Model and algorithm of stochastic dynamic traffic assignment based on dynamic rainfall intensity

Author:

Ji Xun1,Shao Chunfu1

Affiliation:

1. School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

Abstract

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.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference38 articles.

1. Effects of Rain on Freeway Traffic in Southern California;Dhaliwal;Transportation Research Record,2017

2. Novel Probabilistic Resilience Assessment Framework of Transportation Networks against Extreme Weather Events;Nogal;ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering,2017

3. Integrating Behavioral Models in Network Operations: Evaluating Traveler Information and Demand Management for Weather-Related Events;Frei;Transportation Research Record,2014

4. Calibration of traffic flow models under adverse weather and application in mesoscopic network simulation;Hou;Transportation Research Record,2013

5. Sensitivity of street network capacity under the rain impact: case study of Belgrade;Ivanović;Transport,2018

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