Urban link travel speed dataset from a megacity road network

Guo, Feng; Zhang, Dongqing; Dong, Yucheng; Guo, Zhaoxia

doi:10.1038/s41597-019-0060-3

Cited by 29 publications

(14 citation statements)

References 25 publications

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“…Then, the stability level of the S scenarios is calculated using the stability test proposed by Guo et al [27] to determine the number of stochastic scenarios required. The processes for calculating the stability level of S scenarios are shown as follows: generate 2m + 1 scenario sets that have S − m, S − m + 1, .…”

Section: Experimental Settingsmentioning

confidence: 99%

“…Modeling the stochasticity and correlation of link travel speeds in real road networks is highly complicated because there are very high-dimensional dependent random vector [27]. For example, a stochastic time-dependent road network with 200 road links and 10 time periods implies 2000 random speed variables and 1,999,000 (2000 × 1999 ÷ 2) distinct correlations.…”

Section: Introductionmentioning

confidence: 99%

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On the Necessity and Effects of Considering Correlated Stochastic Speeds in Shortest Path Problems Under Sustainable Environments

Zhang

Guo

2019

Sustainability

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This research addresses how the stochasticity and correlation of travel speeds affect the shortest path solutions in sustainable environments. We consider a shortest path problem with the objective function of minimizing a linear combination of the mean and standard deviation of carbon emissions. By adjusting the proportion of the standard deviation in the objective function, the effects of speed stochasticity and correlation are studied under different preferences of the decision-makers on the fluctuations of carbon emissions. Based on 102-day real speed data from the Los Angeles freeway network, this research conducts extensive numerical experiments on 200 randomly chosen origin-destination pairs. Experimental results demonstrate the necessity of considering speed stochasticity and correlation, especially when the standard deviation of carbon emissions takes a large proportion in the objective function. As the weight of the standard deviation in the objective function increases from 0 to 1.5, the reduction of emission objective values increases from 0.03% to 0.13% by considering speed stochasticity, and increases from 0.02% to 0.20% by considering speed correlation. Taking the city Los Angeles with about 2361 taxis and about 525,945 passenger orders in January 2017 as an example, 0.03% and 0.02% reductions respond to about 3156 kg and 2630 kg carbon emission, respectively.

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Section: Experimental Settingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Necessity and Effects of Considering Correlated Stochastic Speeds in Shortest Path Problems Under Sustainable Environments

Zhang

Guo

2019

Sustainability

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“…Link travel speeds in road networks are fundamental for a variety of decision-making problems in logistics, transportation and traffic 7 . Link travel speeds change over space and time due to such as changing travel demands and unstable traffic flows.…”

Section: Introductionmentioning

confidence: 99%

“…By examining the correlations of immediately neighboring links in space and time based on a 45-day travel speed dataset, significant spatial correlations were observed for about 50% of the links and their adjacent links in the same direction, while travel speeds between two consecutive time periods exhibited strong significant temporal correlations 7 . By investigating temporal correlations and spatial correlations of 30 randomly chosen links from the California freeway network based on a 102-day travel speed dataset 17 , it is found that, the temporal correlation of travel speeds on one link decreases on the whole with the increase of time period lag.…”

Section: Introductionmentioning

confidence: 99%

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Understanding the marginal distributions and correlations of link travel speeds in road networks

Guo

et al. 2020

Sci Rep

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Link travel speeds in road networks are essential data for a variety of research problems in logistics, transportation, and traffic management. Real-world link travel speeds are stochastic, and highly dependent on speeds in previous time periods and neighboring road links. To understand how link travel speeds vary over space and time, we uncover their distributions, their space- and/or time-dependent correlations, as well as partial correlations, based on link travel speed datasets from an urban road network and a freeway network. We find that more than 90% (57%) of travel speeds are normally distributed in the urban road (freeway) network, and that correlations generally decrease with increased distance in time and space. We also investigate if and how different types of road links affect marginal distributions and correlations. The results show that different road link types produce quite similar marginal distributions and correlations. Finally, we study marginal distributions and correlations in a freeway network. Except that the marginal distribution and time correlation are different from the urban road network, others are similar.

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Algorithms for optimal min hop and foremost paths in interval temporal graphs

Jain

Sahni

2022

Appl Netw Sci

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Path problems are fundamental to the study of graphs. Temporal graphs are graphs in which the edges connecting the vertices change with time. Min hop paths problem in a temporal graph is the problem of finding time respecting paths from source vertex to every destination vertex such that the path goes through minimum number of edges. Foremost paths problem in a temporal graph requires to find time respecting paths that arrive at the destination vertices at earliest possible time. In this paper we present algorithms to find min hop paths and foremost paths in interval temporal graphs. These algorithms are benchmarked against the fastest algorithms known for foremost and min-hop paths by Wu et al. (IEEE Trans Knowl Data Eng 28(11):2927–2942, 2016a. https://doi.org/10.1109/TKDE.2016.2594065) that work on contact sequence temporal graph model. On the available test data, our foremost path algorithm provides a speedup of up to 1800 over the fastest algorithm for contact sequence graphs; the speedup for our min-hop algorithm is up to 6700. We also demonstrate that interval temporal graph model on which our algorithms work represents a superset of contact sequence temporal graphs. We show that path problems exist that are NP-hard in interval temporal graph model but polynomial in the contact sequence temporal graph model in terms of the number of vertices and edges in the input graph. This is due to the fact that the contact sequence graph model may require much larger number of edges than the corresponding interval temporal graph to represent a given temporal graph.

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Urban link travel speed dataset from a megacity road network

Cited by 29 publications

References 25 publications

On the Necessity and Effects of Considering Correlated Stochastic Speeds in Shortest Path Problems Under Sustainable Environments

On the Necessity and Effects of Considering Correlated Stochastic Speeds in Shortest Path Problems Under Sustainable Environments

Understanding the marginal distributions and correlations of link travel speeds in road networks

Algorithms for optimal min hop and foremost paths in interval temporal graphs

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