A Pedestrian Destination-Chain Choice Model from Bayesian Estimation of Pedestrian Activities using Sensors Data
Pedestrian modeling is emerging as a tool for designing new infrastructures and optimizing the use of current ones. Given sensor traces, we are interested in developing a dynamic model that can predict the destination chain of an individual in pedestrian facilities. As a first step, we developed a methodology to collect activity-episodes sequences from scarce data, directly modeling the imprecision in the measure. It generates several candidate lists of activity-episodes sequences associated with a corresponding likelihood.
- URL: http://www.kth.se/en/abe/centra/cts/heart/heart-2013-2nd-symposium-of-the-european-association-for-research-in-transportation-1.354729
- URL: http://blogs.epfl.ch/article/38361
Record created on 2013-09-05, modified on 2017-02-16