基于人-车-路-环境综合计算的驾驶员期望车速

微观交通流仿真是智能运输系统研究与开发的重要手段。期望车速是微观交通流仿真研究的一个重要参数,受到驾驶员特性、车辆特性、道路条件、交通干扰、天气和承运任务急缓等多种因素的影响,准确确定期望车速是驾驶员行为研究的难点。从研究驾驶员心理-物理特性的角度出发,利用层次分析法,对驾驶员决策思维的递阶层次进行量化,建立基于人-车-路-环境综合计算的驾驶员期望车速模型。经过实测数据验证,该方法用于驾驶员期望车速模型的研究是可行的。     

基于决策树模型的驾驶员期望车速

微观交通流仿真是智能运输系统(ITS)研究与开发的重要手段.期望车速是微观交通流仿真研究的一个重要参数,受到驾驶员特性、车辆特性、道路条件、交通干扰、天气和承运任务急缓等多种因素的影响,准确地确定期望车速是驾驶员行为研究的难点.从研究驾驶员心理-物理特性的角度出发,利用决策树能融知识表示与获取于一身的优点,将决策树用于驾驶员期望车速的研究,以实现对驾驶员行为的模拟再现.仿真结果表明,该方法用于驾驶员期望车速的研究是可行的.     

车道变换决策仿真模型

由于影响车道变换因素的多样性、因素自身变化的随机性和影响因素的难测性,正确反映驾驶员换道行为的不确定性,是微观交通流模拟模型中的难点,也是驾驶员车道变换模型相对于跟驰模型落后的最主要原因之一。从驾驶员心理-物理特性的角度出发,利用层次分析法,对驾驶员决策思维的递阶层次进行量化,建立了基于层次分析的驾驶员车道变换决策模型。经过实测数据验证,该方法用于车道变换决策模型的研究是可行的。     

基于Agent的驾驶员-车辆建模研究与实现

微观交通仿真技术是解决城市交通网络拥塞问题的有效工具.在各种交通元素中,驾驶员-车辆单元是交通流的主体.该文通过对交通流中驾驶员、车辆特性的分析,将驾驶员和车辆视为一个整体,并基于Agent理论对之进行建模.文中详细分析了Agent的生成和路径搜索及选择算法,研究了Agent的跟驰、换道和挤占道等行为.该文最后介绍了基于Agent模型建立的一种微观交通仿真器,并在该仿真器上进行仿真实验.结果表明该系统能够较好的仿真实际交通流状况.     

高速公路驾驶员行为模型的建立与仿真

传统的高速公路模型往往忽略了驾驶员微观个性的差别,很难满足控制、诱导等方面的精度要求.本文依据实际数据聚类分析结果将高速公路上行驶车辆的驾驶员分为五类,提出新的换道模型,并对高速公路上的自由流和拥挤流两种交通流的速度一密度关系用模糊推理进行建模,然后用实际数据进行仿真;最后对仿真结果进行了讨论,分析了模型的可行性.     

基于汽车操纵动力学的神经网络驾驶员模型

作为人一车—路闭环系统的重要环节,驾驶员模型对汽车闭环系统仿真和汽车主动安全性评价都具有重要的意义.本文基于汽车操纵动力学,预瞄—跟随理论以及神经网络建立了一种驾驶员方向控制模型,即两层前馈神经网络驾驶员模型,并在此基础上建立了驾驶员—汽车闭环系统模型.对该闭环模型进行了单移线与双移线仿真试验,仿真结果与理想数据具有很好的一致性,表明该驾驶员模型是合理的,可以有效地模拟驾驶员控制汽车方向的行为特性,为进一步研究人一车一路闭环系统提供了一条可行途径.     

图像处理技术在标定微观交通仿真模型中的应用

城市交通控制的许多决策都是基于微观交通流仿真模型进行的。文章研究应用了图像处理技术来对微观交通流仿真模型的参数进行标定，并使用模拟退火算法使仿真的结果和被仿真对象的实际观测数据吻合。     

三维模拟驾驶仿真系统的研究与实现

为了解决模拟驾驶仿真系统中开发成本昂贵、缺乏二次开发特性等问题,研究并实现了一种结合3DMAX建模软件、开放源代码的Newton物理引擎和OSG图像渲染引擎的三维模拟驾驶仿真系统.硬件系统采用多传感器融合技术来采集驾驶员模拟驾驶时的操作行为,软件系统根据所采集的操作数据实现对车辆的运动和碰撞反应的控制以及对场景视角的切换.实验结果表明,该方法具有软件开发成本低,场景逼真度高,动态效果好等特点,可以满足对驾驶员的驾驶行为进行记录并分析的需要.     

基于最优控制的ANN驾驶员模型与仿真分析

在分析驾驶员行为特性和行为操纵的基础上 ,根据预测跟随理论 ,建立了驾驶员预测控制神经网络 (ANN)模型 ;提出了用最优控制方法确定ANN模型参数的计算方法 ,采用遗传算法 (GA)进行全局优化保证参数的收敛 .对飞机俯仰角操纵进行仿真计算 .结果表明 ,所建立的驾驶员模型考虑了系统的非线性因素 ,实现了多输入多输出功能 ,具有智能特点 .     

考虑速度对期望间距影响的车辆跟驰模型研究

为了真实地反映驾驶员在道路行驶中的车辆跟驰机理,使用相关性分析方法找出影响期望间距的关键因素,从而提出改进的基于期望间距的车辆跟驰模型(improved desired distance model,IDDM).利用NGSIM数据对IDDM和经典的Gipps车辆跟驰模型的参数进行了标定,之后对标定的模型进行评价.研究结果表明,前后两车的速度以及相对速度主要影响跟驰过程中驾驶员采用的期望间距;IDDM与传统Gipps模型相比,其加速度、速度与位置的仿真精度分别提高了0.24 m/s2、0.72 m/s、0.53 m,可以为车辆跟驰行为分析提供参考.     

一种TCP/IP网络与LonWorks网络的集成方案

针对TCP/IP网络与LonWorks网络互操作和集成的需要，该文给出了一种进行两类网络集成的方案——“LonTalk-TCP/IP”集成方案，并详细叙述了此方案的实施步骤。方案基于ISO/OSI参考模型进行设计，采用DDE技术和客户机/服务器模式实现。方案简单实用，具有良好的开放性和可扩展性。     

微观交通仿真中的模型验证技术

模型标定和模型验证是微观交通流仿真建模理论中非常重要的两个方面。人们往往注重前者而忽略后者,或因数据采集困难等原因,注重从宏观角度、而忽略从微观角度进行模型验证,从而导致模型在进一步应用过程中的失效。针对上述情况,文章运用五轮仪实验系统所采获的实际数据,结合了一种基于综合认知结构的车辆跟驰模型的构建过程,从微观角度研究了模型检验和确认的关键技术。研究表明,直观对比和统计推断都是模型验证过程中行之有效的方法。     

Modeling discrete choice behavior based on explicit informationintegration and its application to the route choice problem

Two-stage framework for modeling discrete choice behavior in the presence of new information is presented. It is based on explicit information integration at the first stage, and a decision process based on the integrated information at the second stage. The first stage is conducted using an integration scheme which is source- and content-dependent, and the second stage is implemented using an approximate-reasoning-based choice model. The existence of an explicit information integration stage provides the advantage of improving the calibration procedure of the choice model by facilitating a two-phase calibration process in which both rules and membership functions are calibrated. A simple case study demonstrates the applicability of the approach for modeling human route choice decisions in transportation networks when updated online traffic information is available to drivers. The case study also provides interesting insights on the trade-offs between the number of rules and the importance of generating good membership functions. The suggested decision model is roughly compared to traditional random utility model, and provides favourable results     

Developing a simplified finite element model of a car seat with occupant for predicting vibration transmissibility in the vertical direction

The transmissibility of seat depends on the dynamics of both the seat and the human body, and shows how the amplification and attenuation of vibration varies with the frequency of vibration. A systematic methodology was developed for finite element (FE) modelling of the dynamic interaction between a seat and the human body and predicting the transmissibility of a seat. A seat model was developed to improve computational efficiency before models of the seat pan and backrest were calibrated separately using load–deflection and dynamic stiffness measurements, joined to form the complete seat model, and integrated with the model of a manikin for further calibration. The calibrated seat model was combined with a human body model to predict the transmissibility of the seat. By combining a calibrated seat model with a calibrated human body model, and defining appropriate contacts between the two models, the vibration transmissibility with a seat–occupant system can be predicted.     

Modeling of the City Transport Flows as Applied to the Moscow Agglomeration

A mathematical model of the transport system of a city or an urban agglomeration intended for forecasting the transport and passenger flows was described. It is distinguished for (i) modeling the differences in the structure of travels at different times of day as well as at different days of week and seasons and (ii) consistent use of the concept of “generalized cost” of travel as a criterion for estimating the paths and inter-district “transport” distances. The model was calibrated in practice for the transport network of the Moscow agglomeration which includes the city of Moscow and its suburbs where the major part of the population of the Moscow province is concentrated. The computer-aided realization was based on the TRANSNET integrated designer environment for transport flow modeling.     

Assessing the influence of temperature variations on the geometrical properties of a low-cost calibrated camera system by using computer vision procedures

This paper estimates temperature influence on geometrical properties of both a single camera and a calibrated camera system, assuming low-cost CCD cameras. It does not cover the effect of temperature on the camera’s electronics. Firstly, the influence of temperature change on camera parameters was modelled and integrated into an existing analytical camera model. A modified camera model enables quantitative assessment regarding the influence of temperature variations for a single camera. Temperature variations also directly influence the accuracies of calibrated cameras. The inability to analytically determine the calibration method error magnitude, led us to experimentally estimate errors regarding calibrated cameras. Finally, the total error regarding calibrated cameras was derived by combining the numerical error of the calibration method with those errors originating from temperature variations. The results show that the influence of temperature variations decreases when increasing the distances of the observed objects from the cameras. On a typical building site, the temperature influence is reflected in the image as an error of less than one pixel.     

An integrated approach for water quality assessment of a Kansas watershed

An integrated modeling process was used to estimate the nutrient loadings of different sub-watersheds of the Cheney Reservoir watershed, Kansas, USA. The Agricultural Nonpoint Source Pollution (AGNPS)-ARC INFO interface was used to extract input parameters from various Geographic Information System (GIS) layers, including a landcover layer prepared from Landsat TM image, for the AGNPS model during selected storm events. The curve numbers (CNs) were adjusted depending on the antecedent moisture condition (AMC) of the sub-watershed before each storm. The storm energy intensity (EI) values were computed using a probability method from a rainfall-EI relationship for the location of the study area. Several sensitive parameters of the AGNPS model were then calibrated to match the model-estimated total nitrogen (total-N) and total phosphorous (total-P) with the measured data on a sub-watershed basis during various runoff events. This process was validated by running the calibrated AGNPS model on each sub-watershed of the Cheney Reservoir watershed. This integrated modeling process was found to be effective for smaller watersheds that had adequate rainfall data.     

Identifiability analysis for receiving water body quality modelling

In urban drainage, new computational possibilities have supported the development of new integrated approaches aimed at joint water quantity and quality analysis of the whole urban drainage system. Although the benefit of an integrated approach has been widely demonstrated, to date, several aspects prevent its applicability such as scarce availability of field data if compared with model complexity. These aspects sometimes prevent the correct estimation of parameters thus leading to large uncertainty in modelling response. This is a typical parameter identifiability problem that is discussed in the present paper evaluating the effect of identifiability procedures in increasing operator confidence in modelling results. The methodology presented has been applied to a home-made integrated urban drainage model that has been calibrated/validated considering field data collected in the Savena experimental catchment (Bologna, Italy). The results demonstrate the effectiveness of the identifiability analysis in obtaining a tool for urban integrated modelling applications and field data gathering campaigns.     

Framework for assessing and improving the performance of recursive digital filters for baseflow estimation with application to the Lyne and Hollick filter

Baseflow is often regarded as the streamflow component derived predominantly from groundwater discharge. The estimation of baseflow is important for water supply, water allocation, investigation of contamination impacts, low flow hydrology and flood hydrology. Baseflow is commonly estimated using graphical methods, recursive digital filters (RDFs), tracer based methods, and conceptual models. Of all of these methods, RDFs are the most commonly used, due to their relatively easy and efficient implementation. This paper presents a generic framework for assessing and improving the performance of RDFs for baseflow estimation for catchments with different characteristics and subject to different hydrological conditions. As part of the framework, a fully integrated surface water/groundwater (SW/GW) model is used to obtain estimates of streamflow and baseflow for catchments with different properties, such as soil types and rainfall patterns. An RDF is then applied to the simulated streamflow to assess how well the baseflow obtained using the filter matches the baseflow obtained using the fully integrated SW/GW model. In order to improve the performance of the filter, the user-defined parameter(s) controlling filter operation can be adjusted in order to obtain the best match between the baseflow obtained using the filter and that obtained using the fully integrated SW/GW model (i.e. through calibration). The proposed framework is tested by applying it to a common SW/GW benchmarking problem, the tilted V-catchment, for a range of soil properties. HydroGeoSphere (HGS) is used to develop the fully integrated SW/GW model and the Lyne and Hollick (LH) filter is used as the RDF. The performance of the LH filter is assessed using the commonly used value of the filter parameter of 0.925, as well as calibrated filter parameter values. The results obtained show that the performance of the LH filter is affected significantly by the saturated hydraulic conductivity (K_s) of the soil and that calibrated LH filter parameter can result in significant improvements in filter performance.     

Process optimal design in non-isothermal backward extrusion of a titanium alloy by the finite element method

A new approach to process optimal design in non-isothermal, non-steady metal forming is presented. In this approach, an optimal design problem is formulated on the basis of an integrated thermo-mechanical finite element process model so as to treat diverse process parameters, either thermal or mechanical, as the design variables to be optimized, and a derivative based approach is adopted for conducting optimization. Described in detail are the integrated process model, a formulation for process optimal design, and the schemes for the evaluation of design sensitivity, in particular, a scheme for reflecting the effect of remeshing on design sensitivity. The validity of the schemes for the evaluation of design sensitivity is examined by performing a numerical test. Also examined is the integrated process model regarding its capability of predicting defect formation, through comparison with experimental observations. Then, the proposed optimal design technique is applied to process optimization in non-isothermal backward extrusion of a titanium alloy, with emphasis on preventing defect formation.