English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present an integrated microsimulation framework to estimate the pedestrianmovement over time and space with limited data on directional counts. Using theactivity-based approach, simulation can compute the overall demand andtrajectory of each agent, which are in accordance with the available partialobservations and are in response to the initial and evolving supply conditionsand schedules. This simulation contains a chain of processes including:activities generation, decision point choices, and assignment. They areconsidered in an iteratively updating loop so that the simulation candynamically correct its estimates of demand. A Markov chain is constructed forthis loop. These considerations transform the problem into a convergenceproblem. A Metropolitan Hasting algorithm is then adapted to identify theoptimal solution. This framework can be used to fill the lack of data or tomodel the reactions of demand to exogenous changes in the scenario. Finally, wepresent a case study on Montreal Central Station, on which we tested thedeveloped framework and calibrated the models. We then applied it to a possiblefuture scenario for the same station.

Integrated Microsimulation Framework for Dynamic Pedestrian Movement Estimation in Mobility Hub