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A stochastic optimization framework for road traffic controls based on evolutionary algorithms and traffic simulation

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ADVANCES IN ENGINEERING software 2017年 114卷 348-360页

作者： Jin, Junchen Ma, Xiaoliang Kosonen, Iisakki KTH Royal Inst Technol Syst Simulat & Control S2CLab Dept Transport Sci Tekn Ringen 10 S-10044 Stockholm Sweden Aalto Univ Dept Civil & Environm Engn POB 12100 FI-00076 Aalto Finland

Traffic flow is considered as a stochastic process in road traffic modeling. Computer simulation is a widely used tool to represent traffic system in engineering applications. The increased traffic congestion in urban areas and their impacts require more efficient controls and management. While the effectiveness of control schemes highly depends on accurate traffic model and appropriate control settings, optimization techniques play a central role for determining the control parameters in traffic planning and management applications. However, there is still a lack of research effort on the scientific computing framework for optimizing traffic control and operations and facilitating real planning and management applications. To this end, the present study proposes a model-based optimization framework to integrate essential components for solving road traffic control problems in general. In particular, the framework is based on traffic simulation models, while the solution needs extensive computation during the engineering optimization process. In this work, an advanced genetic algorithm, extended by an external archive for storing globally elite genes, governs the computing framework, and in application it is further enhanced by a sampling approach for initial population and utilizations of adaptive crossover and mutation probabilities. The final algorithm shows superior performance than the ordinary genetic algorithm because of the reduced number of fitness function evaluations in engineering applications. To evaluate the optimization algorithm and validate the whole software framework, this paper illustrates a detailed application for optimization of traffic light controls. The study optimizes a simple road network of two intersections in Stockholm to demonstrate the model-based optimization processes as well as to evaluate the presented algorithm and software performance. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Simulation-based optimization Archived genetic algorithm Road traffic controls Traffic light control object-oriented software framework

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An object-oriented framework for multidisciplinary, multi-physics, computational mechanics

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ENGINEERING WITH COMPUTERS 1999年第1期15卷 105-125页

作者： Sahu, R Panthaki, MJ Gerstle, WH Univ New Mexico Albuquerque High Performance Comp Ctr Albuquerque NM 87131 USA

This paper presents the design and development of an object-oriented framework for computational mechanics. The framework has been designed to address some of the major deficiencies in existing computational mechanics software packages. The framework addresses the deficiencies of existing computational mechanics software packages by (a) having a sound design using the stare of the art in software engineering, and (b) providing model manipulation features that are common to a large set of computational mechanics problems. The framework provides features that are essential to a large set of computational mechanics problems. The domain-specific features provided by the framework are a geometry sub-system specifically designed for computational mechanics, an interpreted Computational Mechanics Language (CML), a structure for management of analysis projects, a comprehensive data model, model development, model query and analysis management. The domain independent features provided by the framework are a drawing sub-system for data visualization, a database server;a quantity sub-system, a simple GUI and an online help server It is demonstrated that the framework, can be used to develop applications that can: (a) extend or modify important parts of the framework to suit their own needs;(b) use CML for rapid prototyping and extending the functionality of the framework;(c) significantly ease the task of conducting parametric studies;(d) significantly ease the task of modeling evolutionary problems;(e) be easily interfaced with existing analysis programs;and (f) be used to carry out basic computational, mechanics research. It is hope that the the framework will substantially ease the task of ct-earing families of software applications that apply existing and upcoming theories of computational mechanics to solve bath academic and real world interdisciplinary simulation problems.

关键词： analysis management computational mechanics computational mechanics language geometric modeling model management object-oriented software framework

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framework for sequential approximate optimization

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STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION 2004年第5期27卷 384-400页

作者： Jacobs, JH Etman, LFP van Keulen, F Rooda, JE Eindhoven Univ Technol Dept Mech Engn Syst Engn Grp NL-5600 MB Eindhoven Netherlands Fac Design Engn & Prod Struct Optimizat & Computat Mech Grp NL-2628 CD Delft Netherlands

An object-oriented framework for sequential approximate optimization (SAO) is proposed. The framework aims to provide an open environment for the specification and implementation of SAO strategies. The framework is based on the Python programming language and contains a toolbox of Python classes, methods, and interfaces to external software. The framework distinguishes modules related to the optimization problem, the SAO sequence, and the numerical routines used in the SAO approach. The problem-related modules specify the optimization problem, including the simulation model for the evaluation of the objective function and constraints. The sequence-related modules specify the sequence of SAO steps. The routine-related modules represent numerical routines used in the SAO steps as "black-box" functions with predefined input and output, e.g., from external software libraries. The framework enables the user to (re-) specify or extend the SAO dependent modules, which is generally impossible in most available SAO implementations. This is highly advantageous since many SAO approaches are application-domain specific due to the type of approximation functions used. A ten-bar truss design problem with fixed loads as well as uncertain loads is used as an illustration and demonstrates the flexibility of the framework.

关键词： object-oriented software framework Python sequential approximate optimization

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framework approach for system on chip software development 20

Framework approach for system on chip software development

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International Symposium on VLSI Technology, Systems and Applications

作者： See, WB Hsiung, PA Chen, SJ Aerosp Ind Dev Co Taichung Taiwan

ISBN: (纸本)0780377656

The demands for new embedded system products that provide new functionality are booming. The system on chip (SoC) technologies enables further cost, feature size reduction and makes embedded system product much more affordable accordingly. However, the software development for SoC product pushes the challenge further in reducing time to market. We propose a framework approach for embedded SoC software development that would (a) enable the parallel development in hardware and software, and (b) provide software framework for cross platform software reuse. Our approach is based on a tunable embedded software development platform (TESDP) that integrates an Embedded software framework (ESF) and a Simulated Hardware framework (SHF). ESF provides a set real-time software frameworks that support cross platform reuse. SHF helps in decoupling the hardware and software development and enable the parallel development in software development parallel with the SoC hardware development. We demonstrate the feasibility of the TESDP approach with the development of a car-borne modular mobile data terminal (MMDT). MMDT provides data communication and global positioning capability for applications in the cargo truck fleet dispatching and monitoring. MMDT can also be applied in the domain related to intelligent transportation system (ITS).

关键词： embedded system object-oriented software framework real-time system

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framework for sequential approximate optimization

Framework for sequential approximate optimization

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3rd ISSMO/AIAA Internet Conference on Approximations in Optimization

关键词： object-oriented software framework Python sequential approximate optimization

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Implementation and Optimization of Group-based Signal Control in Traffic Simulation

Implementation and Optimization of Group-based Signal Contro...

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IEEE International Conference on Intelligent Transportation Systems

作者： Junchen Jin Xiaoliang Ma ITS Lab. KTH R. Inst. of Technol. Stockholm Sweden

ISBN: (纸本)9781479960798

Over the past decades, group-based control has become one of the most popular signal technologies being applied in many cities around the world. LHOVRA control is one of such group-based controls widely employed in Scandinavian countries. While several previous studies showed that group-based control outperforms stage-based control in many aspects, implementation and evaluation of signal controllers are complicated in a real application. In addition, little effort has been put in optimizing such group-based controllers in traffic management practice. This study implements generic group-based control in an object-oriented software framework, while a software-in-the-loop simulation is developed to integrate the signal controller with an open-source traffic simulator, SUMO. Also, stochastic optimization is applied to generate optimal signal parameters according to different settings of objective. In particular, part of the study is to improve the computational performance of the optimization process by parallelized simulation runs. Test-based experiments are finally carried out to evaluate traffic and optimize its impact on a small traffic network in Stockholm.

关键词： control engineering computing digital simulation object-oriented programming public domain software road traffic control signalling stochastic programming traffic engineering computing LHOVRA control SUMO Scandinavian countries Stockholm group-based signal control object-oriented software framework open-source traffic simulator optimal signal parameters parallelized simulation signal technologies small traffic network software-in-the-loop simulation stage-based control stochastic optimization traffic management practice traffic simulation Computational modeling Control systems Delays object oriented modeling Optimization Unified modeling language Vehicles

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