Redesigning Subway Map to Mitigate Bottleneck Congestion: An Experiment in Washington DC Using Mechanical Turk

TitleRedesigning Subway Map to Mitigate Bottleneck Congestion: An Experiment in Washington DC Using Mechanical Turk
Publication TypeJournal Article
Year of Publication2017
AuthorsZhan Guo, Jinhua Zhao, Chris Whong, Prachee Mishra, Lance Wyman
JournalTransportation Research Part A
Volume106
Pagination158–169
KeywordsCongestion, Mechanical Turk, route choice, subway map, Washington DC
Abstract

This paper explores the possibility of using subway maps as a planning tool to influence passenger route choice to mitigate congestion. Specifically, it tests whether extending the appearance of an overcrowded subway line on the Washington DC subway map would encourage passengers to use other underutilized lines. The experiment was conducted through the Mechanical Turk, a crowdsourcing platform, with 3056 participants, producing 21,240 route choice decisions on the official and six alternative maps. Results show that redesigned maps significantly affect participants’ route choices. Depending on the specific design, a 20% length increase of the overcrowded line could move 1.9–5.7 percentage points of ridership to an alternative, underutilized line. The change could remove up to 10 passengers per car during the highest peak, reducing the number of highly congested half-hour periods (max load = 100–120 passengers per car) on the overcrowded line from 4 to 1, and the number of crush periods (max load > 120 passengers per car) from 3 to 1. This is done at minimal or zero cost. The paper calls for more attention from transit agencies to the planning potential of transit maps.

URLhttps://doi.org/10.1016/j.tra.2017.09.017
DOI10.1016/j.tra.2017.09.017

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Advanced Mobility Management, Singapore-MIT Alliance for Research and Technology (SMART)

Singapore-MIT Alliance for Research and Technology (SMART), 2016-2020

As part of the Future Urban Mobility (FM) IRG of the Singapore-MIT Alliance for Research and Technology (SMART), the team led by Prof. Zhao combine behavioral science and transportation technology to envision a future urban mobility system for Singapore that integrates public transit, walking and bicycling, shared mobility and autonomous vehicles.  Read More