浅谈宁波市水上公共交通的可行性

考虑到宁波市林立的桥梁,较大的水域纵横连通,同时路面上的交通状况时常不理想,本文基于历史面向未来,从民众需求,政府支持,航道情况,其他兄弟城市的相关现状等角度着手,通过文献调研,问卷调查,数据分析等方式来论述宁波市发展水上公共交通的可行性.     

城市客运模式选择研究

国内目前各城市的客运发展存在着地域之间不平衡,发展面临问题众多的局面,行业管理存在较多待破解的关键性问题.本文从城市客运管理运营模式作为研究视角,通过审视和比较世界不同城市交通的发展模式,结合影响城市客运模式的主要决定因素,论证国内目前的发展阶段和城市客运模式,研究提出适合于中国特点的、可持续发展的城市交通发展模式.     

一种基于GPS和IC卡数据的城市公交出行分布推算方法

城市公交规划、管理工作迫切需要信息化技术给予定量的决策数据支持.公交出行分布数据通常基于居民出行调查获得,然而因其调查代价巨大不能作为常态化调查手段.短期的公交线网调整工作更依赖于现状的公交出行分布需求,本文由此提出了一种利用公交GPS和IC卡(含老年卡)数据推算现状公交出行分布的实用方法.当前在大城市常住人口使用IC卡作为公交支付手段已得到相当普及,采用基于车载GPS和乘客IC卡记录能够推断得到全日公交OD数据并用于公交出行量回归模型的标定.模型检验通过后,可结合人口数据和就业岗位资料用标定模型计算以投币作为主要付费方式的流动人口公交OD;叠加两部分OD得到完整的城市公交出行分布结果.该模型的有效性通过2010年郑州市综合交通调查实践得以验证,对其它城市具有借鉴意义.     

船用起重机电气改造

本文对工程船起重机的电控系统的现状进行了介绍和分析,针对目前的系统配置和使用过程中存在的问题,提出了采用交流变频电控系统的改造方案,阐述了系统的配置及设备的选型。通过改造,提升了系统操控性和可靠性。     

柴油机电控单体泵高速电磁阀驱动设计

介绍了柴油机电控单体泵高速电磁阀工作原理及其特点,基于Matlab Simulink对其驱动控制方式进行了仿真分析,给出了单体泵高速电磁阀控制的关键技术。结合分析结果通过对其驱动电路进行了设计,实现了单体泵电磁阀的快速开启与截止,从而精确控制喷油量。     

智能分布式驱动汽车路径跟踪/制动能量回收协同控制策略研究

为了解决智能分布式驱动汽车路径跟踪与制动能量回收系统间的协同控制难题,充分考虑分布式驱动汽车四轮扭矩独立可控在智能驾驶系统中的优势,设计适应不同路面附着条件的智能分布式驱动汽车转向、制动分层协同控制策略。上层控制器依据不同的路面类型设计差异化的多目标代价函数,以综合优化各工况下的控制目标。高附路面下,制定满足最大能量回收值的全局参考车速,在线优化路径跟踪指令,实现最优能量回收的同时减小系统运算负荷;低附路面下,优先考虑车辆的路径跟踪性能和行驶稳定性,在多目标代价函数中取消对全局参考车速的跟随要求,增设终端速度约束与能量回收项性能指标并减小能量回收项性能指标的权重系数。上层控制器基于模型预测控制方法对多目标代价函数进行滚动优化与预测求解,得到期望的前轮转角及4个车轮的总制动扭矩需求。下层控制器根据制动扭矩需求对四轮的液压制动扭矩和电机制动扭矩进行分配,最终完成整个复合制动过程。基于MATLAB/Simulink和CarSim软件,搭建控制器在环仿真平台,并在高附和低附路面条件下对所提出的策略进行试验验证。研究结果表明：高附路面下,所提出的控制策略在准确跟踪期望路径的同时相较固定比例制动力分配方法可提升2.7%的能量回收值并减少约0.02 s的单次计算时间;低附路面下,与使用高附控制策略相比,能够保证车辆的路径跟踪准确性与行驶稳定性,同时可提升7.8%的能量回收值;控制器在环试验结果证明了该协同控制策略对车辆性能提升的有效性。     

电动汽车双电机耦合驱动系统发展与趋势

阐述了国内外电动汽车双电机耦合驱动系统的发展现状,对不同双电机耦合驱动系统的结构特点和应用等进行了总结。从动力性、经济性、布置灵活性、控制复杂性和成本五个方面对不同耦合驱动系统进行了综合对比分析,并对其发展潜力和趋势做出了归纳和展望。     

锂电池储能系统在绞吸挖泥船的应用分析

对国内主流的绞吸挖泥船按照动力系统配置特点进行分类,对各类典型船舶从动力系统与锂电池储能系统应用结合方面开展相关研究,分析各类绞吸挖泥船与锂电池储能系统应用结合的可行性,为后续实船与锂电池储能系统的应用结合提供依据。     

Why do some motorbike riders wear a helmet and others don’t? Evidence from Delhi,India

Road traffic accident fatalities lead to important private and social costs in the metropolitan areas of most low and middle income countries. An important share of these fatalities is due to injuries to the head and the neck. Helmets can provide efficient protection, but many drivers do not use them. We focus on helmet use behavior among motorbike users in Delhi. We use a detailed data set collected for the purpose of the study. To guide our empirical analysis, we rely on a model in which drivers decide on self-protection and self-insurance. The empirical findings suggest that risk-averse drivers are more likely to wear a helmet and that this has no systematic effect on speed. Helmet use also increases with education. Drivers who show a higher awareness of road risks seem to be both more likely to wear a helmet and to speed less. Controlling for risk awareness, we observe that drivers tend to compensate between speed and helmet use. The results can provide a basis for awareness-raising policies. They also show that improvements to the road infrastructure risk leading to risk-compensating behavior.     

Estimating the influence of common disruptions on urban rail transit networks

With the continuous expansion of urban rapid transit networks, disruptive incidents—such as station closures, train delays, and mechanical problems—have become more common, causing such problems as threats to passenger safety, delays in service, and so on. More importantly, these disruptions often have ripple effects that spread to other stations and lines. In order to provide better management and plan for emergencies, it has become important to identify such disruptions and evaluate their influence on travel times and delays. This paper proposes a novel approach to achieve these goals. It employs the tap-in and tap-out data on the distribution of passengers from smart cards collected by automated fare collection (AFC) facilities as well as past disruptions within networks. Three characteristic types of abnormal passenger flow are divided and analyzed, comprising (1) “missed” passengers who have left the system, (2) passengers who took detours, and (3) passengers who were delayed but continued their journeys. In addition, the suggested computing method, serving to estimate total delay times, was used to manage these disruptions. Finally, a real-world case study based on the Beijing metro network with the real tap-in and tap-out passenger data is presented.