scholarly journals Simulation-based optimization of toll pricing in large-scale urban networks using the network fundamental diagram: A cross-comparison of methods

2021 ◽  
Vol 122 ◽  
pp. 102894
Author(s):  
Ziyuan Gu ◽  
Meead Saberi
2020 ◽  
Vol 1 ◽  
Author(s):  
Gabriel Tilg ◽  
Zain Ul Abedin ◽  
Sasan Amini ◽  
Fritz Busch

The three-dimensional passenger macroscopic fundamental diagram (pMFD) describes the relation of the network accumulation of public transport and private vehicles, and the passenger production. It allows for modeling the multi-modal traffic dynamics in urban networks and deriving innovative performance indicators. This paper integrates this concept into a multi-modal transport system design framework formulated as a simulation-based optimization problem. In doing so, we consider the competition for limited road space and the operational characteristics, such as congestion occurrences, at the strategic design level. We evaluate the proposed framework in a case study for the Sioux Falls network. Thereby, we deliver a proof of concept, and show that the proposed methodology indeed designs a transport system which benefits the overall system's performance. This paper further advances the integration of sequential model-based optimization techniques, macroscopic traffic flow concepts, and traffic simulation to design multi-modal transport systems. This supports transport planners and local authorities in composing efficient and robust transport networks.


Author(s):  
Chongxuan Huang ◽  
Nan Zheng ◽  
Jun Zhang

This paper investigates traffic dynamics in bimodal urban networks utilizing the macroscopic fundamental diagram (MFD) and the three-dimensional macroscopic fundamental diagram (3D-MFD), which are network-level traffic flow modeling tools. Although the existence and the properties of the MFD have been extensively analyzed with field data in literature, few empirical studies examine these features of the 3D-MFDs for large-scale networks. For this work, GPS data for cars and buses running in the network of Shenzhen city in China are available for analysis and this offers a great opportunity for the investigation. Interestingly, both MFD and 3D-MFD dynamics are reflected in the data. Network partition is performed to reduce the hysteresis on the MFD and the network is split into two regions for further analysis. Then the investigation focuses on the MFD relationship for buses only. The average passenger occupancy is estimated and incorporated to generate a passenger MFD (pMFD) for buses. Moreover, bus operation on dedicated bus lanes is analyzed. Having understood traffic dynamics of cars, buses, and passengers respectively, the 3D-MFDs which illustrate the joint influence of car and bus accumulations on the global network-level traffic performance are presented. Given the scatter plot of the 3D-MFDs for the two partitioned regions, analytical approximations are provided, fitting by exponential functions. These results are promising, as they confirm the traffic features that were found from simulation-based studies in previous work.


2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Chris S. K. Leung ◽  
Henry Y. K. Lau

Competitive market factors, such as more stringent government regulations, larger number of competitors, and shorter product life cycle, in recent years have created more significant pressure on the management in all supply chain parties. To this end, the ability of analyzing and evaluating systems and related operations involving the deployment of complex multiobjective material handling systems is vital for distribution practitioners. In this respect, simulation modeling techniques together with optimization have emerged as a very useful tool to facilitate the effective analysis of these complex operations and systems. In this paper, we apply a multiobjective simulation-based optimization framework consisting of a hybrid immune-inspired algorithm named Suppression-controlled Multiobjective Immune Algorithm (SCMIA) and a simulation model for solving a real-life multiobjective optimization problem. The results show that the framework is able to solve large scale problems with a large number of parameters, operators, and equipment involved.


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