Population Capacity Threats to Urban Area Resiliency: Observations on Chaotic Transportation Network Behavior

Abstract

This paper is an endeavor to picture excessive population threats to the resiliency of a large metropolitan area. By employing an existing evolutionary model of tra c ow on a small expository network, we show how chaotic situations occur at certain demand and supply parameter values and try to address the questions: How may one determine city population capacity for its transportation network, what happens if the city passes this limit, or how may one return the city to a stable situation when it runs into unstable or chaotic situations. Under certain assumptions, the paper designs a simulation experiment to revisit the phenomenon discovered by Greenshields in 1934, but for a transportation network in a large city. A ow simulation shows that very small changes in the demand and supply of the network result in large variations in the throughput of the network, such that the time series of the latter values to an external observer are chaotic (with positive Lyapunov exponent). The limit to the resiliency of the city from the standpoint of its transportation network capacity is, then, estimated by a value for the city's population. It is then argued that how to take the network out of this situation.

Resilience Assessment and Optimization for Urban Rail Transit Networks: A Case Study of Beijing Subway Network

“…The network performance is calculated after each node is deleted in the topological map, then the resilience of the network in different scenarios can be achieved by using (14). Some disruptions are listed in Table 2.…”

“…Berdica [13] proposed the concept of vulnerability of road transportation systems which is from a safety point of view and taken as a problem of an insufficient level of service. In transportation networks, vulnerability is commonly measured based on the complement of reliability [13], [14]. Deng et al [6] used the Space L model to analyze the topological vulnerability of the Nanjing Subway network in China which is based on topological characteristics and functional properties of subway networks.…”

Measuring Route Diversity for Urban Rail Transit Networks: A Case Study of the Beijing Metro Network

“…For example, Holmgren [26] defines vulnerability as a collection of properties of an infrastructure system that may weaken or limit its ability to maintain its intended function when exposed to threats and hazards. In transportation networks, vulnerability is commonly seen as the complement of reliability [7,27]. Deng et al [28] use the Space L model to examine the topological vulnerability of the Nanjing Metro network in China.…”