A dynamic traffic assignment model with traffic-flow relationships

Frequent occurrence of urban rainy weather, especially rainstorm weather, affects transportation operation and safety, so it is essential that effective intervention measures to recover disordered traffic be adopted and then analyzed for their influence on the dynamic network. Therefore, models and algorithm to show dynamic traffic flow of traffic network in rainy weather are a fundamental need and have drawn great interest from governments and scholars. In this paper, innovative content contains a travel cost function considering rainfall intensity; considering the travel cost function, a dynamic traffic assignment model based on dynamic rainfall intensity is built. Then a corresponding algorithm is designed. Moreover, this study designs three scenarios under rainfall and analyzes the influence of the rainfall on an example network. The results show that rainfall has a significant effect on traffic flow. The finding proved the proposed models and algorithm can express the development trend of path flow rate on a dynamic network under rainfall.

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A dynamic traffic assignment model for highly congested urban networks

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2012.02.006 ◽

2012 ◽

Vol 24 ◽

pp. 62-82 ◽

Cited By ~ 87

Author(s):

Moshe E. Ben-Akiva ◽

Song Gao ◽

Zheng Wei ◽

Yang Wen

Keyword(s):

Traffic Assignment ◽

Dynamic Traffic Assignment ◽

Dynamic Traffic ◽

Urban Networks ◽

Assignment Model

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A Dynamic Traffic Assignment Model for the Sustainability of Pavement Performance

Sustainability ◽

10.3390/su11010170 ◽

2018 ◽

Vol 11 (1) ◽

pp. 170 ◽

Cited By ~ 9

Author(s):

Xinhua Mao ◽

Jianwei Wang ◽

Changwei Yuan ◽

Wei Yu ◽

Jiahua Gan

Keyword(s):

Travel Time ◽

Traffic Flow ◽

Traffic Assignment ◽

Dynamic Traffic Assignment ◽

Heavy Traffic ◽

Pollutant Emissions ◽

Pavement Performance ◽

Dynamic Traffic ◽

Teaching Learning ◽

Pavement Damage

Existing Dynamic Traffic Assignment (DTA) models assign traffic flow with the principle of travel time, which are easy to distribute most of the traffic flows on the shortest path. A serious unbalance of traffic flow in the network can speed up pavement deterioration of highways with heavy traffic, which influences the sustainability of pavement performance and increases maintenance expenditures. The purpose of this research is to obtain a more optimized traffic assignment for pavement damage reduction by establishing a multi-objective DTA model with the objectives of not only minimum travel time but minimum decline of Present Serviceability Index (PSI) for pavements. Then, teaching-learning-based optimization (TLBO) algorithm is utilized to solve the proposed model. Results of a case study indicate that a more balanced traffic flow assignment can be realized by the model, which can effectively reduce average PSI loss, save maintenance expenditures, extend pavement service life span, save fuel consumption and reduce pollutant emissions in spite of a little increase of average travel time. Additionally, sensitivity of weight factor for the two objective functions is analyzed. This research provides some insights on methods on sustainable pavement performance.

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