Győző Gidófalvi

• PhD
• Professor (Associate) at KTH Royal Institute of Technology

To better understand the interactions between physical built environment conditions and one’s well-being, we created a passive data collector for travellers and made the first step towards an explanatory model based on psychophysiological relations. By measuring biometric information from select trial participants we showed how different controlled...

Travel surveys can uncover information regarding travel behaviour, needs, and more. Collected information is utilised to make choices when reorganising or planning built environments. Over the years, methods for conducting travel surveys have changed from interviews and forms to automated travel diaries in order to monitor trips made by travellers....

Detecting movement patterns with complicated spatial or temporal characteristics is a challenge. The past decade has witnessed the success of deep learning in processing image, voice and text data. However, its application in movement pattern detection is not fully exploited. To address the research gap, this paper develops a deep learning approach...

The increased interest in the automation of travel diary collection, together with the ease of access to new artificial intelligence methods led scientists to explore the prerequisites to the automatic generation of travel diaries. One of the most promising methods for this automation relies on collecting GPS traces of multiple users over a period...

Wide deployment of global positioning system (GPS) sensors has generated a large amount of data with numerous applications in transportation research. Due to the observation error, a map matching (MM) process is commonly performed to infer a path on a road network from a noisy GPS trajectory. The increasing data volume calls for the design of effic...

Large collections of trajectories provide rich insight into movement patterns of the tracked objects. By map matching trajectories to a road network as sequences of road edge IDs, contiguous sequential patterns can be extracted as a certain number of objects traversing a specific path, which provides valuable information in travel demand modeling a...

The growing need of acquiring data that is useful for travel behaviour analysis led scientists to pursue new ways of obtaining travel diaries from large groups of people. The most promising alternative to traditional (declarative) travel diary collection methods are those that rely on collecting trajectories from individuals and then extract travel...

Poster for the ”A Series of Three Case Studies on the Semi-Automation of Activity Travel Diary Generation Using Smartphones” paper presented at the 96th Annual Meeting of the Transportation Research Board,Washington, D.C., January 2017

The wide adoption of location-enabled devices, together with the acceptance of services that leverage (personal) data as payment, allows scientists to push through some of the previous barriers imposed by data insufficiency, ethics and privacy skepticism. The research problems whose study require hard-to-obtain data (e.g. transportation mode detect...

This paper describes the lessons learned from the trial of MEILI, a smartphone based semi-automatic activity-travel diary collector, in Stockholm city, Sweden. The design of the system, together with state-of-the-art improvements of different elements of the tool, are presented before and after the trial to better illustrate the improvements based...

Rooted in the philosophy of point- and segment-based approaches for transportation mode segmentation of trajectories, the measures that researchers have adopted to evaluate the quality of the results (1) are incomparable across approaches, hence slowing the progress in the field and (2) do not provide insight about the quality of the continuous tra...

Congestion is a major problem in most metropolitan areas. Systems that can in a timely manner inform drivers about relevant, current or predicted traffic congestion are paramount for effective traffic management. Without loss of generality, this paper proposes such a system that by adopting a grid-based discretization of space, can flexibly scale t...

Motivated by the high utility and growing availability of Floating Car Data (FCD) streams for traffic congestion modeling and subsequent traffic congestion-related intelligent traffic management tasks, this paper proposes a grid-based, time-inhomogeneous model and method for the detection of congestion from large FCD streams. Furthermore, the paper...

Mobile Ghent '13, Ghent, Belgium; 10/2013

Extended abstract on "Mobility Collector: Battery Conscious Mobile Tracking" submitted to Mobile Ghent '13

The needs for cheaper and less intrusive ways to collect activity-travel diaries led scientist to pursue new technologies, e.g., positioning technologies like GPS. While a fully, reliable and widely accepted automatic activity-travel diary collection system is yet to be developed, scientists have presented systems that automate parts of an activity...

Comparative framework for activity-travel diary collection systems

Despite the availability of mobile positioning technologies and scientists' interests in tracking, modelling and predicting the movements of individuals and populations, these technologies are seldom efficiently used. The continuous changes in mobile positioning and other sensor technologies overburden scientists who are interested in data collecti...

Using "check-in" data gathered from location-based social networks, this paper proposes to measure the similarity of users by considering the geographical and the temporal aspect of their geographical and temporal aspects of their "check-ins". Temporal neighborhood is added to support the time dimension on the basis of the traditional DBSCAN cluste...

Recent technological trends enable modern traffic prediction and management systems in which the analysis and prediction of movements of objects is essential. To this extent the present paper proposes IncCCFR---a novel, incremental approach for managing, mining, and predicting the incrementally evolving trajectories of moving objects. In addition t...

Tracking and analyzing the location of users to understand, to predict (and ultimately control) the movement of humans (or animals) has been an important part of research in different groups such as human geographers, urban planers, behavioral scientists or movement ecologists. Despite the availability of tracking technology, the above research act...

Mobility Collector: Battery Conscious Mobile Tracking

The ability to predict when an individual mobile user will leave his current location and where we will move next enables a myriad of qualitatively different Location-Based Services (LBSes) and applications. To this extent, the present paper proposes a statistical method that explicitly performs these related temporal and spatial prediction tasks i...

The efficient analysis of spatio-temporal data, generated by moving objects, is an essential requirement for intelligent location-based services. Spatio-temporal rules can be found by constructing spatio-temporal baskets, from which traditional association rule mining methods can discover spatio-temporal rules. When the items in the baskets are spa...

Recent advances in Information and Communication Technology (ICT), such as the increasing accuracy of Global Positioning Systems (GPSs) technology and the miniaturisation of wireless communication devices, pave the road for Location-Based Services (LBSs). Among these services, m-advertising is predicted to represent a high-yield revenue stream. In...

Delivering "relevant" advertisements to consumers carrying mobile devices is regarded by many as one of the most promising mobile business opportunities. The relevance of a mobile ad depends on at least two factors: (1) the proximity of the mobile consumer to the product or service being advertised, and (2) the match between the product or service...

The popularity of embedded positioning technologies in mobile devices and the development of mobile communication technology have paved the way for powerful location-based services (LBSs). To make LBSs useful and user- friendly, heavy use is made of context information, including patterns in user location data which are extracted by data mining met...

Recently, random projection, a key dimensionality reduction technique, was successfully incorporated into the learning of mixture of Gaussians with the EM algorithm. In this work we examine the possibility of incorporating random projection to into the learning of other mixture models. More specifically, we use random projection in conjunction with...

This paper shows that short-term stock price movements can be predicted using financial news articles. Given a stock price time series, for each time interval we classify price movement as "up," "down," or (approximately) "unchanged" relative to the volatility of the stock and the change in a relevant index. Each article in a training set of news a...

3 www.motoros.hu: Online Hungarian Forum for Mobility and Transport, gergely.herenyi@motoros.hu ABSTRACT Ride–sharing is a resource efficient mode of personal transportation. While the perceived ben-efits of ride–sharing include reduced travel times, transportation costs, congestion, and carbon emissions, its wide–spread adoption is hindered by a n...