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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.
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.
Internationally, significant attention is given to transport sustainability including planning, design, construction, evaluation, safety and durability of the road system. The 4th International Gulf Conference on Roads: Efficient Transportation and Pavement Systems - Characterization, Mechanisms, Simulation, and Modeling, hosted by the University o
The chapters which appear in this volume are selected studies presented at the First International Conference on Engineering and Applied Sciences Optimization (OPT-i), Kos, Greece, 4-6 June 2014 and works written by friends, former colleagues and students of the late Professor M. G. Karlaftis; all in the area of optimization that he loved and published so much in himself. The subject areas represented here range from structural optimization, logistics, transportation, traffic and telecommunication networks to operational research, metaheuristics, multidisciplinary and multiphysics design optimization, etc. This volume is dedicated to the life and the memory of Professor Matthew G. Karlaftis, who passed away a few hours before he was to give the opening speech at OPT-i. All contributions reflect the warmth and genuine friendship which he enjoyed from his associates and show how much his scientific contribution has been appreciated. He will be greatly missed and it is hoped that this volume will be received as a suitable memorial to his life and achievements.
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 book contains a selection of higher quality and reviewed papers of the 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, held in Aveiro, Portugal, in October 2009. The 55 revised full papers presented were carefully reviewed and selected from a total of 163 submissions. The papers are organized in topical sections on artificial intelligence in transportation and urban mobility (AITUM), artificial life and evolutionary algorithms (ALEA), computational methods in bioinformatics and systems biology (CMBSB), computational logic with applications (COLA), emotional and affective computing (EAC), general artificial intelligence (GAI), intelligent robotics (IROBOT), knowledge discovery and business intelligence (KDBI), muli-agent systems (MASTA) social simulation and modelling (SSM), text mining and application (TEMA) as well as web and network intelligence (WNI).