New Procedure for Detector Data Screening in Traffic Management Systems

2000 ◽  
Vol 1727 (1) ◽  
pp. 127-131 ◽  
Author(s):  
Rod E. Turochy ◽  
Brian L. Smith
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Critical Role ◽  
Flow Theory ◽  
Threshold Value ◽  
Management Systems ◽  
Traffic Flow Theory ◽  
Traffic Conditions ◽  
Wide Range ◽  
Data Screening

Automated monitoring of traffic conditions in traffic management systems is of increasing importance as the sizes and complexities of these systems expand. Accurate monitoring of traffic conditions is dependent on accurate input data, yet techniques that can be used to screen data and remove erroneous records are not used in many traffic management systems. Procedures that can be used to perform quality checks on the data before their use in traffic management applications play a critical role in ensuring the proper functioning of condition-monitoring methods such as incident detection algorithms. Tests that screen traffic data can be divided into two categories: threshold value tests and tests that apply basic traffic flow theory principles. Tests that use traffic flow theory use the inherent relationships among speed, volume, and occupancy to assess data validity. In particular, a test that derives the average effective vehicle length from the observed traffic variables detects a wide range of erroneous data. A new data-screening procedure combines both threshold value tests and traffic flow theory–based tests and can serve as a valuable tool in traffic management applications.

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.

Novel Area Occupancy–Based Method for Passenger Car Unit Estimation on Multilane Urban Roads Under Heterogeneous Traffic Scenario

2017 ◽  
Vol 2615 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Raunak Mishra ◽  
Pallav Kumar ◽  
Shriniwas S. Arkatkar ◽  
Ashoke Kumar Sarkar ◽  
Gaurang J. Joshi
Keyword(s):  
Traffic Flow ◽  
Performance Measure ◽  
Area Ratio ◽  
Heterogeneous Traffic ◽  
Passenger Car ◽  
Traffic Conditions ◽  
Passenger Car Unit ◽  
Wide Range ◽  
Traffic Volumes ◽  
Measure Of Performance

This research was aimed at developing an area occupancy–based method for estimating passenger car unit (PCU) values for vehicle categories under heterogeneous traffic conditions on multilane urban roads for a wide range of traffic flow levels. First, PCU values of vehicle categories were determined according to the Transport and Road Research Laboratory definition and replaced the commonly considered measure of performance speed with area occupancy using simulation. The PCU values obtained were found to be significantly different for different volume-to-capacity ratios; this result shows that the PCU value is dynamic in nature. While the dynamic nature of PCU values is well appreciated, practitioners may prefer a single set of optimized PCU values (unique for each vehicle category). Hence, a new method with a matrix solution was proposed to estimate the optimized or unique set of PCU values with area occupancy as the performance measure. To check the credibility of the proposed method, the estimated PCU values were compared from existing guidelines regulated by the Indian Roads Congress (IRC) and values estimated with the widely accepted dynamic PCU concept of speed–area ratio. Results show that the PCU values suggested by IRC and the dynamic PCU concept using the speed–area ratio underestimate and overestimate the flows, respectively, at different traffic volumes. However, the values obtained with the area-occupancy concept were found to be consistent with the traffic flow in a cars-only traffic situation at different flow conditions. The derived set of optimized PCU values proposed can be useful for traffic engineers, researchers, and practitioners for capacity and level-of-service analysis under heterogeneous traffic conditions.

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