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Microscopic traffic simulations are tools for simulation of traffic in form of individual vehicles. Road types have various traffic characteristics and therefore different models for their traffic simulation and analysis. The Rural Road Traffic Simulator, RuTSim, is a model which was developed by the Swedish National Road and Transport Research Institute, VTI. RuTSim is a microscopic traffic simulator for rural roads. The 2+1 roads are the type of rural roads that allocate 2 lanes to one direction and one lane to the other, with this configuration for the lanes changing sides after a certain distance. In this research a calibration of the current version of RuTSim for 2+1 roads is presented. The project clarifies microscopic traffic simulation models, RuTSim and its specific settings for 2+1 roads, different approaches for calibrating models and finally the calibration process for 2+1 roads in the current version of the RuTSim model.The calibration process provides a better understanding of the specific effects (of the change) of calibration parameters and their role in returning better simulation outputs on traffic of 2+1 roads.
Microscopic traffic simulation models have been widely accepted and applied in transportation engineering and planning practice for the past decades because simulation is cost-effective, safe, and fast. To achieve high fidelity and credibility for a traffic simulation model, calibration and validation are of utmost importance. Most calibration efforts reported in the literature have focused on the informal practice with a specific simulation model, but seldom did they propose a systematic procedure or guideline for simulation model calibration and validation. The purpose of this study was to develop and evaluate a procedure for microscopic simulation model calibration and validation. Three widely used microscopic traffic simulation models, VISSIM, PARAMICS, and CORSIM, were selected for model review and practice of model calibration and validation. The validity of the proposed procedure was evaluated and demonstrated via two case studies including an actuated signalized intersection and a 5-mile freeway segment with a lane-closure work zone. The simulation results were compared against the field data to determine the performance of the calibrated models. The proposed procedure yielded acceptable results for all applications, thus confirming that it was effective for the different networks and simulation models used in the study. Although the calibrated parameters generated the performance measures that were representative of the field conditions, the simulation results of the default parameters were significantly different from the field data.
The increasing power of computer technologies, the evolution of software en- neering and the advent of the intelligent transport systems has prompted traf c simulation to become one of the most used approaches for traf c analysis in s- port of the design and evaluation of traf c systems. The ability of traf c simulation to emulate the time variability of traf c phenomena makes it a unique tool for capturing the complexity of traf c systems. In recent years, traf c simulation – and namely microscopic traf c simulation – has moved from the academic to the professional world. A wide variety of traf- c simulation software is currently available on the market and it is utilized by thousands of users, consultants, researchers and public agencies. Microscopic traf c simulation based on the emulation of traf c ows from the dynamics of individual vehicles is becoming one the most attractive approaches. However, traf c simulation still lacks a uni ed treatment. Dozens of papers on theory and applications are published in scienti c journals every year. A search of simulation-related papers and workshops through the proceedings of the last annual TRB meetings would support this assertion, as would a review of the minutes from speci cally dedicated meetings such as the International Symposiums on Traf c Simulation (Yokohama, 2002; Lausanne, 2006; Brisbane, 2008) or the International Workshops on Traf c Modeling and Simulation (Tucson, 2001; Barcelona, 2003; Sedona, 2005; Graz 2008). Yet, the only comprehensive treatment of the subject to be found so far is in the user’s manuals of various software products.
The goal of this project is to explore the development of methods and tools for the use of microscopic traffic simulation models to support the traffic management center (TMC) software implementation, operation, and testing on the one hand, and the use of Intelligent Transportation System (ITS) data to support the development and calibration of simulation models on the other. The project products include software utilities that use the existing TMC databases and other available information for the preparation and calibration of microscopic simulation tools. In addition, the products include utilities to support testing of the TMC software modules and data archiving processes, as demonstrated by use cases of the tools developed in this study.
The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.
This project proposes a Memetic Algorithm (MA) for the calibration of microscopic traffic flow simulation models. The proposed MA includes a combination of genetic and simulated annealing algorithms. The genetic algorithm performs the exploration of the search space and identifies a zone were a possible global solution can be located. After this zone has been found the simulated annealing algorithm refines the search and locates an optimal set of parameters within that zone. The design and implementation of this methodology seeks to enable the generalized calibration of microscopic traffic flow models. Two different CORSIM vehicular traffic systems were calibrated. All parameters after the calibration were within reasonable boundaries. The calibration methodology has been developed independently of the characteristics of the traffic flow models. Hence, it is likely to be easily used for the calibration of any other model. The proposed methodology has the capability to calibrate all model parameters considering multiple performance measures and time periods simultaneously. A comparison between the proposed MA and the SPSA algorithm was provided. The results are similar; however, the effort required to fine-tune the MA is considerably small compared to the SPSA. The running time of the MA based calibration is larger compared to the SPSA. The MA still requires some knowledge of the model in order to set adequate optimization parameters. The perturbation of the parameters during the mutation process must be large enough to create a measurable change in the objective function but not too large to avoid noisy measurements.
The calibration of microscopic traffic simulation models is an area of intense study; however, additional research is needed into how to select which parameters to calibrate. In this project a procedure was designed to eliminate the parameters unnecessary for calibration and select those which should be examined for a VISSIM model. The proposed iterative procedure consists of four phases: initial parameter selection, measures of effectiveness selection, Monte Carlo experiment, and sensitivity analysis and parameter elimination. The goal of the procedure is to experimentally determine which parameters have an effect on the selected measures of effectiveness and which do not. This is accomplished through the use of randomly generated parameter sets and subsequent analysis of the generated results. The second phase of the project involves a case study on implementing the proposed procedure on an existing VISSIM model of Cobb Parkway in Atlanta, Georgia. Each phase of the procedure is described in detail and justifications for each parameter selection or elimination are explained. For the case study the model is considered under both full traffic volumes and a reduced volume set representative of uncongested conditions.