Time Coefficient Estimation for Hourly Origin-Destination Demand from Observed Link Flow Based on Semidynamic Traffic Assignment

Motohiro Fujita,Shinji Yamada,Shintaro Murakami

doi:10.1155/2017/6495861

Motohiro Fujita, Shinji Yamada + Show 1 more

Open Access

https://doi.org/10.1155/2017/6495861

Copy DOI

Abstract

Day-long origin-destination (OD) demand estimation for transportation forecasting is advantageous in terms of accuracy and reliability because it is not affected by hourly variations in the OD distribution. In this paper, we propose a method to estimate the time coefficient of day-long OD demand to estimate hourly OD demand and to predict hourly traffic for urban transportation planning of a large-scale road network that lacks discrete-time rich traffic data. The model proposed estimates the time coefficients from observed link flows given a proven day-long OD demand based on a bilevel formulation of the generalized least square and semidynamic traffic assignment (OD-modification approach). The OD-modification approach is formulated as a static user-equilibrium assignment with elastic demand, based on the residual demand at the end of each period. Our model does not require setting many parameters regarding the OD demand matrices and the discrete-time dynamic traffic assignments. Applying the model to large-scale road network demonstrates that it efficiently improves estimation accuracy because the 24-hour time coefficients of survey data are slightly biased and may be modified properly. In addition, the methods that partially relax the assumption of OD-modification approach and transform the estimated demand into demand based on departure time are examined.

Highlights

The four-step prediction technique on a one-day unit to predict day-long origin-destination (OD) demand and link flow is generally used worldwide for urban and transportation planning
The proposed time coefficient estimation (TCoE) model estimates the time coefficients from observed link flows given a proven day-long OD demand, which in turn is based on a bilevel formulation of the generalized least square and semidynamic traffic assignment
We proposed the time coefficient estimation (TCoE) model to obtain the hourly OD demand from observed link flows given a proven day-long OD demand

Summary

Introduction

The four-step prediction technique on a one-day unit to predict day-long origin-destination (OD) demand and link flow is generally used worldwide for urban and transportation planning. The proposed TCoE model estimates the time coefficients from observed link flows given a proven day-long OD demand, which in turn is based on a bilevel formulation of the generalized least square and semidynamic traffic assignment. By using the quasi-dynamic assumption, this method can reduce the number of unknowns given the same set of observed traffic counts This model requires rich data input such as time-dependent OD data (or inflow data from origin) and link flows and did not apply to a generalized large-scale road network, including a nationwide intercity network. The TCoE model proposed uses a bilevel formulation, in which the upper problem is based on the generalized least square to estimate 24-hour time coefficients given the day-long OD demand matrix and observed link flows. The method transforming the estimated hourly OD demand into OD demand based on departure time is examined

Concept of Semidynamic OD Demand-Modification Approach and TCoE Model

Basic Analysis of Time Coefficients for Hourly Origin-Destination Demands

Application of Initial OD Demand into

Assignment Result and Consideration for TCoE

Findings

Conclusion