An Adaptive Bi-Level Gradient Procedure for the Estimation of Dynamic Traffic Demand

Cantelmo, Guido; Cipriani, Ernesto; Gemma, Andrea; Nigro, Marialisa

doi:10.1109/tits.2014.2299734

Cited by 57 publications

(36 citation statements)

References 17 publications

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“…It is demonstrated that the increase in the value of could permit a higher efficiency in terms of iterations of the algorithm; however, this added value is not always able to compensate for the longer computational times per iteration. A value of equal to 10 ÷ 15% of the number of variables can be a good compromise between reliability of the solution and computational times [11]. …”

Section: Solution Approachmentioning

confidence: 99%

“…All the parameters to be defined for the application of SPSA AD-PI have been chosen according to the directions given in Cantelmo et al [11]: in particular, parameter of (5) convex combination between the seed matrix ( = 0 in the figure) and the true matrix ( = 1 in the figure) and assuming the DNL assignment criterion. A similar picture is shown in Figure 5, where the DTA-DUE criterion adopted for Set I is applied.…”

Section: Numerical Experimentsmentioning

confidence: 99%

“…In the same year, Djukic et al [9] applied the principal component analysis method to reduce the O-D demand variables. Then, Cantelmo et al [11] extended the SPSA AD-PI method to a second-order approximation by applying a Quasi-Newton method. 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.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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: Solution Approachmentioning

confidence: 99%

Section: Numerical Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Self Cite

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“…This approach has later on been improved in [22]. In the formulation proposed by [78] the bi-level problem to solve is:…”

Section: Time-dependent Od Estimationmentioning

confidence: 99%

Traffic Management for Smart Cities

Allström

Barceló

Ekström

et al. 2016

Designing, Developing, and Facilitating Smart Cities

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Smart cities, participatory sensing as well as location data available in communication systems and social networks generates a vast amount of heterogeneous mobility data that can be used for traffic management. This chapter gives an overview of the different data sources and their characteristics and describes a framework for utilizing the various sources efficiently in the context of traffic management. Furthermore, different types of traffic models and algorithms are related to both the different data sources as well as some key functionalities of active traffic management, for example short-term prediction and control.

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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%

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 Adaptive Bi-Level Gradient Procedure for the Estimation of Dynamic Traffic Demand

Cited by 57 publications

References 17 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

Traffic Management for Smart Cities

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

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