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Journal ArticleDOI

The real time estimation of origin-destination flows in the presence of platoon dispersion

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TLDR
Simulation results for data containing geometrically distributed travel times suggests that fitting the correctly specified model produces better estimates of the turning proportions than does the conventional approach where travel times are restricted to a fixed number of time intervals.
Abstract
A number of procedures for the estimation in real time of origin-destination flows in junctions or small networks are reviewed. These are based on the assumption that the time taken by vehicles to traverse the junction or network is either small in relation to the chosen time interval or equal to some fixed number of time intervals. In reality, there will be a distribution of travel times that may span a number of time intervals. This paper proposes two ways to allow for this in the estimation of origin-destination flows. The first, appropriate if travel times are approximately geometrically distributed, makes use of the recurrence model of platoon dispersion. The second makes no assumption about the form of the distribution of travel times, but in general requires the estimation of substantially more parameters. Simulation results for data containing geometrically distributed travel times suggests that fitting the correctly specified model produces better estimates of the turning proportions than does the conventional approach where travel times are restricted to a fixed number of time intervals.

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Dissertation

Estimation and prediction of time-dependent origin-destination flows

Kalidas Ashok
TL;DR: This paper examines two different approaches for real-time estimation/prediction of time-dependent Origin--Destination (O--D) flows and finds that a formulation based on departure rates and shares yields better predictions with some loss of accuracy in filtered estimates.
Journal ArticleDOI

Ridesourcing systems: A framework and review

TL;DR: In this paper, a general framework to describe ridesourcing systems is proposed, which can aid understanding of the interactions between endogenous and exogenous variables, their changes in response to platforms' operational strategies and decisions, multiple system objectives, and market equilibria in a dynamic manner.
Journal ArticleDOI

Alternative Approaches for Real-Time Estimation and Prediction of Time-Dependent Origin--Destination Flows

TL;DR: In this article, two different approaches for real-time estimation/prediction of time-dependent Origin-Destination (O--D) flows are examined, one based on departure rates from each origin and the shares headed to each destination.
Journal ArticleDOI

Estimation and Prediction of Time-Dependent Origin-Destination Flows with a Stochastic Mapping to Path Flows and Link Flows

TL;DR: A new suite of models for the estimation and prediction of time-dependent Origin-Destination (O-D) matrices using a stochastic assignment matrix to address both the offline and real-time versions of the O-D estimation/prediction problem.
Journal ArticleDOI

Travel time forecasting and dynamic origin-destination estimation for freeways based on bluetooth traffic monitoring

TL;DR: The main objectives of this paper are to explore the quality of the data produced by Bluetooth detection of mobile devices that equip vehicles for travel time forecasting and its use in estimating time-dependent origin-destination matrices.
References
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Book

Theory and Practice of Recursive Identification

TL;DR: Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected.

SCOOT-a Traffic Responsive Method of Coordinating Signals

TL;DR: It is concluded that SCOOT reduces vehicle delay by an average of about 12 per cent compared with up-to-date optimised fixed time plans; further substantial benefits are likely where, as is often the case, the fixed time Plans are based on old traffic data.

Transyt: a traffic network study tool

D I Robertson
TL;DR: A "HILLCLIMB" type of OPTIMISATION is used which gives good convergence on the OPTIMAL SIGNAL SETTINGS which gives Good CONVERGENCY on theOptimal Signal Plans.
Journal ArticleDOI

A new class of dynamic methods for the identification of origin-destination flows

TL;DR: Four different methods were developed: an ordinary least squares estimator involving cross-correlation matrices, a constrained optimization method, a simple recursive estimation formula and estimation by Kalman filtering, which are particularly useful for tracking time-variable O-D patterns for on-line identification and control purposes.
Journal ArticleDOI

Recursive estimation of origin-destination matrices from input/output counts

TL;DR: The application of recursive prediction error techniques to the problem of estimating origin-destination patterns from input and output volume counts is described, and those algorithms employing Gauss-Newton search directions appear superior to gradient-based methods, while the constraining procedures improve accuracy.
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