Second order macroscopic traffic flow model validation using automatic differentiation with resilient backpropagation and particle swarm optimisation algorithms

Poole, Adam; Kotsialos, Apostolos

doi:10.1016/j.trc.2016.07.008

Cited by 18 publications

(9 citation statements)

References 39 publications

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“…Compared with other heuristic algorithms, PSO algorithm is suitable for solving large-scale multiobjective problems. It converges fast to optimal solution and encodes simply because it only uses a few parameters for tuning [37][38][39]. Based on the mentioned characteristics, the PSO algorithm is applied to solve the double-objective model that considers the utilizing rate and the walking distance.…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance

Zhang

Gao

ShuRui

et al. 2020

Journal of Advanced Transportation

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Efficient parking tends to be challenging in most large cities in China. Drivers often spend substantial amounts of time looking for parking lots while driving at low speeds, thereby resulting in interference with road traffic. This paper focuses on efficiently allocating parking spaces to the demanders. A double-objective model is proposed that considers both the utilizing rate and the walking distance. First, managers want to utilize parking resources fully. Therefore, they tend to prioritize the efficient distribution of parking spaces in response to parking demands. However, demanders typically choose parking spaces according to convenience. The second objective is the acceptable walking distance from the parking space to the destination. The particle swarm optimization (PSO) algorithm is used to solve this model. We collected parking demand and supply data in a central business district (CBD) of Harbin in China and evaluated the feasibility of the model. The results demonstrate that the proposed model increases the occupying rates of parking lots in residential zones while decreasing the walking distance. The shared use of parking spaces maximizes the utility and alleviates the shortage of parking spaces in downtown.

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Section: Particle Swarm Optimizationmentioning

confidence: 99%

A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance

Zhang

Gao

ShuRui

et al. 2020

Journal of Advanced Transportation

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“…The differentiation method used in this study is based on the following approximation of the time derivative: [26], scheduling [27], and model validation [28]. In these studies, PSO was employed to solve multi-objective models and locate optimal values.…”

Section: Pid Controllermentioning

confidence: 99%

Hybrid approach for variable speed limit implementation and application to mixed traffic conditions with connected autonomous vehicles

Zhao

Ranjitkar

et al. 2018

IET Intelligent Transport Systems

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“…Four of them are located on the edges of the city's central district, and two within that district. The number of vehicles veh min (h) travelling in the city at time h was determined by minimising the difference between the real number of vehicles crossing the selected intersections (as observed by ITS cameras) and the number of vehicles returned by the model [35]:…”

Section: Parameter Identificationmentioning

confidence: 99%

Identification of parameters and verification of an urban traffic flow model. A case study in Wrocław

Chalfen

Kamińska

2018

ITM Web Conf.

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A macroscopic model of road traffic flow in an entire city is constructed, using the example of Wrocław. The model is of deterministic-random type. The start and finish points of each vehicle journey are random elements of the model, while the street graph, routes of travel and traffic parameters are obtained in a deterministic manner. Vehicle speed is dependent on traffic density, and the time needed to cross an intersection depends on the number of waiting vehicles. The route of travel between given start and finish points is determined using Dijkstra’s algorithm, minimising the journey time. The street graph of Wrocław was constructed using data from the Open Street Map website. Identification of parameters and verification of the model were performed using hourly data on traffic volumes at the city’s major intersections in the years 2015–16, obtained from the Intelligent Transport System (ITS). Identification was made of the total number of vehicles travelling in the city at each time of day, a quantity that is difficult to determine by other methods. An accuracy of around 15% was obtained for times between 6.00 and 22.00, while for night-time the verification error exceeded 30%. The model may be used to analyse the impact of planned modifications to the transport system on traffic parameters in the city. It may also serve as a constituent of a larger model for investigating the effect of road transport on atmospheric pollution or for identifying areas at risk of noise pollution.

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Second order macroscopic traffic flow model validation using automatic differentiation with resilient backpropagation and particle swarm optimisation algorithms

Cited by 18 publications

References 39 publications

A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance

A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance

Hybrid approach for variable speed limit implementation and application to mixed traffic conditions with connected autonomous vehicles

Identification of parameters and verification of an urban traffic flow model. A case study in Wrocław

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