Convergence behavior for traffic assignment characterization metrics

Patil, Priyadarshan N.; Ross, Katherine C.; Boyles, Stephen D.

doi:10.1080/23249935.2020.1857883

Cited by 9 publications

(8 citation statements)

References 41 publications

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“…This finding is encouraging, suggesting that the conclusions of the GP experiments are applicable to other algorithms, and that the relative gap is a good universal measure of convergence, regardless of the specific assignment algorithm. Again, these results are in line with prior results from Patil, Ross, and Boyles (2021).…”

Section: Convergence Experimentssupporting

confidence: 92%

“…Both ∆T ST T and ∆V M T converge at roughly similar rates, but ∆V M T is usually slightly lower at a particular gap level. This behavior is in line with the metric behavior for TAP, as noted in Patil, Ross, and Boyles (2021).…”

Section: Convergence Experimentssupporting

confidence: 88%

“…Some applications include network design problems (Yang 1997;Patil, Walthall, and Boyles 2022;Gokalp, Patil, and Boyles 2021), sensitivity analysis (Boyles 2012), trip table estimation (Yang 1995;Lundgren and Peterson 2008), network pricing (Yang and Lam 1996), and other bilevel optimization problems (Yin 2000;Astroza et al 2017;Pandey and Patil 2022;Boyles et al 2018). Patil, Ross, and Boyles (2021) provide additional background on convergence analysis for TAP.…”

Section: Convergence Experimentsmentioning

confidence: 99%

“…These are not merely theoretical concerns -if dynamic equilibrium may not exist at all, or if multiple equilibria exist, it is not at all clear how to use the results of such a model for alternatives analysis; and if a model is highly sensitive to parameters which are hard to estimate (such as a time-dependent OD matrix decades in the future) its practical utility is heavily limited. More extended versions of these issues are discussed in Bar-Gera (2010), Boyles and Ruiz Juri (2019), and Patil, Ross, and Boyles (2021); in short, some applications demand the realism of a dynamic model, while in other applications the advantages of static models outweigh their drawbacks, and careful researchers and practitioners select their tool based on the problem at hand. This ongoing conversation serves as background for our investigation.…”

Section: Introductionmentioning

confidence: 99%

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A fresh look at symmetric traffic assignment and algorithm convergence

Patil¹

2023

Preprint

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Extensions of the static traffic assignment problem with link interactions were studied extensively in the past. Much of the network modeling community has since shifted to dynamic traffic assignment incorporating these interactions. We believe there are several reasons to re-examine static assignment with link interactions. First, if link interactions can be captured in a symmetric, monotone manner, equilibrium always exists and is unique, and provably-correct algorithms exist. We show that several of the most efficient algorithms for the separable traffic assignment problem can be readily applied with symmetric interactions. We discuss how the (asymmetric) Daganzo merge model can be approximated by symmetric linear cost functions. Second, we present computational evidence suggesting that convergence to equilibrium is faster when symmetric, monotone link interactions are present. This is true even when interactions are asymmetric, despite the lack of a provable convergence result. Lastly, we present convergence behavior analysis for commonly used network and link metrics. For these reasons, we think static assignment with link interactions deserves additional attention in research and practice.

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Section: Convergence Experimentssupporting

confidence: 92%

Section: Convergence Experimentssupporting

confidence: 88%

Section: Convergence Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A fresh look at symmetric traffic assignment and algorithm convergence

Patil¹

2023

Preprint

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“…OpenStreetMap [165] [166] , [167] , [168] Transportation Networks [169] [170] , [171] , [172] DTAlite [173] [174] , [175] , [176] PeMS [177] [178] , [179] , [180] New York City Taxi Data [181] [182] , [183] , [184] 图 3 描述了道路结构认知领域的表征方式及发展脉络。传统自动驾驶方案主要基于高精地图信息，预测周围车辆未来数秒时间内的驾驶行为和运动轨迹 [133,134] ，进而规划出安全、高效、舒适行驶的自车运动轨迹。近年来在车联网技术加持下，也有侧重于通过优化多车轨迹节省燃油消耗的相关研究 [135,136] 。车辆级别，结合车辆运动学和动力学模型，获取操纵车辆加减速和转向所对应的油门与刹车踏板行程、方向盘或转向轮转角，以最小操纵代价的前提下驱使车辆完成给定的行驶轨迹。表 4 列出了自动驾驶预测与规划任务的数据集。在运动预测方面， Argoverse 运动预测数据集 [16] 12…”

Section: Conservationunclassified

自动驾驶开源数据体系：现状与未来

Li,

Wang

et al. 2024

Sci. Sin.-Inf.

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Flow count data-driven static traffic assignment models through network modularity partitioning

Roocroft,

Punzo,

Ramli

2023

Transportation

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Accurate static traffic assignment models are important tools for the assessment of strategic transportation policies. In this article we present a novel approach to partition road networks through network modularity to produce data-driven static traffic assignment models from loop detector data on large road systems. The use of partitioning allows the estimation of the key model input of Origin–Destination demand matrices from flow counts alone. Previous network tomography-based demand estimation techniques have been limited by the network size. The amount of partitioning changes the Origin–Destination estimation optimisation problems to different levels of computational difficulty. Different approaches to utilising the partitioning were tested, one which degenerated the road network to the scale of the partitions and others which left the network intact. Applied to a subnetwork of England’s Strategic Road Network and other test networks, our results for the degenerate case showed flow and travel time errors are reasonable with a small amount of degeneration. The results for the non-degenerate cases showed that similar errors in model prediction with lower computation requirements can be obtained when using large partitions compared with the non-partitioned case. This work could be used to improve the effectiveness of national road systems planning and infrastructure models.

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Convergence behavior for traffic assignment characterization metrics

Cited by 9 publications

References 41 publications

A fresh look at symmetric traffic assignment and algorithm convergence

A fresh look at symmetric traffic assignment and algorithm convergence

自动驾驶开源数据体系：现状与未来

Flow count data-driven static traffic assignment models through network modularity partitioning

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