Public Participation GIS for sustainable urban mobility planning: methods, applications and challenges

Sustainable mobility planning is a new approach to planning, and as such it requires new methods of public participation, data collection and data aggregation. In the article we present an overview of Public Participation GIS (PPGIS) methods with potential use in sustainable urban mobility planning. We present the methods using examples from two recent case studies conducted in Polish cities of Poznań and Łodź. Sustainable urban mobility planning is a cyclical process, and each stage has different data and participatory requirements. Consequently, we situate the PPGIS methods in appropriate stages of planning, based on potential benefits they may bring into the planning process. We discuss key issues related to participant recruitment and provide guidelines for planners interested in implementing methods presented in the paper. The article outlines future research directions stressing the need for systematic case study evaluation

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Vehicle Navigation Service Based on Real-Time Traffic Information

GNSS-assisted vehicle navigation services are nowadays very common in most of the developed countries. However, most of those services are either delivered through proprietary technologies, or fall short in flexibility because of the limited capability to couple road information with real-time traffic information. This paper presents the motivations and a brief summary of a vehicle navigation service based on real-time traffic information, delivered through an open protocol that is currently under standardization in the Open Mobile Alliance forum

Estimation of indirect cost and evaluation of protective measures for infrastructure vulnerability: A case study on the transalpine transport corridor

Infrastructure vulnerability is a topic of rising interest in the scientific literature for both the general increase of unexpected events and the strategic importance of certain links. Protective investments are extremely costly and risks are distributed in space and time which poses important decision problems to the public sector decision makers. In an economic prospective, the evaluation of infrastructure vulnerability is oriented on the estimation of direct and indirect costs of hazards. Although the estimation of direct costs is straightforward, the evaluation of indirect cost involves factors non-directly observable making the approximation a difficult issue. This paper provides an estimate of the indirect costs caused by a two weeks closure of the north-south Gotthard road corridor, one of the most important infrastructure links in Europe, and implements a cost-benefit analysis tool that allows the evaluation of measures ensuring a full protection along the corridor. The identification of the indirect cost relies on the generalized cost estimation, which parameters come from two stated preference experiments, the first based on actual condition whereas the second assumes a road closure. The procedure outlined in this paper proposes a methodology aimed to identify and quantify the economic vulnerability associated with a road transport infrastructure and, to evaluate the economic and social efficiency of a vulnerability reduction by the consideration of protective measures.infrastructure vulnerability, choice experiment, cost-benefit analysis, freight transport

Modelling trust in semantic web applications

This paper examines some of the barriers to the adoption of car-sharing, termed carpooling in the US, and develops a framework for trusted recommendations. The framework is established on a semantic modelling approach putting forward its suitability to resolving adoption barriers while also highlighting the characteristics of trust that can be exploited. Identification is made of potential vocabularies, ontologies and public social networks which can be used as the basis for deriving direct and indirect trust values in an implementation

Study on k-shortest paths with behavioral impedance domain from the intermodal public transportation system perspective

Behavioral impedance domain consists of a theory on route planning for pedestrians, within which constraint management is considered. The goal of this paper is to present the k-shortest path model using the behavioral impedance approach. After the mathematical model building, optimization problem and resolution problem by a behavioral impedance algorithm, it is discussed how behavioral impedance cost function is embedded in the k-shortest path model. From the pedestrian's route planning perspective, the behavioral impedance cost function could be used to calculate best subjective paths in the objective way.Postprint (published version

Hiking Trip Selection Based On Reachability By Public Transport

Smart cities should enable the citizens to utilize available ressources. One of the goals is the reduction of individual motorized traffic. However, many citizens still use cars to get to the location of an ourtdoor activity. As a concrete example we use hiking trips and identify those that can be reached by public transport. The result is a map (and a corresponding GIS data set) showing the hiking locations for a single day hiking trip. The concept can be used for various other applications although there are still open questions, e.g., what part of the answer can be precomputed and what should be determined on demand

Multi-Paradigm Reasoning for Access to Heterogeneous GIS

Accessing and querying geographical data in a uniform way has become easier in recent years. Emerging standards like WFS turn the web into a geospatial web services enabled place. Mediation architectures like VirGIS overcome syntactical and semantical heterogeneity between several distributed sources. On mobile devices, however, this kind of solution is not suitable, due to limitations, mostly regarding bandwidth, computation power, and available storage space. The aim of this paper is to present a solution for providing powerful reasoning mechanisms accessible from mobile applications and involving data from several heterogeneous sources. By adapting contents to time and location, mobile web information systems can not only increase the value and suitability of the service itself, but can substantially reduce the amount of data delivered to users. Because many problems pertain to infrastructures and transportation in general and to way finding in particular, one cornerstone of the architecture is higher level reasoning on graph networks with the Multi-Paradigm Location Language MPLL. A mediation architecture is used as a “graph provider” in order to transfer the load of computation to the best suited component – graph construction and transformation for example being heavy on resources. Reasoning in general can be conducted either near the “source” or near the end user, depending on the specific use case. The concepts underlying the proposal described in this paper are illustrated by a typical and concrete scenario for web applications