scholarly journals Dynamic OD estimation using three phase traffic flow theory

2010 ◽  
Vol 45 (2) ◽  
pp. 143-158 ◽  
Author(s):  
Seungjae Lee ◽  
Benjamin Heydecker ◽  
Yong Hoon Kim ◽  
Eui-Young Shon
Keyword(s):  
Traffic Flow ◽  
Flow Theory ◽  
Od Estimation ◽  
Traffic Flow Theory ◽  
Three Phase

Linking Incidents to Customers (LINC): An Algorithm for Linking Incidents to Rail Customer Delays Inspired by Traffic Flow Theory

2021 ◽  
pp. 036119812110548
Author(s):  
Michael Eichler
Keyword(s):  
Traffic Flow ◽  
Business Processes ◽  
Flow Theory ◽  
Incident Response ◽  
Traffic Flow Theory ◽  
Root Cause ◽  
Rail Systems ◽  
Transit Agencies ◽  
Customer Delay ◽  
Impact Zones

Rail transit agencies have greatly advanced the ability to measure delays to rail system customers and have developed key performance indicators for rail systems based on customer travel time. The ability for operators to link these customer delay metrics to root causes would provide great benefit to agencies, from incident response improvement to capital program prioritization. This paper describes a method for linking late train arrivals to both late customers and incident tickets. Inspired by traffic flow theory, the method identifies impact zones in time and space that can then be linked to a potential root cause by way of incident tickets. This algorithm is currently under development by the Washington Metropolitan Area Transit Authority’s Office of Planning, and its outputs are being integrated into a variety of operations- and capital-related business processes.

From Particle Hopping Models to Traffic Flow Theory

1998 ◽  
Vol 1644 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Kai Nagel
Keyword(s):  
Traffic Flow ◽  
Flow Theory ◽  
Traffic Jam ◽  
Traffic Flow Theory ◽  
Hopping Models ◽  
Simple Models

Very simple models of particles hopping on a grid appear too simple to have much similarity to traffic. Yet, some of these models can be proved to generate, in the so-called fluid-dynamical limit, variations of the Lighthill-Whitham theory. For more realistic particle hopping models, the fluid-dynamical limit is not known, but insight can be obtained by observing traffic jam dynamics.

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