柳州市城市交通现状分析与对策研究

通过分析柳州市发展特点、交通设施、城市布局等方面的因素,对城市交通所面临的问题进行初步探讨.提出了通过加快路网建设、发展公交系统等措施解决交通困境问题.     

快速公交系统通行能力计算方法研究

快速公交系统的通行能力是由瓶颈车站决定的.首先分析了车站通行能力的基本原理和主要影响因素,并基于排队论构造了单一停靠位通行能力的计算模型.同时,根据北京、杭州和昆明三地快速公交系统(公交专用道)的实际运营状况对模型参数进行了详细地标定和说明,提出缩短公交车平均停靠时间和改善系统运营稳定性是提升通行能力的重要途径.在此基础上,以北京市南中轴路快速公交为例,说明了模型的应用方法,并定量分析了各种因素对通行能力的影响.最后,对多停靠位车站的周转效率变化规律进行了分析,提出了其通行能力的计算方法.     

车载总线通讯安全分析

随着汽车智能化和网联化的快速发展,车辆上应用的电子控制单元（ECU）数量越发庞大。在成本有效控制的基础上保证不同种类的电子控制单元可以有效地通讯,不同的总线协议被应用到车辆上。车辆作为对于安全性要求非常高的一种产品,不同的总线协议有着其独有的特点。对不同总线应用过程可能出现的安全性问题进行分析,是保证车辆安全开发的必要的条件。文章对不同的车载总线应用情况进行简要介绍,明确常见总线类型的各自特点,归纳不同协议类型的总线在应用过程中的面临的共性问题,分析风险问题的产生,可能风险点并提出简要防护措施。     

Passenger travel characteristics and bus operational states: a study based on IC card and GPS data in Yinchuan,China

ABSTRACT

In recent years, public transport has been developing rapidly and producing large amounts of traffic data. Emerging big data-mining techniques enable the application of these data in a variety of ways. This study uses bus intelligent card (IC card) data and global positioning system (GPS) data to estimate passenger boarding and alighting stations. First, an estimation model for boarding stations is introduced to determine passenger boarding stations. Then, the authors propose an innovative uplink and downlink information identification model (UDI) to generate information for estimating alighting stations. Subsequently, the estimation model for the alighting stations is introduced. In addition, a transfer station identification model is also developed to determine transfer stations. These models are applied to Yinchuan, China to analyze passenger flow characteristics and bus operations. The authors obtain passenger flows based on stations (stops), bus lines, and traffic analysis zones (TAZ) during weekdays and weekends. Moreover, average bus operational speeds are obtained. These findings can be used in bus network planning and optimization as well as bus operation scheduling.     

基于CAN总线数据的LNG公交车能源 消耗分析

为研究公交车辆在正常运营中能源消耗的影响因素,通过CAN总线数据与公交IC 卡数据 的融合,从站点间断面以及站点两个层面对北京市液化天然气（LNG） 公交车辆的能源消耗影响 因素进行了相关分析。首先分析了不同道路等级下的能耗消耗,然后利用SPSS 的相关性分析工 具对能耗的影响因素进行了分析。通过分析发现,公交车辆在公交专用道路段的行驶速度约为非 公交专用道的1.7 倍,能源消耗约为无公交专用道的70%。能源消耗由高到低依次为辅路、匝 道、主干路。同时在站点层面,车辆的能源消耗主要受到停滞时间、车辆的加减速时间、乘客的 上下车人数的影响。期望通过此项研究能够帮助公共交通的运营和规划部门制定相应的政策,以 达到减少能源消耗的同时提高公共交通运行效率的目的。     

船舶区域配电监控系统模块设计

区域配电系统是一种新型的配电系统,可以简化电缆敷设工作,提高船舶生命力,降低船舶建造成本．本文根据区域配电系统的特点提出了区域配电监控系统模块的设计方案．以TMS320F2812DSP为现场监控模块的核心并采用c语言和汇编语言混合编程的方法开发下位机软件;以LabVIEW作为上位机系统开发平台;采用CAN总线作为上、下位机之间的通讯接口．该区域配电监控系统模块具有界面友好、操作简单、功能齐全和扩展方便等优点．     

On the capacity of isolated, curbside bus stops

The maximal rates that buses can discharge from bus stops are examined. Models were developed to estimate these capacities for curbside stops that are isolated from the effects of traffic signals. The models account for key features of the stops, including their target service levels assigned to them by a transit agency. Among other things, the models predict that adding bus berths to a stop can sometimes return disproportionally high gains in capacity. This and other of our findings are at odds with information furnished in professional handbooks.     

Adaptive control algorithm to provide bus priority with a pre-signal

In urban areas, where road space is limited, it is important to provide efficient public and private transportation systems to maximize person throughput, for example from a signalized intersection. To this end, this research looks at providing bus priority using a dedicated bus lane which is terminated upstream of the intersection, and placing an additional signal at this location, called a pre-signal. Although pre-signals are already implemented in some countries (e.g. UK, Denmark, and Switzerland), an adaptive control algorithm which responds to varying traffic demands has not yet been proposed and analyzed in the literature. This research aims to fill that gap by developing an adaptive control algorithm for pre-signals tailored to real-time private and public transportation demands. The necessary infrastructure to operate an adaptive pre-signal is established, and guidelines for implementation are provided. The relevant parameters regarding the boundary conditions for the adaptive algorithm are first determined, and then quantified for a typical case using a micro-simulation model. It is demonstrated with case studies that, under all considered scenarios, implementing a pre-signal with the proposed adaptive control algorithm will result in the least average person delay at the intersection. The algorithm is expected to function well with a wide range of car demands, bus frequencies, and bus passenger occupancies. Moreover, the algorithm is robust to errors in these input values, so exact information is not required.     

Bus arrival time calculation model based on smart card data

Bus arrival time is usually estimated using the boarding time of the first passenger at each station. However, boarding time data are not recorded in certain double-ticket smart card systems. As many passengers usually swipe the card much before their alighting, the first or the average alighting time cannot represent the actual bus arrival time, either. This lack of data creates difficulties in correcting bus arrival times. This paper focused on developing a model to calculate bus arrival time that combined the alighting swiping time from smart card data with the actual bus arrival time by the manual survey data. The model was built on the basis of the frequency distribution and the regression analysis. The swiping time distribution, the occupancy and the seating capacity were considered as the key factors in creating a method to calculate bus arrival times. With 1011 groups of smart card data and 360 corresponding records from a manual survey of bus arrival times, the research data were divided into two parts stochastically, a training set and a test set. The training set was used for the parameter determination, and the test set was used to verify the model’s precision. Furthermore, the regularity of the time differences between the bus arrival times and the card swiping times was analyzed using the “trend line” of the last swiping time distribution. Results from the test set achieved mean and standard error rate deviations of 0.6% and 3.8%, respectively. The proposed model established in this study can improve bus arrival time calculations and potentially support state prediction and service level evaluations for bus operations.     

Is rail cleaner and greener than bus?

The popular consensus is that urban passenger rail is more environmentally friendly than urban passenger bus. This position is largely associated with the key energy source for each mode, respectively electricity and diesel, where electric vehicle use will typically result in local air quality improvements away from the electricity generation source. Surveys of community perceptions reflect this sentiment; however the relationship between the source of energy and its resultant emissions is not something that citizens fully understand. There is a general lack of awareness of the resource base of much of electricity generation in some countries. Where generation sources are suitably renewable or low-carbon, electricity use will offer greenhouse gas abatement potential. However, in countries which still rely heavily on coal-fired power stations, such as Australia, abatement is not as assured and estimating emission outcomes can require careful assessment. Supporters of alternatives to diesel use can focus on the future supply of fossil-fuels, an argument which has merit; however such arguments are often confounded with environmental qualities related to local air pollution and enhanced greenhouse gas emissions. This paper takes a close look at the greenhouse emissions that are associated with urban rail and bus in Australia. Estimated intensities, when presented in the context of effective service delivery (primarily in terms of emissions per passenger kilometre), raise questions about the distortions that are present in the widespread promotion in Australia (at least) of rail as a more environmentally friendly and hence a sustainable mode of urban passenger transport than bus.