scholarly journals Report on integration of the stochastic traffic simulation

2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  

As part of the AutoDrive project, the OpenPASS framework is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. This framework was adapted and further developed. The deliverable D5.13 deals with the construction of the stochastic traffic simulation. At this point of the process, the theoretical design aspects of D4.20 are implemented. D5.13 explains the operating principles of the different modules. This includes the foundations, boundary conditions, and mathematical theory of the traffic simulation.

2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  

As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).


2018 ◽  
Vol 19 (4) ◽  
pp. 364-371
Author(s):  
Mihails Savrasovs ◽  
Irina Pticina ◽  
Valery Zemlyanikin ◽  
Ioannis Karakikes

Abstract The current paper aim is to present the technique of demand data modelling for microscopic simulation of the traffic flows. Traffic microscopic simulation is a powerful decision supporting tool, which could be applied for a wide range of tasks. In a past microscopic traffic simulation was used to test local changes in transport infrastructure, but the growth of computers performance allows now to simulate wide-scale fragments of the traffic network and to apply more advanced traffic flow simulation approaches, like an example dynamic assignment (DA). The results, obtained in the frame of this research are part of the project completed for one of the shopping malls (Riga, Latvia). The goal of the project was to evaluate different development scenarios of the transport network to raise the accessibility of the shopping mall. The number of practical issues in the frame of this project pushed to develop a new technique to model the demand data for the simulation model. As a traffic flow simulation tool, the PTV VISSIM simulation software was applied. The developed model was based on dynamic assignment approach. To complete the simulation the demand data was represented in two forms: 1) OD matrix for regular traffic in the transport network; 2) trip-chain file for a description of the pass-by and targeted trips.


2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  

Within the AutoDrive project, openPASS is used to develop a cognitive stochastic traffic flow simulation for urban intersections and highway scenarios, which are described in deliverable D1.14. The deliverable D2.16 includes the customizations of the framework openPASS that are required to provide a basis for the development and implementation of the driver behavior model and the evaluated safety function. The trial design for the evaluation of the safety functions is described. Furthermore, the design of the driver behavior study is introduced to parameterize and validate the underlying driver behavior model.


2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
Hikaru Shimizu ◽  
Sho Nishiyama ◽  
Yukiko Wakita ◽  
Eisuke Kita

A driver usually controls the vehicle according to only the information from the nearest leader vehicle. If the information from the other leader vehicles is also available, the driver can control the vehicle more adequately. The aim of this study is to discuss the effectiveness of the information from the other leader vehicles than the nearest one for the traffic flow. For this purpose, the traffic flow is modeled by using the Chandler-type multi-vehicle-following model. This model changes the vehicle acceleration rate according to the velocity differences between the vehicle and its multileader vehicles. After the model stability analysis, the traffic flow simulation is performed. The results reveal that the stable region of the model parameters expands according to the increase of the number of the leader vehicles.


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