公交网络中的乘客需求预测系统和方法

公共交通工具,尤其是公交车服务,可以减少私家车的使用和燃油消耗,缓解交通拥堵和环境污染状况。当乘坐公交车时,乘客不仅关心等车时间,更在乎公交车的拥挤程度,过度拥挤的公交车会导致乘客放弃乘坐。可见,准确、实时、可靠的乘客需求预测可以帮助公交公司决定合理的公交发车时间间隔,并且可以减少乘客的等车时间,这是人们急切需要的。基于实际公交系统的大量数据,提出一个面向移动用户的乘客需求预测系统。该系统包括服务器端的信息数据流处理和挖掘程序,以及客户端的移动应用程序。然而,公交网络中的乘客需求预测存在三大挑战:不均匀性、突发性和周期性。为了解决这些问题,提出了3种预测模型和1种基于滑动窗口的框架来预测乘客的数目。开发了一个原型系统,该系统可运行在多个版本的Android移动手机上,22个月的连续实验证明,该系统能够对公交网络中的864110项乘客需求进行精确预测,其准确度超过78%。     

An empirical examination of factors influencing the intention to use mobile payment

With recent advances in mobile technologies, mobile commerce is having an increasingly profound impact on our daily lives, and beginning to offer interesting and advantageous new services. In particular, the mobile payment (m-payment) system has emerged, enabling users to pay for goods and services using their mobile devices (especially mobile phones) wherever they go. Mobile payment is anticipated to enjoy a bright future.     

Newspaper demand prediction and replacement model based on fuzzy clustering and rules

A problem that most newspaper companies encounter daily is how to predict the right number of newspapers to print and distribute among distinct selling points. The aim is to predict newspaper demand as accurately as possible to meet customer need and decrease loss, the number of newspaper offered but not sold. The right amount depends of the newspaper demand at different selling points and is a function of the geographical location and customer profile. Currently, demand prediction is based on values experienced in the past and on management knowledge. This paper suggests the use of predictive data mining techniques as a systematic approach to explore newspaper company database and improve predictions. Predictions require accurate forecast of the daily newspaper amount needed at each selling point. The focus of the paper is on a prediction method that uses fuzzy clustering for data base exploration and fuzzy rules together with performance scores of selling points for prediction. Experimental results using actual data show that the method is effective when compared with the current methodology, neural network-based predictors, and autoregressive forecasters. In particular, the predictive data mining technique improves on average 10% in comparison with the use of the existing approaches.     

Traffic congestion identification by combining PCA with higher-order Boltzmann machine

Traffic congestion identification is a popular research topic of intelligent transport systems. Identification rate of existing methods usually cannot meet the practical requirements. To improve the identification rate and reduce the computation cost, a novel intelligent identification method is proposed. The proposed method combines principal component analysis (PCA) method with higher-order Boltzmann machine (BM). PCA is used to reduce the dimension of input feature space. It can not only reduce the computation cost but also filter noise of the source data. BM is a kind of stochastic network that can obtain the global optimum solution. Higher-order BM without hidden units can save lots of computation cost without decreasing modeling power. The trained higher-order BM is used to identify traffic state. The efficiency of the proposed method is illustrated through analyzing Jinan urban transportation data. This work is partially supported by Shandong Province Special development funds on Information Industry (No. 2006R00042).     

Robust identification for multi-section freeway traffic models

1IntroductionIt is important to estimate the densityandspeed oftrafficfor the safetyandtraffic control .For decades ,manyresearchwork have been done to estimate traffic density, trafficvolume ,average speed,and other parameters[1,2] .Theproblemof estimating dynamic traffic has been involved inparts of those research work[1 ~4] .By means of O_Dmatrix,some researchers have also made a series of studiesof traffic prediction and traffic layout estimation[5] .However , most of the research work m…     

基于流量特征的网络流量预测研究

传统的非线性模型已经不再适用于网络流量建模,为了能够更精确地对网络流量建模,必须考虑到网络流量的特性。针对网络流量的自相似、长度分布、周期等特征进行分析,结合小波变换与时间序列模型,有效地建立流量预测模型。首先对流量的自相似和平稳性进行分析,并对长度、周期等特征进行描述,其次根据实际流量的自相似性和平稳性选择小波变换与时间序列相结合的方法进行建模,产生预测结果,最后根据长度与周期特征粗略判断预测的合理性。根据实验验证与分析,该方法具有极大的灵活性,相比单一的小波-FARIMA模型可以减少大量的运算,同时能够描述网络流量的短相关与长相关特性。     

The Prognosis of Acoustic Conditions in the Centre of Szczecinek

The article presents the results of traffic noise measurement research conducted in Szczecinek Center. The measurements were supported by European initiative called CIVITAS Reanissance. The measurements results were used for preparation of documents related to Sustainable Urban Transport Mobility Plan and Noise Action Plan. Traffic congestion is the main source of noise emission in the center Szczecinek. So there was a need to assess the noise emission level. Noise measurements were part of the measure implemented in Szczecinek during the CIVITAS project. It was made during implementation one of the ten measures implemented in Szczecinek. The main objectives of the measure were preparation and acoustic maps of the city center and prognosis the change of traffic noise in the future.     

基于CAN总线的移动机器人通信系统设计

近年来,对移动机器人的研究已成为热点,尤其是对移动机器人数据通信系统的研究。由于CAN总线技术具有网络功能,因此本文利用CAN总线构建了一个移动机器人的数据通信系统,使得机器人内部可以灵活地挂接多个功能模块。本文所设计的移动机器人具有动作模块、语音交互模块、避障与导航模块等。实验表明利用CAN总线技术可以提升移动机器人数据通信的可靠性和可扩展性。     

Robust identification for multi_section freeway traffic models

Since it is difficult to fit measured parameters using the conventional traffic model, a new traffic density and average speed model is introduced in this paper.To determine traffic model structures accurately, a model identification method for uncertain nonlinear system is developed.To simplify uncertain nonlinear problem, this paper presents a new robust criterion to identify the multi-section traffic model structure of freeway efficiently.In the new model identification criterion,numerically efficient U-D factorization is used to avoid computing the determinant values of two complex matrices.By estimating the values of U-D factor of data matrix, both the upper and lower bounds of system uncertainties are described. Thus a model structure identification algorithm is proposed.Comparisons between identification outputs and simulation outputs of traffic states show that the traffic states can be accurately predicted by means of the new traffic models and the structure identification criterion.     

A dynamic and automatic traffic light control expert system for solving the road congestion problem

Traffic congestion is a severe problem in many modern cities around the world. To solve the problem, we have proposed a framework for a dynamic and automatic traffic light control expert system combined with a simulation model, which is composed of six submodels coded in Arena to help analyze the traffic problem. The model adopts interarrival time and interdeparture time to simulate the arrival and leaving number of cars on roads. In the experiment, each submodel represents a road that has three intersections. The simulation results physically prove the efficiency of the traffic system in an urban area, because the average waiting time of cars at every intersection is sharply dropped when the red light duration is 65 s and the green light time duration is 125 s. Meanwhile, further analysis also shows if we keep the interarrival time of roads A, B, and C, and change that of roads D, E, and F from 1.7 to 3.4 s and the interdeparture times at the three intersections on roads A, B, and C are equal to 0.6 s, the total performance of the simulation model is the best. Finally, according to the data collected from RFID readers and the best, second and third best traffic light durations generated from the simulation model, the automatic and dynamic traffic light control expert system can control how long traffic signals should be for traffic improvement.     

面向交通流检测的Mean Shift多目标自适应跟踪算法

随着社会的发展,交通问题越来越严重,交通流检测技术是解决这一问题的重要途径,而目标跟踪又是交通流检测中必不可少的一部分。目前在目标跟踪领域Mean Shift算法是被广泛采用的技术,但是传统的Mean Shift跟踪算法计算量很大,难以实现交通流检测中的多目标实时追踪。鉴于此,提出一种基于线性预测的Mean Shift跟踪算法。该算法引入一个预测矢量,用来预测目标在下一帧可能出现的位置,在跟踪时算法从预测的位置开始迭代,直至收敛于目标真实位置。实验结果表明,该算法从很大程度上提高了原有算法的效率,有利于实时跟踪。而且,为了解决Mean Shift跟踪算法中核函数带宽自适应的问题,还提出了一种基于比较目标中心灰度比例变化来实现带宽自适应更新的新方法。     

电子政务需求研究综述*

试图从电子政务的定义从供给方向需求方的转变、电子政务的用户关系模式、服务内容、影响服务的因素、政府与企业和公民的互动、CRM及其在电子政务中的应用、需求研究的意义,以及需求研究在实际电子政务中的应用等角度对现有的文献进行研究。在此基础上对这些研究进行了评述,并提出了以后的研究方向。     

Safe design of mobile equipment traffic management systems

Designing and implementing safe, efficient and operator-centred traffic management systems for mobile equipment, other vehicles and pedestrians is of key importance in almost every industrial domain. Such systems rarely develop successfully on their own; whilst standards and guidelines do exist, they are often not stringently and comprehensively employed in all industrial settings, and additional guidance to managers responsible for traffic management would be beneficial.Building on models of the elements required for effective traffic management, the work described in this paper used a review of the literature, case studies from a variety of different industrial domains and operator-centred safe design processes to develop a set of 50 human element questions to help ensure mobile equipment safety. The process was iterative, and involved subject matter expert feedback, trialling the draft question set in an audit of several sites following a major incident and incorporating emerging findings about the possible use of new assistive technologies (such as collision detection systems).

Relevance to industry

In terms of industrial applications, the resultant question list can be used to identify potential problem areas, primarily safety but also partly inefficiency, regarding mobile equipment interactions with pedestrians, infrastructure or other equipment. Potential problem areas revealed could then undergo more detailed investigation and possible correction using risk assessment techniques or similar.     

Design of online auctions: Proxy versus non-proxy settings

Recent years have witnessed the rapid development of online auctions. Currently, some online auctions, such as eBay, introduce a proxy bidding policy, under which bidders submit their maximum bids and delegate to a proxy agent to automatically outbid other competitors for the top bidder, whereas other online auctions do not. This paper compares these two widely used auction mechanisms (proxy setting and non-proxy setting) and characterizes the equilibrium bidding behavior and the seller's expected revenue. We find the proxy auction outperforms the non-proxy auction in terms of the seller's expected revenue. This dominance result is not prone to the specific bid announcement policy, the bidder's knowledge regarding the number of bidders, the impact of traffic congestion along the bidding process, the number of items sold through the auction, and the existence of a reserve price.We further find that the proxy setting usually fails to sustain the truthful bidding as a dominant strategy equilibrium even if no minimum bid increments are adopted, and the possibility of a low-valuation-bidder dilemma where the low-valuation bidders could be better off if all bidders collude to bid at the last minute. We also discuss the dramatically different equilibrium bidding behaviors under the two auction mechanisms.     

交通拥挤控制的实时决策支持模型

针对交通拥挤的快速检测和控制问题,设计了一种基于管理者知识和经验,能够实时反映交通拥挤状况的决策支持模型．设计的自动决策支持模型中包含了概念模型和推理模型,推理模型中集成了交通拥挤自动检测算法和拥挤交通量控制方案选择的模糊推理算法．研究结果表明,采用自动决策支持模型能在一定程度上取代交通管理者对拥挤的管理,从而提高拥挤管理的效率和决策质量．     

交通诱导预测控制仿真研究

将动态交通分配实施过程纳入预测控制框架下以满足实时交通诱导的目的,提出一种交通诱导预测控制算法．该算法是在滚动时域基础上进行的,包括实时交通分配、交通流模拟运行及评价以及进化最佳路径３ 个重要环节．仿真结果表明,交通诱导预测控制是一种良好的计算机控制方法学,其优化过程预先考虑了目前交通分配对未来路网的影响,因而可有效地防范交通拥堵,实现考虑反馈的路网交通流实时分配优化,同时为出行者提供最佳路径．