An enhanced SPSA algorithm for the calibration of Dynamic Traffic Assignment models

Lu, Lu; Xu, Yan; Antoniou, Constantinos; Ben‐Akiva, Moshe

doi:10.1016/j.trc.2014.11.006

Cited by 121 publications

(80 citation statements)

References 48 publications

(48 reference statements)

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“…Finally, a third research line, which refers to the contents analyzed in this paper, concerns the structure of the objective function and specifically the investigation of the performances of SPSA AD-PI solution method when applied to the vector formulation recently introduced by Lu et al [12], which showed to improve the efficiency of traditional SPSA method significantly.…”

Section: Conclusion and Further Researchmentioning

confidence: 99%

“…In addition, they proposed an adaptive approach that computes, at each iteration, the weights in the gradient computation according to the relevance of any O-D pair as computed. Lu et al [12] introduced an enhanced SPSA algorithm, which incorporates spatial and temporal correlation between parameters and measurements to minimize the noise generated by uncorrelated measurements and reduce the gradient approximation error. While in the original SPSA the objective function is a single scalar, in the weighted SPSA it is a vector, whose gradient components are weighed by a matrix that expresses the correlations between parameters and measurements.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic O-D Demand Estimation: Application of SPSA AD-PI Method in Conjunction with Different Assignment Strategies

Nigro

Abdelfatah

Cipriani

et al. 2018

Journal of Advanced Transportation

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This paper examines the impact of applying dynamic traffic assignment (DTA) and quasi-dynamic traffic assignment (QDTA) models, which apply different route choice approaches (shortest paths based on current travel times, User Equilibrium: UE, and system optimum: SO), on the accuracy of the solution of the offline dynamic demand estimation problem. The evaluation scheme is based on the adoption of a bilevel approach, where the upper level consists of the adjustment of a starting demand using traffic measures and the lower level of the solution of the traffic network assignment problem. The SPSA AD-PI (Simultaneous Perturbation Stochastic Approximation Asymmetric Design Polynomial Interpolation) is adopted as a solution algorithm. A comparative analysis is conducted on a test network and the results highlight the importance of route choice model and information for the stability and the quality of the offline dynamic demand estimations.

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Section: Conclusion and Further Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic O-D Demand Estimation: Application of SPSA AD-PI Method in Conjunction with Different Assignment Strategies

Nigro

Abdelfatah

Cipriani

et al. 2018

Journal of Advanced Transportation

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“…The first-order SPSA (1SPSA) is related to the KieferWolfowitz (K-W) stochastic approximation (SA) method (Spall, 1992), whereas the second-order SPSA (2SPSA) is a stochastic analogue of the deterministic Newton-Raphson algorithm (Spall, 2000). Lu et al (2015) and Antoniou et al (2015) proposed an enhanced SPSA algorithm for large-scale dynamic traffic assignment applications, called Weighted SPSA (W-SPSA), which incorporates the information of spatial and temporal correlation in a traffic network to limit the impact of noise and improve convergence and robustness. Tymbakianaki et al (2015) proposed the c-SPSA algorithm, a modification which applies the simultaneous perturbation approximation of the gradient within a small number of carefully constructed "homogeneous" clusters one at a time, as opposed to all elements at once.…”

Section: Simultaneous Perturbation Stochastic Approximation (Spsa)mentioning

confidence: 99%

Dynamic Car–Following Model Calibration Using SPSA and ISRES Algorithms

Markou¹,

Papathanasopoulou

Antoniou

2018

Period. Polytech. Transp. Eng.

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“…However, no significant improvement was made (Lu, 2014). This led us to believe that SPSA itself has fundamental limitations, when applied to very large scale, noisy problems without analytical representation and with correlated parameters and measurements, as identified in Lu et al (2015); Cipriani et al (2011);Cantelmo et al (2014). One of those limitations refers to the agnostic perspective on the correlation structure between the variables involved and the observations.…”

Section: Introductionmentioning

confidence: 99%

“…The proposal of Weighted SPSA (W-SPSA) from Lu et al (2015) aims precisely to overcome these limitations by relying on a weight matrix, W, that represents the appropriate correlation structure. While the authors demonstrated the concept and successfully compared it with SPSA in several settings, the treatment of the essential ingredient (i.e.…”

Section: Introductionmentioning

confidence: 99%

W–SPSA in Practice: Approximation of Weight Matrices and Calibration of Traffic Simulation Models

Antoniou

Azevedo

et al. 2015

Transportation Research Procedia

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The development and calibration of complex traffic models demands parsimonious techniques, because such models often involve hundreds of thousands of unknown parameters. The Weighted Simultaneous Perturbation Stochastic Approximation (W-SPSA) algorithm has been proven more efficient than its predecessor SPSA (Spall, 1998), particularly in situations where the correlation structure of the variables is not homogeneous. This is crucial in traffic simulation models where effectively some variables (e.g. readings from certain sensors) are strongly correlated, both in time and space, with some other variables (e.g. certain OD flows). In situations with reasonably sized traffic networks, the difference is relevant considering computational constraints. However, W-SPSA relies on determining a proper weight matrix (W) that represents those correlations, and such a process has been so far an open problem, and only heuristic approaches to obtain it have been considered.This paper presents W-SPSA in a formally comprehensive way, where effectively SPSA becomes an instance of W-SPSA, and explores alternative approaches for determining the matrix W. We demonstrate that, relying on a few simplifications that marginally affect the final solution, we can obtain W matrices that considerably outperform SPSA. We analyse the performance of our proposed algorithm in two applications in motorway networks in Singapore and Portugal, using a dynamic traffic assignment model and a microscopic traffic simulator, respectively.

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An enhanced SPSA algorithm for the calibration of Dynamic Traffic Assignment models

Cited by 121 publications

References 48 publications

Dynamic O-D Demand Estimation: Application of SPSA AD-PI Method in Conjunction with Different Assignment Strategies

Dynamic O-D Demand Estimation: Application of SPSA AD-PI Method in Conjunction with Different Assignment Strategies

Dynamic Car–Following Model Calibration Using SPSA and ISRES Algorithms

W–SPSA in Practice: Approximation of Weight Matrices and Calibration of Traffic Simulation Models

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