The temporal concentration of travel demand in an urban transport network

TL;DR

This paper introduces a new metric to quantify the temporal concentration of travel demand at urban transport stations, validated with London Underground data, and identifies key attributes influencing demand patterns.

Contribution

It presents a novel metric for assessing travel demand concentration and a Random Forest-based framework to identify factors affecting temporal demand variability.

Findings

Outer London stations show higher demand concentration due to low-density areas.

Inner London stations in high-density zones have more concentrated demand during peak hours.

The proposed metric effectively captures spatial variations in travel demand patterns.

Abstract

Suppose $A$ and $B$ are two stations within the mass rapid transit network of a city. Both stations see approximately the same average daily number of passengers entering and exiting their gates. However, passengers are evenly distributed at $A$, whereas activity is concentrated mainly during peak hours at $B$. Although the daily travel demand is the same for both stations, $B$ requires more resources since the number of vehicles, station dimensions and staffing level must be tailored to meet the demands of peak hours. This hypothetical scenario underscores the need to quantify the concentration of travel demand for optimising resource allocation and planning efficiency in an urban transport network. To this end, we introduce a novel metric for assessing the temporal concentration of travel demand at different locations in a generic transport network. Our approach is validated using granular data sourced from smart travel cards, encompassing 272 London Underground (LU) stations. Additionally, we present a methodological framework based on Random Forests to identify attributes of the locations of interest within the transport network that contribute to varying levels of temporal concentration of travel demand. Our case study unveils that LU stations located in areas characterised by low residential, retail, and employment density, predominantly situated in outer London, exhibit the most pronounced temporal concentration of travel demand. Conversely, within inner London, stations servicing high-density employment zones, especially around the City of London, experience a greater temporal concentration of travel demand compared to those catering to commercial and residential districts, typically situated in West London.