scholarly journals Parameter Calibration Method of Microscopic Traffic Flow Simulation Models based on Orthogonal Genetic Algorithm

2016 ◽  
Author(s):  
Yanfang Yang ◽  
Yong Qin ◽  
Honghui Dong ◽  
Qing Zhang
Keyword(s):  
Genetic Algorithm ◽  
Traffic Flow ◽  
Flow Simulation ◽  
Simulation Models ◽  
Calibration Method ◽  
Parameter Calibration ◽  
Traffic Flow Simulation

scholarly journals Traffic and Driving Simulator Based on Architecture of Interactive Motion

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Alexander Paz ◽  
Naveen Veeramisti ◽  
Romesh Khaddar ◽  
Hanns de la Fuente-Mella ◽  
Luiza Modorcea
Keyword(s):  
Simulation Model ◽  
Traffic Flow ◽  
Driving Simulator ◽  
Flow Simulation ◽  
Simulation Models ◽  
User Equilibrium ◽  
Human Beings ◽  
Traffic Flow Simulation ◽  
Background Traffic ◽  
Communication And Coordination

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

scholarly journals A Multi-Objective Approach for the Calibration of Microscopic Traffic Flow Simulation Models

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 103124-103140 ◽  
Author(s):  
Carlos Cobos ◽  
Alexander Paz ◽  
Julio Luna ◽  
Cristian Erazo ◽  
Martha Mendoza
Keyword(s):  
Traffic Flow ◽  
Flow Simulation ◽  
Simulation Models ◽  
Multi Objective ◽  
Traffic Flow Simulation

Modelling and Simulation for Safe and Efficient Navigation in Narrow Waterways

2004 ◽  
Vol 57 (1) ◽  
pp. 53-71 ◽  
Author(s):  
A. N. Ince ◽  
E. Topuz
Keyword(s):  
Information System ◽  
Prediction Model ◽  
Traffic Flow ◽  
Traffic Management ◽  
Flow Simulation ◽  
Simulation Models ◽  
Modelling And Simulation ◽  
Traffic Flow Simulation ◽  
Prediction And Simulation ◽  
Ship Handling

This paper outlines the design of a Vessel Traffic Management and Information System (VTMIS) for the Turkish Straits and taking this as an example shows how modelling and simulation may aid safe and efficient navigation of vessels through waterways which are narrow and winding with changing currents and are therefore difficult to navigate and prone to accidents. Ship Handling and Vessel Traffic Flow simulation models and Hyrographic Prediction model are described and the simulation trials conducted under different traffic and environment conditions are discussed to show the role that these prediction and simulation programmes can play in preventing marine casualities in different waterways, which may result in loss of human lifes and property and contamination of the environment.

scholarly journals A Parameters Calibration Method in Simulated Complex Traffic Network

2015 ◽  
Vol 9 (1) ◽  
pp. 262-265 ◽  
Author(s):  
Hu Xinghua ◽  
Zhang Yu
Keyword(s):  
Genetic Algorithm ◽  
Intelligent Transportation Systems ◽  
Simulation Models ◽  
Calibration Method ◽  
Transportation Systems ◽  
Simulation Software ◽  
Parameter Calibration ◽  
Beijing City ◽  
Micro Simulation ◽  
Dynamic Stochastic

Traffic simulation models have been extensively used because of their ability to model the dynamic stochastic nature of transportation systems. Parameter calibration is very complex and does not give optimal results easily. Besides, it is also time-consuming especially for large and complex networks. Initially, the procedure of traffic micro-simulation parameter calibration was put forward. A Vehicle Intelligent Simulation Software Model (VISSIM) models were selected for parameter calibration in complex-network, and, the role of Simultaneous Perturbation Genetic Algorithm (SPGA) was examined in the optimization of component. Moreover an automatic calibration methodology for micro-simulation models was developed in order to select the best parameter set based on the observed Intelligent Transportation Systems (ITS) data which proved effective for different networks. Finally, the methodology was applied to calibrate the Beijing city VISSIM models, followed by the comparison of convergence rate of Genetic Algorithm (GA), Simultaneous Perturbation Stochastic Approximation (SPSA) and SPGA algorithm. The results show that the SPGA was effective and had good performance.

scholarly journals Calibration of Microscopic Traffic Flow Simulation Models considering Subsets of Links and Parameters

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Alexander Paz ◽  
Kul Shrestha ◽  
Cristian Arteaga ◽  
Douglas Baker
Keyword(s):  
Traffic Flow ◽  
Performance Measures ◽  
Flow Simulation ◽  
Simulation Models ◽  
Programming Approach ◽  
Model Parameters ◽  
Traffic Flow Simulation ◽  
Calibration Methods ◽  
Simultaneous Selection ◽  
Selection Of

This study proposes a methodology for the calibration of microscopic traffic flow simulation models by enabling simultaneous selection of traffic links and associated parameters. The analyst selects any number and combination of links and model parameters for calibration. Most calibration methods consider the entire network and use ad hoc approaches without enabling a specific selection of location and associated parameters. In practice, only a subset of links and parameters is used for calibration based on several factors such as expert knowledge of the system or constraints imposed by local governance. In this study, the calibration problem for the simultaneous selection of links and parameters was formulated using a mathematical programming approach. The proposed methodology is capable of calibrating model parameters considering multiple time periods and performance measures simultaneously. Traffic volume and speed are the performance measures used in this study, and the methodology is developed without considering the characteristics of a specific traffic flow model. A genetic algorithm was implemented to find a solution to the proposed mathematical program. In the experiments, two traffic models were calibrated: the first set of experiments included selection of links only, while all associated parameters were considered for calibration. The second set of experiments considered simultaneous selection of links and parameters. The implications of these experiments indicate that the models were calibrated successfully subject to selection of a minimum number of links. As expected, the more links and parameters that are used for calibration, the more time it takes to find a solution, but the overall results are better. All parameter values were reasonable and within constraints after successful calibration.

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).

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