Road traffic estimation and algorithmic routing in a spatially dependent network

ABSTRACT This work concerns a procedure to estimate the joint distribution of the per‐edge travel times in a road traffic network with spatial dependence. The constructed estimator, based on the realized travel times of a collection of independently operating probe vehicles traversing the network, is shown to be consistent and rate‐optimal. The obtained estimates of the joint travel‐time distribution can be used in routing policies. In particular, as realized travel times are observed en route to the destination, spatial dependence can be leveraged to iteratively update the predictive distribution of the remaining travel time. Importantly, we can deal with general objective functions, reflecting the individual traveler's specific risk aversion, including ones that involve the uncertainty of the estimates. Through a series of numerical experiments, we systematically study the estimator's performance in combination with specific routing policies and objective functions.

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Publication Details

Journal
Scandinavian Journal of Statistics
Published
2025-03-21
DOI
https://doi.org/10.1111/sjos.12780
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Road traffic estimation and algorithmic routing in a spatially dependent network

Rens Kamphuis, Michel Mandjes, Paulo Serra
Scandinavian Journal of Statistics
Data Management and Algorithms
article

Road traffic estimation and algorithmic routing in a spatially dependent network

Rens Kamphuis, Michel Mandjes, Paulo Serra
article en

Abstract

ABSTRACT This work concerns a procedure to estimate the joint distribution of the per‐edge travel times in a road traffic network with spatial dependence. The constructed estimator, based on the realized travel times of a collection of independently operating probe vehicles traversing the network, is shown to be consistent and rate‐optimal. The obtained estimates of the joint travel‐time distribution can be used in routing policies. In particular, as realized travel times are observed en route to the destination, spatial dependence can be leveraged to iteratively update the predictive distribution of the remaining travel time. Importantly, we can deal with general objective functions, reflecting the individual traveler's specific risk aversion, including ones that involve the uncertainty of the estimates. Through a series of numerical experiments, we systematically study the estimator's performance in combination with specific routing policies and objective functions.

Scandinavian Journal of StatisticsVol. 52(2)
Vrije Universiteit Amsterdam (NL), University of Amsterdam (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 94%
Data Management and Algorithms
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Road traffic estimation and algorithmic routing in a spatially dependent network — Rens Kamphuis, Michel Mandjes, et al. · Scandinavian Journal of Statistics (2025) | TGRS Research Map | TGRS