Proactive and reactive strategies to handle surges in urban crowds

Most urban infrastructures are built to cater a planned capacity, yet surges in usage do happen in times (can be either expected or unexpected), and this has long been a major challenge for urban planner. In this thesis, I propose to study approaches handle surges in urban crowd movement. In particu...

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Bibliographic Details
Main Author: DU, Jiali
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/etd_coll_all/25
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1029&context=etd_coll_all
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Institution: Singapore Management University
Language: English
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Summary:Most urban infrastructures are built to cater a planned capacity, yet surges in usage do happen in times (can be either expected or unexpected), and this has long been a major challenge for urban planner. In this thesis, I propose to study approaches handle surges in urban crowd movement. In particular, the surges in demand studied are limited to situations where a large crowd of commuters/visitors gather in a small vicinity, and I am concerned with their movements both within the vicinity and out of the vicinity (the egress from the vicinity). Significant crowd build-ups and congestions can be observed in a number of cases I studied, and when capacity expansion is not a viable strategy (either because of budget or physical constraints), smoothing these demand surges would be the only practical solution. To handle such demand surges in urban crowds, we can either: 1. Distribute demands temporally: by slowing down the flow rate of incoming demands to the congested region through providing incentives or distractions. 2. Distribute demands spatially: by redirecting overflowing demands to other parts of network where spare capacities are still available. This might require additional investment in establishing complementary connection service. My thesis aims at proposing computationally efficient strategies to tackle these issues. The first strategy targets on distributing demands temporally in a proactive way. In other words, this strategy is designed to prevent demand peaks from forming by slowing down crowd from congregating to areas of concern. As an example, I propose to study the strategy of crowd management in the context of theme park; in particular, the delay of flow rate towards congested areas is achieved by providing distractions (or incentives). It is demonstrated that crowd build-ups can be mitigated by utilizing this strategy. However, it might not always be possible to delay the crowd movement. For example, after major sports events that end late, most of crowd would just want to leave the stadium and reach home as soon as possible, and they will not slow down their egress pace, regardless of distractions/incentives. In these cases, I propose to study the use of the second strategy, which distributes crowds spatially to other parts of network so as to avoid clogging the vicinity that is closest to the demand node. More specifically, I propose to provide parallel services complementing existing ones so that more commuters can leave overcrowded areas and start their trips from other less crowded nodes. Consequently, there should be much fewer people queuing for services at the origin node.