Empirical estimation of price and income elasticities of air cargo demand: The case of Hong Kong

This paper estimates the price and income elasticities of air cargo demand and examines how they may change after the 2008 financial crisis. Using a set of time series data, we simultaneously estimate the aggregated demand and supply functions of air cargo at Hong Kong International Airport (HKIA). We find that during the entire sampling period of 2001–2013, the price elasticity for air cargo transport demand at HKIA ranges from −0.74 to −0.29, suggesting that air cargo demand in Hong Kong reacts negatively to price (as expected) but does not appear to be very sensitive to price. The income elasticity ranges from 0.29 to 1.47 and appears sensitive to seasonality adjustment approaches. However, in terms of the speed of changes, air cargo demand changes much faster than overall economy, indicating the presence of a pro-cyclical pattern of air cargo traffic with respect to the overall economy. Our analysis shows that air cargo demand becomes more sensitive to changes in both price and income after 2008.     

武汉港阳逻港区多式联运发展思路

多式联运能够充分发挥各种运输方式的综合优势,对于推动物流业降本增效、完善现代综合交通运输体系具有积极意义。武汉港阳逻港区具备发展多式联运的各项要素,但缺乏对多式联运发展的系统性规划,港区多式联运发展相对滞后,综合交通优势尚未有效发挥。通过总结典型案例的发展经验,结合港区内外部综合因素,思考港区多式联运发展思路,探讨港区多式联运的布局规划以及综合服务的提升,并提出相关建议。     

Fractional-order-based ACC/CACC algorithm for improving string stability

Traffic flow optimization and driver comfort enhancement are the main contributions of an Adaptive Cruise Control (ACC) system. If communication links are added, more safety and shorter gaps can be reached performing a Cooperative-ACC (CACC). Although shortening the inter-vehicular distances directly improves traffic flow, it can cause string unstable behavior. This paper presents fractional-order-based control algorithms to enhance the car-following and string stability performance for both ACC and CACC vehicle strings, including communication temporal delay effects. The proposed controller is compared with state-of-the-art implementations, exhibiting better performance. Simulation and real experiments have been conducted for validating the approach.     

Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology,application and impact evaluation

This paper illustrates a ride matching method for commuting trips based on clustering trajectories, and a modeling and simulation framework with ride-sharing behaviors to illustrate its potential impact. It proposes data mining solutions to reduce traffic demand and encourage more environment-friendly behaviors. The main contribution is a new data-driven ride-matching method, which tracks personal preferences of road choices and travel patterns to identify potential ride-sharing routes for carpool commuters. Compared with prevalent carpooling algorithms, which allow users to enter departure and destination information for on-demand trips, the proposed method focuses more on regular commuting trips. The potential effectiveness of the approach is evaluated using a traffic simulation-assignment framework with ride-sharing participation using the routes suggested by our algorithm. Two types of ride-sharing participation scenarios, with and without carpooling information, are considered. A case study with the Chicago tested is conducted to demonstrate the proposed framework’s ability to support better decision-making for carpool commuters. The results indicate that with ride-matching recommendations using shared vehicle trajectory data, carpool programs for commuters contribute to a less congested traffic state and environment-friendly travel patterns.     

The generators of paratransit trips by persons with disabilities

Identifying the generators of paratransit trips by persons with disabilities is important to comprehend the current demand patterns and forecast future demand. Only a handful of studies have been conducted so far to identify the generators of paratransit trips and most focused on the home end of the trips. Given some of the inconsistencies in past studies and the scarcity of studies on the generators of trips away from home, this study attempts to identify the generators of paratransit trips beginning and ending at clients’ homes and away from home. It uses an extremely large dataset consisting of 1.91 million trips made by NJ TRANSIT’s Access Link clients, socioeconomic data from the American Community Survey, employment data from the Longitudinal Employer-Household Dynamics, and establishment data from Dun and Bradstreet. The analytical methods include an ordinary least squares model (OLS) and several spatial generalized linear mixed models (GLMM) to identify the characteristics of census block groups associated with Access Link trip generation at home and away from home, Geographic Information System (GIS) analysis to identify the types of establishments located in the immediate vicinity of drop-offs, and a multinomial logit model (MNL) to examine the relationship between the characteristics of the establishments in the vicinity of drop-offs and the characteristics of the dropped-off clients. Together, the various analyses provide useful insights about paratransit trip generators at the macro and micro levels. Some implications of the findings are discussed.     

对农村金融的差异需求与分层供给行为选择的模型分析——基于机制设计理论的视角

文章基于机制设计理论的思想和框架,建立了农村金融市场上差异需求与分层供给行为选择的相关约束机制模型,分析了相关约束机制变量对农村金融供求行为选择的影响,从而提出了通过进一步改进和完善农村金融市场相关机制变量,促进我国农村金融供求者的匹配性行为选择,改善农村金融市场效率,加强金融对“三农”支持力度的政策建议。     

四川旅游资源交通系统综合布局分析

作为影响旅游活动的重要因素之一,交通布局直接关系到旅游业的发展。本文根据四川旅游资源的现状、地理位置等情况,将四川划分出三大旅游经济圈,从各旅游经济圈交通现状及客流特征入手,利用关联分析的方法,结合数据对比,剖析了各旅游经济圈与交通的关联。最后,在整合四川旅游资源的前提下,得出了四川旅游资源交通系统综合布局的相关结论。     

突发大规模需求下铁路军事运输保障研究

以"5·12"汶川地震为背景,分析了突发大规模需求下铁路军事运输保障的特点及要求,提出了应急铁路军事运输保障的具体对策,如建立健全铁路军事运输指挥机制、制订输送保障运行计划等,对铁路军事运输部门提高突发大规模需求情况下的运输保障能力具有借鉴意义.