Investigating micro-simulation error in activity-based travel demand forecasting: a case study of the FEATHERS framework

Activity-based models of travel demand have received considerable attention in transportation planning and forecasting in recent years. However, in most cases they use a micro-simulation approach, thereby inevitably including a stochastic error that is caused by the statistical distributions of random components. As a consequence, running a transport micro-simulation model several times with the same input will generate different outputs, which baffles practitioners in applying such a model and in interpreting the results. A common approach is therefore to run the model multiple times and to use the average value of the results. The question then becomes: what is the minimum number of model runs required to reach a stable result? In this paper, systematic experiments are carried out using Forecasting Evolutionary Activity-Travel of Households and their Environmental RepercussionS (FEATHERS), an activity-based micro-simulation modelling framework currently implemented for the Flanders region of Belgium. Six levels of geographic detail are taken into account. Three travel indices – average daily activities per person, average daily trips per person and average daily distance travelled per person, as well as their corresponding segmentations – are calculated by running the model 100 times. The results show that the more disaggregated the level, the larger the number of model runs is needed to ensure confidence. Furthermore, based on the time-dependent origin-destination table derived from the model output, traffic assignment is performed by loading it onto the Flemish road network, and the total vehicle kilometres travelled in the whole Flanders are subsequently computed. The stable results at the Flanders level provides model users with confidence that application of FEATHERS at an aggregated level requires only limited model runs.     

A model for the visualization and analysis of elevator traffic

ABSTRACT

Analysis of elevator traffic in high rise buildings is critical to the performance evaluation of elevator group control systems (EGCS). Elevator dispatching methods or parking algorithms in an EGCS can be designed or modified according to analyses of traffic flow. However, interpretation of traffic flow based solely on numerical data may not be explicit and transparent for EGCS experts as well as for other non-expert building administration. In this study, we present a model for visualization and analysis of elevator traffic. First, we present an alternative approach for traffic analysis which we call route visualization. In the proposed approach, we initially decompose elevator traffic into its component parts and investigate each component independently. Then, using superposition of components we obtain a reconstructed model of overall traffic. This modeling approach provides component-based traffic analysis and representation of routes with intensities through data visualization. In the second part we introduce a multi-dimensional analysis of time parameters in ECGS. This approach provides a comparative analysis of several control algorithms such as dispatch or park algorithms for different combinations of traffic components.     

A field evaluation case study of the environmental and energy impacts of traffic calming

This study quantifies the energy and environmental impact of a selection of traffic calming measures using a combination of second-by-second floating-car global positioning system data and microscopic energy and emission models. It finds that traffic calming may result in negative impacts on vehicle fuel consumption and emission rates if drivers exert aggressive acceleration levels to speed up to their journeys. Consequently by eliminating sharp acceleration maneuvers significant savings in vehicle fuel consumption and emission rates are achievable through driver education. The study also demonstrates that high emitting vehicles produce CO emissions that are up to 25 times higher than normal vehicle emission levels while low emitting vehicles produce emissions that are 15–35% of normal vehicles. The relative increases in vehicle fuel consumption and emission levels associated with the sample traffic calming measures are consistent and similar for normal, low, and high emitting vehicles.     

马尔柯夫灰色残差模型在剐构桥控制中的应用

文章结合罗天乐特大桥的马尔柯夫灰色残差模型预测实例,介绍马尔柯夫灰色残差模型在线性控制中的原理、计算及应用过程,并根据实际监控经验提出了建议。罗天乐特大桥的具体监控应用实践表明,马尔柯夫灰色残差模型预测精度高,能较好地应用于大跨连续刚构桥的施工线形控制。     

一种螺旋桨参数化建模方法

对螺旋桨进行优化时,需要建立起优化计算的样本空间,即要实现初始桨的参数化建模。本文基于贝塞尔曲线拟合原理编程实现了螺旋桨的参数化建模,对螺旋桨的径向参数分布分别用一条贝塞尔曲线进行拟合,曲线的控制点通过遗传算法寻优求得。文中以4382桨为例,对其进行参数化建模,讨论了三、四、五、六阶贝塞尔曲线的拟合效果,发现三阶贝塞尔曲线拟合光顺性最好、拟合平均误差可以控制在0.3%以内,而且控制点个数较少,最适合拟合螺旋桨径向参数分布。最后通过调整三次贝塞尔曲线控制点的位置调整了原桨叶的几何形状,得到光顺性较好的新桨叶模型,表明该参数化建模方法合理。     

海员胜任力结构及其评价标准初步研究

对129名海员进行了5项6个心理指标的测试。通过专家咨询法确定海员胜任力检测指标体系的权重系数，构建了海员胜任力特征结构模型与综合评价模型。提出了40岁以下和以上年龄海员的胜任力评价标准。     

台州港临海港区规划波浪潮流泥沙数学模型研究

文章研究了台州港临海港区规划围垦后的有关潮流泥沙问题。首先对该海区的自然条件进行了分析,而后使用二维波浪潮流泥沙数学模型研究手段对台州港规划围垦后的二维潮流场、泥沙场、地形冲淤变化进行了模拟研究。研究结果表明,从周围水沙环境的影响考虑,该港区规划围垦的方案是可行的。     

基于Simulink/Stateflow的汽车ABS混合建模与仿真

汽车防抱死制动系统(ABS)是一种很关键的汽车主动安全技术。本文采用基于有限状态机的系统仿真方法,采用Simulink和Stateflow模块混合建模,对ABS模型中的连续系统和离散系统进行仿真。仿真结果表明,该混合仿真系统能比较真实地反映汽车ABS系统的实际工作过程,显著缩短制动距离,提高安全性。     

Rhinoceros软件在客车造型设计中的应用

介绍造型设计软件Rhinoceros,并以豪华大客车为例,讲述该软件在客车CAS(计算机辅助造型设计)中的应用。     

面向驾驶模拟器的高等级公路三维视景建模与实现

随着汽车驾驶模拟器在道路交通仿真中的广泛应用,驾驶员对视景的逼真度也相应地提出了较高的要求。视景仿真系统作为模拟器的一个子系统,其逼真度和实时的动态显示是影响道路交通仿真的关键因素。文中介绍了高等级公路三维视景的建模过程、实现方法,以及地形的简化技术。设计成果表明,这种方法对于利用驾驶模拟器进行道路交通仿真等方面的研究是可行的。