Publication

A Bayesian Estimation of Pedestrian Activities using Sensors Data

2013
Posters

Abstract

Pedestrian modeling is a tool for designing and optimizing infrastructures. In particular, walking in transportation hubs such as railway stations and airports is the key for an efficient multimodal transport systems. Data collections are needed in estimating the demand for these infrastructures. These data can further be used in destination choice models in order to understand pedestrian behavior and forecast demand for future scenarios. Possible applications: railway stations, airports, music festivals.

3rd prize of the ENAC Research Day 2013 Doctoral poster award

Official source

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2013
Posters

Abstract

3rd prize of the ENAC Research Day 2013 Doctoral poster award

Official source

Related concepts (31)

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Transportation forecasting

Transportation forecasting is the attempt of estimating the number of vehicles or people that will use a specific transportation facility in the future. For instance, a forecast may estimate the number of vehicles on a planned road or bridge, the ridership on a railway line, the number of passengers visiting an airport, or the number of ships calling on a seaport. Traffic forecasting begins with the collection of data on current traffic. This traffic data is combined with other known data, such as population, employment, trip rates, travel costs, etc.

Related publications (32)

A Bayesian Estimation of Pedestrian Activities using Sensors Data

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