On-line distributed prediction of traffic flow in a large-scale road network

Wang, Yubin; Schuppen, Jan H. van; Vrancken, Jos

doi:10.1016/j.simpat.2014.06.011

Cited by 18 publications

(7 citation statements)

References 41 publications

(27 reference statements)

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“…Paper by Wang et al [100] describes a novel approach which allows predicting the movement of vehicles in a network separated into two or more subnetworks. The authors used an asynchronous, distributed environment along with the AgentScape middleware, which helps manage distributed agents.…”

Section: Literature Analysismentioning

confidence: 99%

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Rydzewski¹,

Czarnul²

2020

IET intell. transp. syst

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Over the past few decades, the increasing number of vehicles and imperfect road traffic management have been sources of congestion in cities and reasons for deteriorating health of its inhabitants. With the help of computer simulations, transport engineers optimise and improve the capacity of city streets. However, with an enormous number of possible simulation types, it is difficult to grasp valuable, innovative solutions which are of the greatest value to city citizens. In this work, the authors expose various problems within this area having reviewed and analysed over 130 papers selected out of 1200 works in the field of urban simulations. The study describes the selection process of important papers and highlights characteristics of microsimulations, macrosimulations, computation optimisations and other approaches found in the literature which are especially useful and should be further built on in the future. They present and compare results provided in reviewed works in terms of throughput improvement, queue, waiting and travel time reduction, vehicle speed increase, speed‐ups as well as assumed simulation parameters. Finally, they focus on research gaps, such as a small number of works considering crisis simulations, few real‐world scale simulations as well as on software architectural changes and low‐level optimizations.

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Section: Literature Analysismentioning

confidence: 99%

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Rydzewski¹,

Czarnul²

2020

IET intell. transp. syst

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show abstract

“…In this case, a solution would have to be attained every 10 minutes, and applied to each intersection for the next 10-minute period. Apart from reducing the computational effort for the solution of the problem, temporal decomposition takes advantage of accurate prediction of traffic demand, which can only be achieved for short-term traffic predictions (10-15 minutes) [36].…”

Section: Centralized Problem Formulationmentioning

confidence: 99%

“…The computation of updates (33) and (36) are based only on local information, while updates (34) and (35) require knowledge of terms ξ k+1 nc+1,t , c ∈ B O i and ξ k+1 yc−1,t , c ∈ B I i t ∈ T which can be obtained from neighboring intersections.…”

Section: A Phase 1: Distributed Solution Of Rmit Scmentioning

confidence: 99%

“…Although, Algorithm 1 is iterative, it is important to highlight the fact that all three steps of each iteration are analytically computed according to Eqs. (26), (28)- (32), and (33)- (36) respectively. Obtaining distributed analytical solutions to all steps of the ADMM algorithm is not a standard result, but emanates from the structure of the problem and the targeted introduction of variables ξ and ζ into formulation (19).…”

Section: A Phase 1: Distributed Solution Of Rmit Scmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Traffic Signal Control Using the Cell Transmission Model via the Alternating Direction Method of Multipliers

Timotheou

Panayiotou

2014

IEEE Trans. Intell. Transport. Syst.

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Traffic signal control is a key ingredient in intelligent transportation systems to increase the capacity of existing urban transportation infrastructure. However, to achieve optimal system-wide operation it is essential to coordinate traffic signals at various intersections. In this paper we model the multiple-intersections traffic signal control problem using the cell transmission model as a mixed integer linear program. The solution of the problem is facilitated by its special structure which allows both temporal and spatial decomposition. Temporal decomposition is employed to reduce problem size by solving subproblems of smaller time-window compared to the original problem. Temporal subproblems can be further spatially decomposed into subproblems associated with different intersections, which are jointly solved by exchanging messages between neighboring intersections. The proposed distributed solution strategy is comprised of two phases. First, the relaxed linear problem is reformulated and distributedly solved via the Alternating Direction Method of Multipliers. Second, two distributed rounding schemes are developed to solve the original problem. Simulation results indicate that the proposed solution strategy is scalable to large transportation topologies, suitable for online execution and provides close to optimal results.

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“…In fact, when an online strategy is sought, traffic signal plans must be updated every T w time units. In addition, temporal problem decomposition takes advantage of accurate prediction of traffic demand, which can only be achieved over short time periods (10-15 minutes) [11].…”

Section: A Motivationmentioning

confidence: 99%

Towards distributed online cooperative traffic signal control using the cell transmission model

Timotheou

Panayiotou

Polycarpou

2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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Traffic signal control is a key ingredient in intelligent transportation systems (ITS) to increase the capacity of existing urban transportation infrastructure. However, to achieve optimal system-wide operation it is essential to coordinate traffic signals at various intersections. In this paper we model the multiple-intersections traffic signal control problem using the cell transmission model. For its solution, we propose two online distributed strategies, which are based on spatially and temporally decomposing the problem into subproblems associated with different intersections and iteratively solving them by exchanging information between neighboring intersections. Simulation results for a four intersection topology indicate that the proposed strategies achieve distributed, online and close to optimal signal timing plans.

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On-line distributed prediction of traffic flow in a large-scale road network

Cited by 18 publications

References 41 publications

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Distributed Traffic Signal Control Using the Cell Transmission Model via the Alternating Direction Method of Multipliers

Towards distributed online cooperative traffic signal control using the cell transmission model

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