The relative importance of visual and sound design in the rehabilitation of a bridge connecting a highly populated area and a park

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The moving crowd: collecting and processing of crowd behaviour data

The MOVE project focuses on the collection and analyses of crowd behavior data. The two main goals of the project are first, the collection of data through mobile phones. The second goal is to develop new technologies to process and mine the collected data for crowd behaviour analysis. The technology will allow to make advanced interpretations of historic and dynamic mobile crowd data coming from GSM/GPS and from different classes of users (vehicle, pedestrian, indoor/outdoor). Fusion will be made between data coming from different sources (smartphone, navigation device) and external map data. The interpretation will allow the mining of advanced features/geometry from the crowd data as well as interprete the dynamic behaviour of the population

An opportunistic indoors positioning scheme based on estimated positions

The localization requirements for mobile nodes in wireless (sensor) networks are increasing. However, most research works are based on range measurements between nodes which are often oversensitive to the measurement error. In this paper we propose a location estimation scheme based on moving nodes that opportunistically exchange known positions. The user couples a linear matrix inequality (LMI) method with a barycenter computation to estimate its position. Simulations have shown that the accuracy of the estimation increases when the number of known positions increases, the radio range decreases and the node speeds increase. The proposed method only depends on a maximum RSS threshold to take into account a known position, which makes it robust and easy to implement. To obtain an accuracy of 1 meter, a user may have to wait at the same position for 5 minutes, with 8 pedestrians moving within range on average

How Human Mobility Models Can Help to Deal with COVID-19

[EN] One of the key factors for the spreading of human infections, such as the COVID-19, is human mobility. There is a huge background of human mobility models developed with the aim of evaluating the performance of mobile computer networks, such as cellular networks, opportunistic networks, etc. In this paper, we propose the use of these models for evaluating the temporal and spatial risk of transmission of the COVID-19 disease. First, we study both pure synthetic model and simulated models based on pedestrian simulators, generated for real urban scenarios such as a square and a subway station. In order to evaluate the risk, two different risks of exposure are defined. The results show that we can obtain not only the temporal risk but also a heat map with the exposure risk in the evaluated scenario. This is particularly interesting for public spaces, where health authorities could make effective risk management plans to reduce the risk of transmission.Hernández-Orallo, E.; Armero-Martínez, A. (2021). How Human Mobility Models Can Help to Deal with COVID-19. Electronics. 10(1):1-24. https://doi.org/10.3390/electronics1001003312410

Criteria for assessment of welfare impacts within regional planning of transport

Regional transport system plans present the wide framework for local transport planning, and are the means of applying the national high-level objectives regionally. Transport system plans are usually created interactively with the regional land use planning. Prediction and appraisal of the potential impacts of the alternatives under discussion form an important part of the planning process. This paper presents Finnish experience in defining criteria for assessing the potential welfare impacts of a transport plan or policy. These criteria are to be used co-operatively by the planners and decision-makers. An important issue is the link between the formation of the objectives and the actual evaluation of impacts, as well as the underlying values and views that influence the selection of planning methods and practises. The criteria were drafted based on a literature review and preliminary discussions with national transport authorities. The preliminary criteria were selected and put into order by using the multi-criteria method MACBETH. The process involved active co-operation with the national transport authorities, as well as with other interest groups. The draft criteria were prioritised based on the opinions of selected representatives of national and regional authorities and transport planners. In this paper we focus on the priorisation process of the criteria, as well as discuss the validity and usability of the criteria created. Furthermore, the suitability of multi-criteria analysis in the context of regional transport planning is discussed, in addition to the consistency requirements between the criteria and the multi-criteria model. The criteria have been created in an ongoing Finnish study that aims at supporting regional transport planning, concerning the impacts that changes in the transport system may have on the welfare of the communities and individuals. Furthermore, the suitability of certain Multi-Criteria Decision Aid (MCDA) methods in creating consensus in the planning process is tested.

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page