traffic assignment game theory

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Game Theory and Traffic Assignment

• By Rambha, Tarun ; Boyles, Stephen D.
• Creators: Rambha, Tarun ; Boyles, Stephen D. Rambha, Tarun ; Boyles, Stephen D. Less -
• Corporate Creators: University of Texas at Austin. Center for Transportation Research
• Corporate Contributors: United States. Dept. of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms: [+] Algorithms Game Theory Highways I71: Planning And Forecasting Research Hub Route Choice Traffic Assignment Traffic Equilibrium Traffic Models Traffic Theory Transportation Planning Travel Time
• Publication/ Report Number: SWUTC/13/600451-00065-1
• Resource Type: Tech Report
• Geographical Coverage: Texas ; United States Texas ; United States Less -
• TRIS Online Accession Number: 01502020
• Edition: Final Report
• Corporate Publisher: Southwest Region University Transportation Center (U.S.)
• Abstract: Traffic assignment is used to determine the number of users on roadway links in a network. While this problem has been widely studied in transportation literature, its use of the concept of equilibrium has attracted considerable interest in the field of game theory. The approaches used in both transportation and game theory disciplines are explored, and the similarities and dissimilarities between the m are studied. In particular, treatment of multiple equilibrium solutions using equilibrium refinements and learning algorithms which convergence to equilibria under incomplete information and/or bounded rationality of players are discussed in detail. More ▼ -->
• Format: PDF
• Funding: DTRT12-G-UTC06
• Collection(s): University Transportation Centers US Transportation Collection
• Main Document Checksum: [+] urn:sha256:eb1283a25eb0c736013a85e25a9d179cb44c1f93bac91b57434c020eb05b92f8
• Download URL: https://rosap.ntl.bts.gov/view/dot/27388/dot_27388_DS1.pdf

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• DOI: 10.1016/S0191-2615(01)00022-4
• Corpus ID: 153625722

Risk-averse user equilibrium traffic assignment: an application of game theory

• M. Bell , C. Cassir
• Published 1 September 2002
• Economics, Computer Science
• Transportation Research Part B-methodological

219 Citations

Wardrop equilibria with risk-averse users, a risk-averse user equilibrium model for route choice problem in signal-controlled networks, integrating equilibrium assignment in game-theoretic approach to measure many-to-many transportation network vulnerability, a mean-risk model for the stochastic traffic assignment problem, cooperative game approaches to measuring network reliability considering paradoxes, risk-averse equilibrium for autonomous vehicles in stochastic congestion games, combined traffic assignment model with game theory, a mean-risk model for the traffic assignment problem with stochastic travel times, the discussion of system optimism and user equilibrium in traffic assignment with the perspective of game theory, risk-averse equilibria for vehicle navigation in stochastic congestion games, 4 references, a game theory approach to measuring the performance reliability of transport networks, fictitious play for finding system optimal routings in dynamic traffic networks 1 this work was supp, travel outcome and performance: the effect of uncertainty on accessibility, related papers.

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Traffic Networks: Dynamic Traffic Routing, Assignment, and Assessment

• Reference work entry
• pp 9429–9470
• Cite this reference work entry

• Hesham Rakha 2 &
• Aly Tawfik 2  

1170 Accesses

25 Citations

Definition of theSubject

The dynamic nature of traffic networks is manifested inboth temporal and spatial changes in traffic demand, roadwaycapacities, and traffic control settings. Typically, theunderlying network traffic demand builds up over time at theonset of a peak period, varies stochastically during thepeak period, and decays at the conclusion of the peak period. Astraffic congestion builds up within a transportationnetwork, drivers may elect to either cancel their tripaltogether, alter their travel departure time, change their modeof travel, or change their route of travel. Dynamic trafficrouting is defined as the process of dynamically selecting thesequence of roadway segments from a trip origin toa trip destination. Dynamic routing entails usingtime‐dependent roadway travel times to compute thissequence of roadway segments. Consequently, the modeling ofdriver routing behavior requires the estimation of roadwaytravel times into...

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Abbreviations

A roadway segment with homogeneous traffic and roadway characteristics (e. g. same number of lanes, base lane capacity, free‐flow speed, speed‐at‐capacity, and jam density). Typically networks are divided into links for traffic modeling purposes.

A sequence of roadway segments (links or arcs) used by a driver to travel from his/her point of origin to his/her destination.

The procedure that computes the sequence of roadways that minimize some utility objective function. This utility function could either be travel time or a generalized function that also includes road tolls.

The procedure used to find the link flows from the Origin‐Destination (O‐D) demand. Traffic assignment involves two steps: (1) traffic routing and (2) traffic demand loading. Traffic assignment can be divided into static, time‐dependent, and dynamic.

The assignment of traffic on a network such that it distributes itself in a way that the travel costs on all routes used from any origin to any destination are equal, while all unused routes have equal or greater travel costs.

The assignment of traffic such that the average journey travel times of all motorists is a minimum, which implies that the aggregate vehicle‐hours spent in travel is also minimum.

Traffic assignment ignoring the temporal dimension of the problem.

An approximate approach to modeling the dynamic traffic assignment problem by dividing the time horizon into steady‐state time intervals and applying a static assignment to each time interval.

Traffic assignment considering the temporal dimension of the problem.

The procedure of assigning O‐D demands to routes.

The procedure that estimates O‐D demands from measured link flow counts, which includes static, time‐dependent, and dynamic.

A mathematical representation (traffic flow model) for traffic stream motion behavior.

A mathematical representation (traffic flow model) for driver longitudinal motion behavior.

The increase in a link's travel time resulting from an assignment of an additional vehicle to this link.

Road pricing is an economic concept in which drivers are charged for the use of the road facility.

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Rakha, H., Tawfik, A. (2009). Traffic Networks: Dynamic Traffic Routing, Assignment, and Assessment. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_562

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Traffic assignment in urban transportation network problem with emission constraints in China: a cooperative game theory

Affiliations.

• 1 School of Traffic & Transportation, Lanzhou Jiaotong University, 88 Anning Rd, Lanzhou, 730070, China. [email protected].
• 2 School of Business Administration, Henan University of Animal Husbandry and Economy, 146 Yingcai St., Huiji District, Zhengzhou, 450053, China. [email protected].
• 3 School of Traffic & Transportation, Lanzhou Jiaotong University, 88 Anning Rd, Lanzhou, 730070, China.
• 4 Key Laboratory of Deep Underground Science and Engineering (Ministry of Education), School of Architecture and Environment, Sichuan University, 24 First Ring Rd, Chengdu, 610065, China.
• PMID: 37131006
• DOI: 10.1007/s11356-023-27108-9

Traffic assignment in urban transport planning is the process of allocating traffic flows in a network. Traditionally, traffic assignment can reduce travel time or travel costs. As the number of vehicles increases and congestion causes increased emissions, environmental issues in transportation are gaining more and more attention. The main objective of this study is to address the issue of traffic assignment in urban transport networks under an abatement rate constraint. A traffic assignment model based on cooperative game theory is proposed. The influence of vehicle emissions is incorporated into the model. The framework consists of two parts. First, the performance model predicts travel time based on the Wardrop traffic equilibrium principle, which reflects the system travel time. No travelers can experience a lower travel time by unilaterally changing their path. Second, the cooperative game model gives link importance ranking based on the Shapley value, which measures the average marginal utility contribution of links of the network to all possible link coalitions that include the link, and assigns traffic flow based on the average marginal utility contribution of a link with system vehicle emission reduction constraints. The proposed model shows that traffic assignment with emission reduction constraints allows more vehicles in the network with an emission reduction rate of 20% than traditional models.

Keywords: Cooperative game theory; Emission constraints; Shapley value; Traffic assignment; Urban traffic; Vehicle emissions.

© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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