A linear framework for dynamic user equilibrium traffic assignment in a single origin-destination capacitated network

Hoang, Nam H.; Vu, Hai L.; Panda, Manoj; Lo, Hong Kam

doi:10.1016/j.trb.2017.11.013

Cited by 13 publications

(11 citation statements)

References 23 publications

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“…Mehrabipour M proposed a multi OD algorithm based on the cell transmission model, which can optimize the dynamic traffic assignment of the system [8]. Hoang N H proposed a new linear programming framework, which uses the relationship between UE (user equilibrium) and the system optimal solution to solve the dynamic traffic assignment problem [9].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method

Wei

Yan

et al. 2020

Sustainability

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The information level of the urban public transport system is constantly improving, which promotes the use of smart cards by passengers. The OD (origination–destination) travel time of passengers reflects the temporal and spatial distribution of passenger flow. It is helpful to improve the flow efficiency of passengers and the sustainable development of the city. It is an urgent problem to select appropriate indexes to evaluate OD travel time and analyze the correlation of these indexes. More than one million OD records are generated by the AFC (Auto Fare Collection) system of Nanjing metro every day. A complex network method is proposed to evaluate and analyze OD travel time. Five working days swiping data of Nanjing metro are selected. Firstly, inappropriate data are filtered through data preprocessing. Then, the OD travel time indexes can be divided into three categories: time index, complex network index, and composite index. Time index includes use time probability, passenger flow between stations, average time between stations, and time variance between stations. The complex network index is based on two models: Space P and ride time, including the minimum number of rides, and the shortest ride time. Composite indicators include inter site flow efficiency and network flow efficiency. Based on the complex network model, this research quantitatively analyzes the Pearson correlation of the indexes of OD travel time. This research can be applied to other public transport modes in combination with big data of public smart cards. This will improve the flow efficiency of passengers and optimize the layout of the subway network and urban space.

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Section: Introductionmentioning

confidence: 99%

“…Direction and stations of Nanjing metro lines 15,14,13,12,11,10,9,8,7,6,5,41,42,43,44,45,46,47,48,49,50,. 51, 52, 53, 54, 55] …”

mentioning

confidence: 99%

Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method

Wei

Yan

et al. 2020

Sustainability

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“…It is easily seen from equation 18that the REFA model is not characterized by a unique solution. us, multiple solutions may be obtained from the minimization problem (16)- (18), which inherits the multiple-evolution-trajectory problem (see [22] for more details).…”

Section: Excepted Route Flowmentioning

confidence: 99%

“…Step 4: update the adjustment route flows y (n) , y (n) , and y (n) in accordance with equations (16)- (18).…”

Section: Algorithmmentioning

confidence: 99%

“…Considering capacity constraints, Hoang et al established the linear programming of a UE-DTA (user equilibrium dynamic traffic assignment), connected the UE solution to the SO solution, and proposed an incremental loading method that effectively reduced the difficulty in obtaining a UE solution [18]. Liu et al analysed the interaction between travellers and traffic information providers through a network evolution model that considered the influence of user inertia on travellers' route decisions [19].…”

Section: Introductionmentioning

confidence: 99%

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A Traffic Flow Evolution Process toward Mixed Equilibrium with Multicriteria of Route Choice Behaviour

Jiang

Huang

Zhao

2020

Journal of Advanced Transportation

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Based on the price-quantity adjustment behaviour principle of disequilibrium theory, the route choices of travellers are also affected by a quantity signal known as traffic flow, while the route cost is considered as a price signal in economics. Considering the quantity signal’s effect among travellers, a new route comfort choice behaviour criterion and its corresponding equilibrium condition are established. The network travellers are classified into three groups according to their route choice behaviour: travellers in the first group choose the shortest route following the route rapidity behaviour criterion with complete information forming the UE (user equilibrium) pattern, travellers in the second group choose the most comfortable route following the route comfort behaviour criterion with complete information forming the QUE (quantity adjustment user equilibrium) pattern, and travellers in the third group choose a route according to their perceived travel time with incomplete information forming the SUE (stochastic user equilibrium) pattern. The traffic flows of all three groups converge to a new UE-QUE-SUE mixed equilibrium flow pattern after interaction. To depict the traveller-diversified choice behaviour and the traffic flow interaction process, a mixed equilibrium traffic flow evolution model is formulated. After defining the route comfort indicator and the corresponding user equilibrium state, the equilibrium conditions of the three group flows are given under a mixed equilibrium pattern. In addition, an equivalent mathematical programming of the mixed equilibrium traffic flow evolution model is proposed to demonstrate that the developed model converges to the mixed equilibrium state. Finally, numerical examples are examined to evaluate the effect of route comfort proportions on the traffic network flow evolution and analyse the performance of the proposed model.

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Methodology of Feeder Bus Timetable Optimization Based on Bike-Sharing and Express Bus Line

Sun,

Zhou,

Liang

et al. 2024

Lecture Notes in Electrical Engineering

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A linear framework for dynamic user equilibrium traffic assignment in a single origin-destination capacitated network

Cited by 13 publications

References 23 publications

Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method

Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method

A Traffic Flow Evolution Process toward Mixed Equilibrium with Multicriteria of Route Choice Behaviour

Methodology of Feeder Bus Timetable Optimization Based on Bike-Sharing and Express Bus Line

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