Sensitivity-Based Linear Approximation Method to Estimate Time-Dependent Origin–Destination Demand in Congested Networks

Sajjad Shafiei · Meead Saberi · Ali Zockaie · Majid Sarvi

16 citations0/0 files storedTransportation Research Record Journal of the Transportation Research Board

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Transportation Planning and Optimization Traffic control and management Traffic Prediction and Management Techniques

Abstract

This paper presents a bi-level optimization problem to estimate offline time-dependent origin–destination (time-dependent O-D) demand on the basis of link flows and historical O-D matrices. The upper-level problem aimed to minimize the summation of errors in both traffic counts and O-D demand. Conventionally, O-D flows are linearly mapped to link flows with the assignment matrix proportions obtained from the dynamic traffic assignment, which is typically formulated as the lower-level problem. However, the linear relationship may be invalid when congestion builds up in the network, and a nonlinear relation between O-D flows and link flows may result. The nonlinearity may lead to a converged solution that is far from the global optimum. An accurate solution should be able to relax the linear assumption and to consider the effect of other O-D flows on the links’ traffic volumes. In this study, a solution method that relied on the sensitivity of assignment proportions to O-D flows was proposed and applied; it required a number of further assignments. To overcome the extra computational requirement, a heuristic method to exclude the extra assignments and to improve the performance of the solution was proposed. The proposed algorithm was applied to multiple networks of varying sizes and congestion levels. The results demonstrated the efficiency of the proposed method for congested networks with less computation time.

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References

2001Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future 1993Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts 1995Heuristic algorithms for the bilevel origin-destination matrix estimation problem 2012A dynamic cordon pricing scheme combining the Macroscopic Fundamental Diagram and an agent-based traffic model 2006Dynamic Origin–Destination Demand Estimation Using Automatic Vehicle Identification Data 2014An enhanced SPSA algorithm for the calibration of Dynamic Traffic Assignment models 2015Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: Design, demonstration and validation 2010A gradient approximation approach for adjusting temporal origin–destination matrices

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2021Comparing Dynamic User Equilibrium and Noniterative Stochastic Route Choice in a Simulation-Based Dynamic Traffic Assignment Model: Practical Considerations for Large-Scale Networks 2023A two-stage stochastic programming approach for dynamic OD estimation using LBSN data 2021An Open GMNS Dataset of a Dynamic Multi-Modal Transportation Network Model of Melbourne, Australia 2020Integration of Departure Time Choice Modeling and Dynamic Origin–Destination Demand Estimation in a Large-Scale Network

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