A fresh look at zero-rating

We provide an economic assessment of zero-rating offers in the context of mobile internet access services and draw six lessons: (1) Zero-rating can have several different characteristics that crucially affect their economic and welfare assessment. Thus, regulatory interventions must be based on a careful case-by-case analysis. (2) In the context of zero-rating offers, it is often crucial to evaluate the extent to which users are able to activate and deactivate a (throttled) zero-rated tariff option. If activation/deactivation is easy and instantaneous, a sound economic theory of harm for consumers will in many cases be hard to establish. (3) Similarly, if access to zero-rated partner programs is non-discriminatory and entails low barriers to entry, a sound theory of harm for content providers will usually not be given. (4) Zero-rating can be beneficial for consumers and (legal) content providers alike by contributing to a reduction of illegal content. Combined with throttling it can mitigate congestion problems. However, by requiring all content belonging to the same content category to be treated equally with respect to throttling, independent of whether a content provider opted for zero-rating or not, the existing regulation creates a negative externality on those content providers that do not wish to be zero-rated for some reason. (5) Particular attention should be paid to the impact of throttled zero-rating tariffs on the competition between mobile network operators (MNOs) and MVNOs. The latter may not be able to compete on equal footing with MNOs, because they benefit less from the traffic management aspects of zero-rating. (6) Competition among (infrastructure-based) ISPs provides a safeguard against severe rent extraction and, thus, an abuse of throttling and zero-rating as an exploitative device. Therefore, regulators should carefully account for the competitive environment and the existing tariff portfolio and options before deciding to intervene. Competition policy, rather than ex-ante regulation, may be more suitable for this task.     

杭州西湖景区游客集散的优化对策

景区的设计与规划总是在追求人与景区环境之间的和谐。高效的游客集散方案,不仅能提升景区的游客接待量,更重要的是能让游客享受美丽的自然风光和浓厚的人文气息。杭州西湖景区因其独特的地理位置、优美的自然风光和浓厚的文化底蕴,吸引着海内外游客。逐年增长的游客量对西湖景区的游客集散能力、车辆通行情况以及停车场设施的配套提出了严峻的挑战。基于对游客游览目的性的调查和景区主要交叉口交通量的实地观测,对杭州西湖景区游客集散能力现状及存在的问题进行了深入分析,并从进入景区主要交叉口的车流量、停车场配置、公共自行车运用等方面提出了提升景区游客集散能力的优化对策。     

基于流数据挖掘的网络流量异常检测及分析研究

网络流量异常检测及分析是网络及安全管理领域的重要研究内容。本文探讨了网络流量异常的种类、网络流量异常检测的方法,分析了基于传统检测方法在网络流量异常检测应用中存在的问题。并重点对基于流数据模型的网络流量异常检测进行了研究,综述了已有流数据挖掘研究方法在网络流量异常检测中的研究进展。最后,本文对现有研究工作存在的问题及未来的研究方向进行了探讨。     

Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration

The Federal Aviation Administration has several tools in its arsenal to manage traffic flows. However, it is very difficult to assess with certainty the impact of traffic flow management procedures such as Time-Based Flow Management (TBFM) or Traffic Management Initiatives (TMI) on airport performance because operational data are not readily available to analysts. This study uses the case of Fort Lauderdale–Hollywood International Airport (FLL) where traffic flow management procedures have been implemented to manage a reduction of airport capacity due to runway constructions. Based on an Autoregressive Conditional Duration (ACD) model, the analysis shows that the use of traffic flow management procedures contributed to reducing the volatility of interarrival duration whether separation relies on time-metering (TBFM) or distance between aircraft (TMI). The lessons learned from this case study may have important implications for airports whose available capacity is severely constrained.     

基于径向基神经网络的铁路短期客流预测

在分析径向基神经网络原理和铁路客流时序特征的基础上,建立基于径向基神经网络的铁路短期客流预测模型,通过径向基神经网络把客运量的年规律、周规律等时间属性有机结合,有效解决客流数据的复杂性和非线性问题。以T15次列车为例进行硬座席别的客运量预测结果表明,径向基神经网络预测模型对铁路短期客流的预测效果较好。     

基于傅里叶级数的铁路客运量预测研究

基于傅里叶级数预测模型,以我国2004—2009年铁路客运量为数据基础,通过将时间序列划分为趋势性与季节性部分,分别采用最小二乘法与傅里叶级数法对两者进行拟合,应用Matlab软件编程,求出预测模型,并进行客运量预测。通过对预测结果的误差分析,结果表明:采用傅里叶级数预测法预测我国铁路客运量的效果较好。     

Traffic exposure near the Los Angeles–Long Beach port complex: using GPS-enhanced tracking to assess the implications of unreported travel and locations

Traffic exposure assessments could misclassify the extent and locations of exposure if traditional recall surveys and self-reported travel diaries do not record all participant activities. The Harbor Communities Time Location Study (HCTLS) examines the nature, extent and implications of underreported locations/trips in a case study which used portable Global Positioning Systems (GPS) devices to track the diurnal patterns and traffic exposure of 47 residents of communities near the Los Angeles–Long Beach port complex. Participants were similar to adults nationwide in time spent indoors, in-vehicle, and outdoors, but spent more time indoors at home (78% vs. 66%). Overall, participants did not report nearly half (49%) of the locations and trips identified in GPS-enhanced data on their activity diaries, resulting in about 3 h/day in unreported locations and 0.6 h/day in unreported trips. The probability of a location/trip being underreported was systematically correlated with participant and location/trip characteristics. Self-reported data missed about 50 min of heightened air pollution exposures during the 5 h/day on average participants spent in high-traffic areas and about 30 min during the 4 h/day near truck routes. GPS-enhanced methods provide opportunities to more precisely characterize exposure periods and tools to identify facility, roadway, and land use types of the greatest concern for mitigation efforts.     

基于可靠性计算的编组站车流预估方法研究

编组站阶段计划作为编组站作业计划的核心,对编组站高效完成运输生产任务具有重要作用。然而编组站阶段计划的编制通常受限于到达车流的时间不确定性和车流信息的不准确性,为提高自动编制阶段计划的准确性,研究一种依据车流实际确报信息对预报信息进行准确性评价、并且根据站内车流和带有准确性评价的到达车流进行车流自动推算的方法。在量化车流可靠性参数评估和列车平均运行时间评估的基础上构建模型,并提出相应的算法,随着系统运行过程中车流信息的不断积累和可靠性评价参数的动态更新,通过模拟调度人员对车流分配的思考过程实现到发车流的自动推算和分配。该方法可以有效提升车流推算的准确程度,提高自动编制的阶段计划的可用性。     

基于改进优劣解距离法的枢纽内客运站能力利用协调度评价

针对枢纽内多个客运站能力利用评价问题,以枢纽内设施能力利用匹配度指标、列车作业组织协调度指标、城市交通接驳适应度指标的耦合计算值定义多个客运站能力利用协调度指标,根据耦合度理论构建基于改进优劣解距离法的枢纽内多个客运站能力利用协调度计算模型,并结合熵权法求解枢纽内多个客运站能力利用协调度。以沈阳铁路枢纽2018年、2019年运行图为例对给出的评价方法进行验证,结果表明:提出的基于改进优劣解距离法的能力利用协调度评价模型可以有效解决枢纽内多个客运站能力利用评价和优化问题,提升运力资源配置效率、减少资源闲置、满足旅客高品质出行体验,为方案比选及预先研判提供技术支持。     

Assessing the Influence of Traffic Impact Assessments on Land Use Development and Decision Making

Rapid urbanisation and land use planning in cities and countries worldwide have an impact on traffic related risks to society as a whole. Strategic planning decisions made during land use development approvals can affect the performance of transport infrastructure significantly impacting on community safety. One major contributor to the decision-making process is Traffic Impact Assessment （TIA） undertaken prior to development approval. The content of each TIA process differs according to the type of development and its geographical location. The paper presents a brief overview of the strategic decision-making process adopted in Australia in land use development approvals. Using a selected case study area, the importance of the TIAs to the decision-making process is demonstrated. Further, the paper presents the observed differences between the facts presented in TIAs completed by four different consultants and the influence of the new development in the community safety. Traffic records after the new development indicate that the accidents have almost doubled after the new development. It is noted that the current TIA process requires significant changes to ensure that the influence of the land use development decisions are captured correctly to ensure informed strategic decision-making. A set of recommendations to overcome the shortcomings of existing planning and TIA designing process is presented.