchors, in route choice. These analyses show that certain features attract more route choices than would be expected were individuals choosing route based on cost minimisation alone. Instead, the results indicate that major urban features form the basis of route choice planning – being selected disproportionately more often, and causing asymmetry in route choice volumes by direction of travel. At a finer scale, decisions made at minor road features are furthermore demonstrated to influence routing patterns. The results indicate a need to revisit the basis of how routes are modelled, shifting from the shortest path perspective to a mechanism structured around urban features. In concluding, the main trends are synthesised within an initial framework for route choice modelling, and presents potential extensions of this research

Modelling shared space users via rule-based social force model

The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design and achieve solutions for optimal design features before implementation. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents' respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since vehicle movements are not as flexible as pedestrian movements, velocity angle constraints are included for vehicles. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs

A GIS-based methodological framework to identify superficial water sources and their corresponding conduction paths for gravity-driven irrigation systems in developing countries

The limited availability of fresh water is a major constraint to agricultural productivity and livelihood security in many developing countries. Within the coming decades, smallholder farmers in drought-prone areas are expected to be increasingly confronted with local water scarcity problems, but their access to technological knowledge and financial resources to cope with these problems is often limited. In this article, we present a methodological framework that allows for identifying, in a short period of time, suitable and superficial water sources, and cost-effective water transportation routes for the provisioning of gravity-driven irrigation systems. As an implementation of the framework, we present the automated and extensible geospatial toolset named “AGRI’’, and elaborate a case study in Western Honduras, where the methodology and toolset were applied to provide assistance to field technicians in the process of identifying water intake sites and transportation routes. The case study results show that 28 % of the water intake sites previously identified by technicians (without the support of AGRI) were found to be not feasible for gravity-driven irrigation. On the other hand, for the feasible water intake sites, AGRI was able to provide viable and shorter water transportation routes to farms in 70 % of the cases. Furthermore, AGRI was able to provide alternative feasible water intake sites for all considered farms, with correspondingly viable water transportation routes for 74 % of them. These results demonstrate AGRI’s potential to reduce time, costs and risk of failure associated with the development of low-cost irrigation systems, which becomes increasingly needed to support the livelihoods of some of the world’s most vulnerable populations

HPC Enhanced Large Urban Area Evacuation Simulations with Vision based Autonomously Navigating Multi Agents

AbstractAn evacuation simulation code based on Multi Agent Systems (MAS), with moderately complex agents in 2D grid envi- ronments, is developed. The main objective of this code is to estimate the effectiveness of the measures taken to smoothen and speedup the evacuation process of a large urban area, in time critical events like tsunami. A vision based autonomous navigation algorithm, which enables the agents to move through an urban environment and reach a far visible destination, is implemented. This simple algorithm enables a visitor agent to navigate through urban area and reach a destination which is several kilometers away. The navigation algorithm is verified comparing the simulated evacuation time and the paths taken by individual agents with those of theoretical. Further, a parallel computing extension is developed for studying mass evacuation of large areas; vision based autonomous navigation is computationally intensive. Several strategies like communication hiding, dynamic load balancing, etc. are implemented to attain high parallel scalability. Preliminary tests on the K-computer attained strong scalability above 94% at least up to 2048 CPU cores, with 2 million agents

Scalable and Vision Free User Interface Approaches for Indoor Navigation Systems for the Visually Impaired

This thesis introduces scalable and vision free user interface approaches for indoor navigation systems for the visually impaired. Using an Android Smartphone that runs the indoor navigation system – Percept Application with accessibility features, the blind user obtains navigation instructions generated automatically by our navigation generation algorithm to the chosen destination when touching specific landmarks tagged with Near Field Communication tags. This thesis also introduces an Orientation & Mobility Survey Tool that can help O&M Instructors survey the building and deploy such indoor navigation system. The system was deployed and tested in a large building at the University of Massachusetts at Amherst

Automatic Extraction of Destinations, Origins and Route Parts from Human Generated Route Directions

Researchers from the cognitive and spatial sciences are studying text descriptions of movement patterns in order to examine how humans communicate and understand spatial information. In particular, route directions offer a rich source of information on how cognitive systems conceptualize movement patterns by segmenting them into meaningful parts. Route directions are composed using a plethora of cognitive spatial organization principles: changing levels of granularity, hierarchical organization, incorporation of cognitively and perceptually salient elements, and so forth. Identifying such information in text documents automatically is crucial for enabling machine-understanding of human spatial language. The benefits are: a) creating opportunities for large-scale studies of human linguistic behavior; b) extracting and georeferencing salient entities (landmarks) that are used by human route direction providers; c) developing methods to translate route directions to sketches and maps; and d) enabling queries on large corpora of crawled/analyzed movement data. In this paper, we introduce our approach and implementations that bring us closer to the goal of automatically processing linguistic route directions. We report on research directed at one part of the larger problem, that is, extracting the three most critical parts of route directions and movement patterns in general: origin, destination, and route parts. We use machine-learning based algorithms to extract these parts of routes, including, for example, destination names and types. We prove the effectiveness of our approach in several experiments using hand-tagged corpora

Tourism and the smartphone app: capabilities, emerging practice and scope in the travel domain.

Based on its advanced computing capabilities and ubiquity, the smartphone has rapidly been adopted as a tourism travel tool.With a growing number of users and a wide varietyof applications emerging, the smartphone is fundamentally altering our current use and understanding of the transport network and tourism travel. Based on a review of smartphone apps, this article evaluates the current functionalities used in the domestic tourism travel domain and highlights where the next major developments lie. Then, at a more conceptual level, the article analyses how the smartphone mediates tourism travel and the role it might play in more collaborative and dynamic travel decisions to facilitate sustainable travel. Some emerging research challenges are discussed