Report on design of modules for the stochastic traffic simulation

2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Main Part ◽  
Traffic Simulation ◽  
Cognitive Structure ◽  
Flow Simulation ◽  
Road User ◽  
The Road ◽  
Traffic Flow Simulation ◽  
Cognitive Behaviour ◽  
Traffic Simulations

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).

scholarly journals Report on integration of the stochastic traffic simulation

2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Traffic Flow ◽  
Mathematical Theory ◽  
Traffic Simulation ◽  
Flow Simulation ◽  
Theoretical Design ◽  
Traffic Flow Simulation

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.

scholarly journals Demand Data Modelling for Microscopic Traffic Simulation

2018 ◽  
Vol 19 (4) ◽  
pp. 364-371
Author(s):  
Mihails Savrasovs ◽  
Irina Pticina ◽  
Valery Zemlyanikin ◽  
Ioannis Karakikes
Keyword(s):  
Traffic Flow ◽  
Traffic Simulation ◽  
Flow Simulation ◽  
Simulation Software ◽  
Transport Network ◽  
Data Modelling ◽  
Microscopic Simulation ◽  
Microscopic Traffic Simulation ◽  
Dynamic Assignment ◽  
Traffic Flow Simulation

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.

Traffic Behaviors Simulation under Congestion Pricing Revenue Redistribution Strategy

2012 ◽  
Vol 253-255 ◽  
pp. 1982-1987
Author(s):  
Ze Bin Zhao ◽  
Yu Tian
Keyword(s):  
Traffic Flow ◽  
Congestion Pricing ◽  
Flow Simulation ◽  
Behavioral Model ◽  
General Idea ◽  
The Road ◽  
Road Capacity ◽  
Traffic Flow Simulation ◽  
Multi Agent ◽  
Bus Service

On the basis of behavioral model under congestion pricing revenue redistribution, this paper proposes the general idea, process of the simulation and designs the essential simulation module of congestion pricing revenue redistribution based on the Multi-Agent technology and Starlogo. Traffic behaviors are simulated under the situation that congestion pricing revenue is used to raise the level of bus service and extend the road capacity. Also the simulation is compared with other two situations with and without congestion pricing. The results demonstrate that this method overcomes the localization of the traditional micro traffic flow simulation model, and the traffic flow of congesting section can be effectively reduced and distributed more optimal.

scholarly journals Report on layout of the traffic simulation and trial design of the evaluation

2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Trial Design ◽  
Traffic Simulation ◽  
Driver Behavior ◽  
Flow Simulation ◽  
Behavior Model ◽  
Behavior Study ◽  
Safety Function ◽  
Traffic Flow Simulation

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.

scholarly journals KAJIAN KINERJA PERSIMPANGAN TIDAK BERSINYAL (STUDI KASUS : PERSIMPANGAN TIGA GADUT, JALAN RAYA INDARUNG – BANDAR BUAT, KOTA PADANG)

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Eko Prayitno ◽  
Veronika Veronika
Keyword(s):  
Traffic Flow ◽  
Environmental Data ◽  
Degree Of Saturation ◽  
Road User ◽  
Total Delay ◽  
The Road ◽  
Traffic Conditions ◽  
Road Capacity ◽  
Side Friction Factor ◽  
Side Friction

The highway is one of the infrastructure for the smooth traffic. One part of the road that are considered necessary to be analyzed and evaluated is an intersection. Three Gadut intersection is non signalized intersection. The traffic flow is quite dense, and lack of discipline of road user factors competing space to pass the crossing, resulting in congestion is very influential on traffic conditions at peak hours in the morning, afternoon and evening. Prior to conducting the survey, the first to do is survey the condition of the intersection that includes geometric characteristics and traffic volume. From the analysis of environmental data, side friction factor to the junction of three Gadut is the criteria being. Rated capacity (C) the smallest is 3706.3 smp/hour, the degree of saturation of 1.1 smp/hour. This value is over the limit permitted values manually indonesian road capacity of 0.8 to 0.9 (1.1> 0.9), it is concluded that the traffic flow is the crossroads of three Gadut saturated traffic flow. The queue probability value between 128.8% - 157.4% with a total delay largest average 11.57 seconds/smp. It is concluded that the chances of a queue at the intersection of three Gadut very large, so it could cause congestion.

scholarly journals Effectiveness of Information from Vehicles beyond Nearest Vehicle Ahead for Traffic Flow

2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
Hikaru Shimizu ◽  
Sho Nishiyama ◽  
Yukiko Wakita ◽  
Eisuke Kita
Keyword(s):  
Stability Analysis ◽  
Traffic Flow ◽  
Flow Simulation ◽  
The Other ◽  
Stable Region ◽  
Model Parameters ◽  
Model Stability ◽  
Acceleration Rate ◽  
Traffic Flow Simulation ◽  
Vehicle Acceleration

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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