scholarly journals Distributed Dynamic Traffic Modeling and Implementation Oriented Different Levels of Induced Travelers

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Yan Liu ◽  
Yao Yu

In order to respond to the variable state of traffic network in time, a distributed dynamic traffic assignment strategy is proposed which can improve the intelligent traffic management. The proposed dynamic assignment method is based on utility theory and is oriented to different levels of induced users. A distributed model based on the marginal utility is developed which combines the advantages of both decentralized paradigm and traveler preference, so as to provide efficient and robust dynamic traffic assignment solutions under uncertain network conditions. Then, the solution algorithm including subroute update and subroute calculation is proposed. To testify the effectiveness of the proposed model in optimizing traffic network operation and minimizing traveler’s cost on different induced levels, a sequence numerical experiment is conducted. In the experiment, there are two test environments: one is in different network load conditions and the other is in different deployment coverage of local agents. The numerical results show that the proposed model not only can improve the running efficiency of road network but also can significantly decrease the average travel time.

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 65679-65692 ◽  
Author(s):  
Li Zhang ◽  
Jiaming Liu ◽  
Bin Yu ◽  
Gang Chen

2010 ◽  
Vol 143-144 ◽  
pp. 1240-1244 ◽  
Author(s):  
Lin Zhang ◽  
Zhao Sheng Yang ◽  
Hong Mei Jia ◽  
Bin Wang

The execution time of shortest path computing determines the efficiency and quality of dynamic traffic assignment. This paper focuses on the design of a parallel calculation system for the shortest path in traffic network aims to reduce the execution time of shortest path computing in dynamic traffic assignment. Here we mainly focus on the process of algorithm parallelization and network decomposition. As the core of the system, a two-queue parallel algorithm is designed for the shortest path in the traffic network which the recursive spectral bisection decomposition approach is employed to separate the network into several parts and the algorithm acts on every sub-network on each processor. The proposed system are experimented on real traffic network and a set of policies are employed that the number of processors is designed in each policy in the study case, and the performances of the parallel calculation system are discussed, the proposed algorithm is proved to be the efficient and effective.


Author(s):  
Liang-Chieh (Victor) Cheng ◽  
Heng Wang

User equilibrium refers to the network-wide state where individual travelers cannot gain improvement by unilaterally changing their behaviors. The Wardropian Equilibrium has been the focus of a transportation equilibrium study. This paper modifies the dynamic traffic assignment method through utilizing the TRANSIMS system to reach the dynamic user equilibrium state in a microscopic model. The focus of research is developing three heuristics in a Routing-Microsimulation-Equilibrating order for reaching system-wide equilibrium while simultaneously minimizing the computing burden and execution. The heuristics are implemented to a TRANSIMS model to simulate a subarea of Houston, TX.


Author(s):  
Yi-Chang Chiu ◽  
Hani S. Mahmassani

An online routing profile updating automaton (ORPUA) approach is introduced as a principal mechanism for operating an online hybrid dynamic traffic assignment (DTA) system for real-time route guidance in a traffic network. The hybrid DTA approach integrates the centralized and the decentralized DTA frameworks by partitioning the set of guided users into two classes according to an initial routing profile (IRP). One class receives the centralized DTA guidance, while the other follows the decentralized DTA routing. ORPUA takes the a priori IRP and updates the guidance supplied to vehicles in a real-time fashion according to the unfolding network conditions and relative performance of the two classes of users. It does not anticipate the future network conditions; instead, it reacts to them and optimizes the overall system performance by improving the performance of the underperforming class of vehicles. Simulation experiments illustrate ORPUA’s potential in maintaining desirable system performance and robustness in most of the demand-supply scenarios considered.


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