Modeling the effect of electric vehicle adoption on pedestrian traffic safety: An agent-based approach

When operated at low speeds, electric and hybrid vehicles have created pedestrian safety concerns in congested areas of various city centers, because these vehicles have relatively silent engines compared to those of internal combustion engine vehicles, resulting in safety issues for pedestrians and cyclists due to the lack of engine noise to warn them of an oncoming electric or hybrid vehicle. However, the driver behavior characteristics have also been considered in many studies, and the high end-prices of electric vehicles indicate that electric vehicle drivers tend to have a higher prosperity index and are more likely to receive a better education, making them more alert while driving and more likely to obey traffic rules. In this paper, the positive and negative factors associated with electric vehicle adoption and the subsequent effects on pedestrian traffic safety are investigated using an agent-based modeling approach, in which a traffic micro-simulation of a real intersection is simulated in 3D using AnyLogic software. First, the interacting agents and dynamic parameters are defined in the agent-based model. Next, a 3D intersection environment is created to integrate the agent-based model into a visual simulation, where the simulation records the number of near-crashes occurring in certain pedestrian crossings throughout the virtual time duration of a year. A sensitivity analysis is also carried out with 9000 subsequent simulations performed in a supercomputer to account for the variation in dynamic parameters (ambient sound level, vehicle sound level, and ambient illumination). According to the analysis, electric vehicles have a 30% higher pedestrian traffic safety risk than internal combustion engine vehicles under high ambient sound levels. At low ambient sound levels, however, electric vehicles have only a 10% higher safety risk for pedestrians. Low levels of ambient illumination also increase the number of pedestrians involved in near-crashes for both electric vehicles and combustion engine vehicles.     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

基于模块化设计理念的北京品牌越野车造型设计研究

模块化设计理念作为提高零件通用化率和缩短开发周期的有效手段,在汽车设计和生产中已广泛应用.如今,随着消费者购买第二辆车,个性化消费热度提升,模块化设计理念在个性化定制方面有了新的应用意义.在这个消费时期,具有可玩性的越野车受到了消费者的关注,其独特的车身结构十分适合应用模块化设计理念.在对世界经典越野车型、相关消费者个...     

指挥决策问题的可拓模型研究

针对指挥决策中含有的大量矛盾、不相容问题,寻求可能的解决途径。引入可拓学理论和方法,采取物元变换思想,对决策系统进行相容度分析,将其中的矛盾、不相容问题转换为相容问题进行处理,最后根据评价准则对方案进行损耗和效果评价。如果决策结果满足决策的目标与要求,就作为决策方案。编队防空仿真实验进一步验证了模型的可行性和合理性,为解决指挥决策中的对立问题提供了依据。     

数字化隧道三维建模分析

为解决既有隧道数字化三维建模的难题,提出利用构件模型库组装隧道的技术路线。整理出隧道构件模型库的分类,并完成各类构件模型的参数设计工作;提出由构件搭建三维隧道模型的具体步骤并将其固化为6个功能组,分析出每个功能组的作用、输入及输出等关键需求;提出继续开发三维隧道设计软件的构想。     

大型舰船纵摇运动的多层递阶预报

主要介绍多层递阶预报原理及其首次在大型舰船纵摇运动预报中的应用实例.仿真结果表明,多层递阶时间序列模型能较好地反映参数的时变特性,取得较精确的预报结果.     

船舶结构有限元模型快速生成研究

寻求一种快速的船舶有限元建模方法一直是船舶设计工作者努力的课题,直接利用AutoCAD中的二维结构图快速生成船舶结构的三维有限元模型,是一种自动化程度较高、快速性较好的方法,通过介绍船舶结构有限元模型数据的计算生成方法等,体现了其在船舶结构有限元建模上的优越性及局限性,以利于深入开展研究.     

Petri网及其维修建模应用研究

Petri网描述异步并发的能力和形象直观的图形表示，使之成为系统维修过程模型描述的有力工具。文章在对Petri网的基本概念、模型描述方法作简要介绍基础上，分别就不可修系统、可修系统、维修资源共享、维修优先级以及维修费用等维修过程问题，进行了Petri网模型描述。     

S型电气绝缘节的建模与仿真

针对无绝缘轨道电路中S型电气绝缘节 ,本文运用电路理论中的支路电流法讨论了其数学模型的建立与仿真算法的实现 ,给出了绝缘节分别在空载和有负载两种情况下的几种典型特性曲线 ,并进一步分析了绝缘节的输入阻抗、电压传输及电气隔离特性。其各种数字仿真结果与实物测试结果具有相近的变化趋势 ,仿真精度满足要求。结果表明 :该模型能够很好地模拟S型绝缘节的电气特性 ,为S型绝缘节的设计提供了有力的分析工具。     

梁状浮筏隔振系统的降价建模方法

本文提出了一种梁状浮筏隔振系统结构形式。该系统是由２根自由－自由梁和连接民梁、梁与基础的弹簧及阻尼组成。为了减少在动力分析和结构动力优化设计中的计算工作量，本文提出了一种降价建模方法。由该方法得到的降价系统，能够很好地保留由示缩聚有限元模型建立起来的系统低阶动特性。与部件模态综合法相比，该方法形成降价系统的总刚度矩阵和质量矩阵过程简单，且计算结果通常不需要坐标转换即可求得系统的动力响应， 实例计算