Accuracy of the Gothenburg congestion charges forecast

This paper explores the accuracy of the transport model forecast of the Gothenburg congestion charges, implemented in 2013. The design of the charging system implies that the path disutility cannot be computed as a sum of link attributes. The route choice model is therefore implemented as a hierarchical algorithm, applying a continuous value of travel time (VTT) distribution. The VTT distribution was estimated from stated choice (SC) data. However, based on experience of impact forecasting with a similar model and of impact outcome of congestion charges in Stockholm, the estimated VTT distribution had to be stretched to the right. We find that the forecast traffic reductions across the cordon and travel time gains were close to those observed in the peak. However, the reduction in traffic across the cordon was underpredicted off-peak. The necessity to make the adjustment indicates that the VTT inferred from SC data does not reveal the travellers’ preferences, or that there are factors determining route choice other than those included in the model: travel distance, travel time and congestion charge.     

An adaptive hawkes process formulation for estimating time-of-day zonal trip arrivals with location-based social networking check-in data

Location-Based Social Networking (LBSN) services, such as Foursquare, Facebook check-ins, and Geo-tagged Twitter tweets, have emerged as new secondary data sources for studying individual travel mobility patterns at a fine-grained level. However, the differences between human social behavioral and travel patterns can cause significant sampling bias for travel demand estimation. This paper presents a dynamic model to estimate time-of-day zonal trip arrival patterns. In the proposed model, the state propagation is formulated by the Hawkes process; the observation model implements LBSN sampling. The proposed model is applied to Foursquare check-in data collected from Austin, Texas in 2010 and calibrated with Origin-Destination (OD) data and time of day factor from Capital Area Metropolitan Planning Organization (CAMPO). The proposed model is compared with a simple aggregation model of trip purposes and time of day based on a prior daily OD estimation model using the LBSN data. The results illustrate the promising benefits of applying stochastic point process models and state-space modeling in time-of-day zonal arrival pattern estimation with the LBSN data. The proposed model can significantly reduce the number of parameters to calibrate in order to reduce the sampling bias of LBSN data for trip arrival estimation.     

Improving fuel consumption and CO2 emissions calculations in urban areas by coupling a dynamic micro traffic model with an instantaneous emissions model

Τhis study demonstrates the combination of a microscopic traffic simulator (AIMSUN) with an instantaneous emissions model (AVL CRUISE) to investigate the impact of traffic congestion on fuel consumption on an urban arterial road. The micro traffic model was enhanced by an improved car-following law according to Morello et al. (2014) and was calibrated to replicate measured driving patterns over an urban corridor in Turin, Italy, operating under adaptive urban traffic control (UTC). The method was implemented to study the impact of congestion on fuel consumption for the category of Euro 5 diesel <1.4 l passenger cars. Free flow and congested conditions led to respective consumption differences of −25.8% and 20.9% over normal traffic. COPERT 5 rather well predicted the impact of congestion but resulted to a much lower relative reduction in free flow conditions. Start and stop system was estimated to reduce consumption by 6% and 11.9% under normal and congested conditions, respectively. Using the same modelling approach, UTC was found to have a positive impact on CO₂ emissions of 8.1% and 4.5% for normal and congested conditions, respectively, considering the Turin vehicle fleet mix for the year 2013. Overall, the study demonstrates that the combination of detailed and validated micro traffic and emissions models offers a powerful combination to study traffic and powertrain impacts on greenhouse gas and fuel consumption of on road vehicles over a city network.     

Short-term traffic flow rate forecasting based on identifying similar traffic patterns

The ability to timely and accurately forecast the evolution of traffic is very important in traffic management and control applications. This paper proposes a non-parametric and data-driven methodology for short-term traffic forecasting based on identifying similar traffic patterns using an enhanced K-nearest neighbor (K-NN) algorithm. Weighted Euclidean distance, which gives more weight to recent measurements, is used as a similarity measure for K-NN. Moreover, winsorization of the neighbors is implemented to dampen the effects of dominant candidates, and rank exponent is used to aggregate the candidate values. Robustness of the proposed method is demonstrated by implementing it on large datasets collected from different regions and by comparing it with advanced time series models, such as SARIMA and adaptive Kalman Filter models proposed by others. It is demonstrated that the proposed method reduces the mean absolute percent error by more than 25%. In addition, the effectiveness of the proposed enhanced K-NN algorithm is evaluated for multiple forecast steps and also its performance is tested under data with missing values. This research provides strong evidence suggesting that the proposed non-parametric and data-driven approach for short-term traffic forecasting provides promising results. Given the simplicity, accuracy, and robustness of the proposed approach, it can be easily incorporated with real-time traffic control for proactive freeway traffic management.     

Congestion spill effects of Heathrow and Frankfurt airports on connection traffic in European and Gulf hub airports

We develop two stage fixed-effects single-spill and double-spill models for congestion connection spills of London Heathrow and Frankfurt airports on 9 hub airports in Europe and the Gulf. Our panel data covers connection traffic from 1997 to 2013 for Heathrow and 1997 to 2011 for Frankfurt. The single-spill results support strongly that the connection spills from Heathrow’s capacity limitations do strengthen competing hub airports of major alliance groups and to a lesser degree one Gulf hub. The double-spill model for Heathrow and Frankfurt shows nearly asymmetric overall spill characteristics between the two airports. Our results underline the influence of airline network strategies on congestion spills as European airline networks are shaped by alliances and umbrella mergers. Thus, the airline network perspective in airport capacity expansion decisions needs to play a greater role, as indicated by our asymmetric results for overall spill effects between Heathrow and Frankfurt airports.     

基于 DES 方法的张力腿平台主体结构水动力特性研究

考虑张力腿平台立柱和浮箱之间的相互影响,通过分离涡模拟法（DES）对均匀流下张力腿平台主体三维水动力流特性进行了研究,讨论了张力腿平台阻力系数、升力系数及其频谱、压力系数和尾涡等特性。研究表明：阻力系数和升力系数时历曲线变化具有一定的周期性和“脉动性”;下游立柱受到上游立柱尾涡作用,导致下游立柱阻力系数较上游立柱阻力系数略大;下游立柱升力系数幅值较上游立柱升力系数幅值大,下游立柱泄涡具有明显的周期性特点;升力系数时历变化呈现紊乱,频谱图中谱峰个数越多且带宽越大。立柱表面压力系数呈现出“W”型且张力腿平台主体周围具有不同垂向流态形式,稳定脱落周期下通过压力系数最大值判断撞击点等特殊位置,压力系数最小值判断尾涡所附位置;尾涡具有高度各向相异性,不同来流方向下张力腿平台主体尾后出现不同尾涡结构和流形态。     

广州智能交通指挥管理系统中拥堵管理策略研究

针对目前城市交通拥堵日益严重的情况，利用先进的技术手段及管理策略，是当今解决城市交通拥堵的一个发展趋势。本文以广州智能交通管理指挥系统项目为背景，研究在该项目中如何利用先进的拥堵管理策略进行城市拥堵区分和管理。     

基于设计模式的内容管理系统"多站点发布"设计

设计模式对当代的面向对象程序设计技术做出了巨大的贡献，为开发人员带来了福音。通过设计模式，程序的结构比以往更为有效。在内容管理系统“多站点发布”的设计中通过引入设计模式并对模式进行组合和简单实现不仅提高了系统设计的可重用性也避免了过分的设计，最终达到了设计与解决问题之间的最佳平衡。     

Public transport policy for central-city travel in the light of recent experiences of congestion charging

Excellent public transport which makes the private car a minority mode of central-city travel is a necessary condition for a political process towards the introduction of congestion charges. However, the charging system costs in London and Stockholm have proved to be unexpectedly high. Therefore, before these costs come down to an affordable level, zero-fares for central-city travel and stricter parking policy would be a first-best combination in many cities, always provided that the public transport is really competitive. A bold venture in public transport development is consequently the top priority irrespective of the transport pricing policy direction.     

Cruise port centrality and spatial patterns of cruise shipping in the Asian market

This paper investigates the centrality of cruise ports in the Asian cruise shipping market while proposing the hubs and authorities centrality (HACC) metric as a directional synthesis of the hubs centrality and authorities centrality to explore cyclical and directional features of centrality in the cruise shipping network. With the development of the cruise shipping industry, research has been actively conducted with a particular focus on identifying the characteristics of hub ports. This paper employs social network analysis to investigate the HACC which is originally developed for analyzing the cruise port centrality problem. Empirical study implies that Ho Chi Minh City, Hong Kong, Nagasaki, Penang, Phuket, Port Klang, Shanghai, and Singapore (in alphabetical order) reflects particulars of cruise hub ports. One of the exceptional results of this paper is Ho Chi Minh City, Penang, Phuket, and Port Klang have demonstrated high HACC (refers to hub ports) while limited degree and betweenness centrality. In contrast, Busan and Keelung are not classified as hub ports.