Incentives and gaming environments for changing commuter behaviour

Scientific Conference (2014, September 30)

The project aims to produce a pervasive, gamified system that tries to incentivize mobility behaviour change by offering alternative activities in contrast to usual journeys in such way that it will ... [more ▼]

The project aims to produce a pervasive, gamified system that tries to incentivize mobility behaviour change by offering alternative activities in contrast to usual journeys in such way that it will reduce traffic, emissions and, in the end, save money. The alternatives, for example, such as taking different modes of transport, are incentivised through gamification. In order to develop this pervasive system, we analysed existing mobility patterns of commuters in Luxembourg. The methodology that we developed consists of a questionnaire, a smartphone application and focus group interviews. This paper presents the findings of the questionnaire and how they influence the design of the gamified pervasive application. [less ▲]

Incorporating trip chaining within online demand estimation

in Transportation Research. Part B, Methodological (2019)

Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dy- namic Traffic Assignment (DTA) systems and real-time traffic management. This work in- troduces a novel state-space ... [more ▼]

Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dy- namic Traffic Assignment (DTA) systems and real-time traffic management. This work in- troduces a novel state-space framework to estimate these demand flows in an online con- text. Specifically, we propose to explicitly include trip-chaining behavior within the state- space formulation, which is solved using the well-established Kalman Filtering technique. While existing works already consider structural information and recursive behavior within the online demand estimation problem, this information has been always considered at the OD level. In this study, we introduce this structural information by explicitly representing trip-chaining within the estimation framework. The advantage is twofold. First, all trips belonging to the same tour can be jointly calibrated. Second, given the estimation during a certain time interval, a prediction of the structural deviation over the whole day can be obtained without the need to run additional simulations. The effectiveness of the proposed methodology is demonstrated first on a toy network and then on a large real-world net- work. Results show that the model improves the prediction performance with respect to a conventional Kalman Filtering approach. We also show that, on the basis of the estimation of the morning commute, the model can be used to predict the evening commute without need of running additional simulations. [less ▲]

Indoor positioning and floor plan based ground truth: Can you really click where you are?

in 15th International Conference on Mobile and Ubiquitious Multimedia (MUM-2016) (2016, December)

The increasing accuracy of indoor positioning systems requires an appropriately accurate evaluation, which compares system outputs with the known coordinates of test locations --- the ground truth ... [more ▼]

The increasing accuracy of indoor positioning systems requires an appropriately accurate evaluation, which compares system outputs with the known coordinates of test locations --- the ground truth. Although ground truth data are rarely (if ever) tested, they are traditionally assumed to be perfectly accurate. However, even small errors introduced by inaccurate ground truth need to be taken into account for fair evaluation and comparison between modern high-resolution positioning systems. In this paper we analyze the quality of ground truth data provided by clicking on an interactive floor plan (a method employed by such classical systems as RADAR and Horus). Experimental results show that this method has high precision but low accuracy, and high systematic errors make it unsuitable for evaluation of fine-grained localization systems. [less ▲]

Inference of switched biochemical reaction networks using sparse bayesian learning

in The proceedings of the 7th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) (2014)

This paper proposes an algorithm to identify biochemical reaction networks with time-varying kinetics. We formulate the problem as a nonconvex optimisation problem casted in a sparse Bayesian learning ... [more ▼]

This paper proposes an algorithm to identify biochemical reaction networks with time-varying kinetics. We formulate the problem as a nonconvex optimisation problem casted in a sparse Bayesian learning framework. The nonconvex problem can be efficiently solved using Convex-Concave programming. We test the effectiveness of the method on a simulated example of DNA circuit realising a switched chaotic Lorenz oscillator. [less ▲]

Inferring Urban Mobility and Habits from User Location History

in Transportation Research Procedia (2020, January), 47

Inferring Urban Mobility and Habits from User Location History

in Transportation Research Procedia (2020, January), 47

INFLUENCE OF PISTON DISPLACEMENT ON THE SCAVENGING AND SWIRLING FLOW IN TWO-STROKE DIESEL ENGINES

in 23rd Nordic Seminar on Computational Mechanics NSCM-23 (2010)

The influence of the Design Task Description on the course and outcome of idea generation meetings

in McDonnell, Janet; Lloyd, Peter (Eds.) About: Designing - Analysing Design Meetings (2009)

This paper presents the results of an explorative, comparative protocol analysis of two design meetings that focused on identifying how the style of the Design Task Description influences the course and ... [more ▼]

This paper presents the results of an explorative, comparative protocol analysis of two design meetings that focused on identifying how the style of the Design Task Description influences the course and the outcome of an idea generation meeting. A framework is used to allocate potential influencing factors, including the DTD, and to discuss the various relationships and influences in order to understand the differences in course and outcome of the meetings. The style of the DTD was found to influence the length of the analysis phase and lead to differences in the course of the two idea generation meetings and to a higher idea generation rate. [less ▲]

Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation Using Imaging Data

in Bildverarbeitung für die Medizin 2022 (2022)

Following the deep brain stimulation (DBS) surgery, the stimulation parameters are manually tuned to reduce symptoms. This procedure can be timeconsuming, especially with directional leads. We propose an ... [more ▼]

Following the deep brain stimulation (DBS) surgery, the stimulation parameters are manually tuned to reduce symptoms. This procedure can be timeconsuming, especially with directional leads. We propose an automated methodology to initialise contact configurations using imaging techniques. The goal is to maximise the electric field on the target while minimising the spillover, and the electric field on regions of avoidance. By superposing pre-computed electric fields, we solve the optimisation problem in less than a minute, much more efficient compared to finite element methods. Our method offers a robust and rapid solution, and it is expected to considerably reduce the time required for manual parameter tuning. [less ▲]

An integrated approach to adaptive anticipatory traffic control and parameter estimation

in Proceedings of the MT-ITS Conference (2015, June)