Distance and time in intermodal goods transport networks in Europe: A generic approach

This paper is about distance and time as factors of competitiveness of intermodal transport. It reviews the relevance of the factors, evaluates time models in practice, compares network distances and times in alternative bundling networks with geometrically varied layouts, and points out how these networks perform in terms of vehicle scale, frequency and door-to-door time. The analysis focuses on intermodal transport in Europe, especially intermodal rail transport, but is in search for generic conclusions. The paper does not incorporate the distance and time results in cost models, and draws conclusions for transport innovation, wherever this is possible without cost modelling. For instance, the feature vehicle scale, an important factor of transport costs, is analysed and discussed.Distance and time are important factors of competitiveness of intermodal transport. They generate (direct) vehicle costs and – via transport quality – indirect costs to the customers. Clearly direct costs/prices are the most important performance of the intermodal transport system. The relevance of quality performances is less clarified. Customers emphasise the importance of a good match between the transport and the logistic system. In this framework (time) reliability is valued high. Often transport time, arrival and departure times, and frequency have a lower priority. But such conclusions can hardy be generalised. The range of valuations reflects the heterogeneity of situations. Some lack of clarity is obviously due to overlapping definitions of different performance types.The following parts of the paper are about two central fields of network design, which have a large impact on transport costs and quality, namely the design of vehicle roundtrips (and acceleration of transport speed) and the choice of bundling type: do vehicles provide direct services or run in what we call complex bundling networks? An example is the hub-and-spoke network. The objective of complex bundling is to increase vehicle scale and/or transport frequency even if network volumes are restricted. Complex bundling requires intermediate nodes for the exchange of load units. Examples of complex bundling networks are the hub-and-spoke network or the line network.Roundtrip and bundling design are interrelated policy fields: an acceleration of the roundtrip speed, often desirable from the cost point of view, can often only be carried out customer friendly, if the transport frequency is increased. But often the flow size is not sufficient for a higher frequency. Then a change of bundling model can be an outcome.Complex bundling networks are known to have longer average distances and times, the latter also due to the presence of additional intermediate exchange nodes. However, this disadvantage is – inside the limits of maximal vehicle sizes – overruled by the advantage of a restricted number of network links. Therefore generally, complex bundling networks have shorter total vehicle distances and times. This expression of economies of scale implies lower vehicle costs per load unit.The last part of the paper presents door-to-door times of load units of complex bundling networks and compares them with unimodal road transport. The times of complex bundling networks are larger than that of networks with direct connections, but nevertheless competitive with unimodal road transport, except for short distances.     

Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use

The rapid development of information and communication technologies (ICT) has been argued to affect time use patterns in a variety of ways, with consequent impacts on travel behaviour. While there exists a significant body of empirical studies documenting these effects, theoretical developments have lagged this empirical work and in particular, microeconomic time allocation models have not to date been fully extended to accommodate the implications of an increasingly digitised society. To address this gap, we present a modelling framework, grounded in time allocation theories and the goods–leisure framework, for joint modelling of the choice of mode of activity (physical versus tele-activity), travel mode and route, and ICT bundle. By providing the expression for a conditional indirect utility function, we use hypothetical scenarios to demonstrate how our framework can conceptualise various activity–travel decision situations. In our scenarios we assume a variety of situations such as the implications of severe weather, the introduction of autonomous vehicles, and the interaction between multiple decision makers. Moreover, our approach lays the microeconomic foundations for deriving subjective values of ICT qualities such as broadband speed or connection reliability. Finally, we also demonstrate the means by which our framework could be linked to various data collection protocols (stated preference exercises, diaries of social interactions, laboratory experiments) and modelling approaches (discrete choice modelling, hazard-based duration models).     

Modelling cyclic container freight index using system dynamics

ABSTRACT

This paper investigates the cyclical nature of container shipping market represented by a containerized freight index and proposes a predictive cyclical model of the market. In contrast to the traditional spectral analysis (univariate), system dynamics reflect the drivers of the market in both supply and demand side, and therefore, it is a multi-variate system equilibrium approach consisting of various causal spillovers from sub-components of the market. This study is the first to analyze the cycle of container market using system dynamics. By utilizing system dynamics cyclicality approach, one-step ahead predictions are generated for monthly containerized freight index and compared to conventional benchmarks for post-sample validation. Our study can also help policymakers and shipping liners for better management and invest timing of container ship.     

不同方法对南黄海重现波高计算值的影响

采用SWAN波浪模型对江苏南黄海地区1979~2018年共40 a的波况进行模拟及验证,将模拟结果与实测资料进行比对,吻合良好。百年重现波高分布通过基于年极值和月极值的广义极值分布函数(GEV)和超阈值取值方法(POT)的广义帕累托分布模型(GP)计算得出。计算结果表明,不同方法的计算结果在辐射沙洲北部地区差别最大,采用月极值所得重现波高偏小,采用年极值计算的重现波高在辐射沙洲南北外围地区最大,其余地区则以POT方法为大值。在分别采用不同数据长度计算重现波高的试验中得出,取月极值的GEV分布计算结果对时间跨度的改变不敏感,而取年极值受之影响最大,POT方法介于两者之间。     

Leveraging social networks for efficient hurricane evacuation

One of the important factors affecting evacuation performance is the departure time choices made by evacuees. Simultaneous departures of evacuees can lead to overloading of road networks causing congestion. We are especially interested in cases when evacuees subject to little or no risk of exposure evacuate along with evacuees subject to higher risk of threat (also known as shadow evacuation). One of the reasons for correlated evacuee departures is higher perceived risk of threat spread through social contacts. In this work, we study an evacuation scenario consisting of a high risk region and a surrounding low risk area. We propose a probabilistic evacuee departure time model incorporating both evacuee individual characteristics and the underlying evacuee social network. We find that the performance of an evacuation process can be improved by forcing a small subset of evacuees (inhibitors) in the low risk area to delay their departure. The performance of an evacuation is measured by both average travel time of the population and total evacuation time of the high risk evacuees. We derive closed form expressions for average travel time for ER random network. A detailed experimental analysis of various inhibitor selection strategies and their effectiveness on different social network topologies and risk distribution is performed. Results indicate that significant improvement in evacuation performance can be achieved in scenarios where evacuee social networks have short average path lengths and topologically influential evacuees do not belong to the high risk regions. Additionally, communities with stronger ties improve evacuation performance.     

基于水平双向作用耦合曲线梁桥地震响应分析

以深圳市某互通立交匝道桥工程为背景,针对曲线梁桥地震响应的复杂性,运用大型结构分析程序Midas/Civil建立空间有限元模型,采用动态时程法对其进行地震响应分析,研究水平地震动单向输入、双向输入时墩梁固结曲线梁桥的地震响应差异,提出墩梁固结曲线梁桥抗震设计要点。     

The effect of railway local irregularities on ground vibration

The environmental effects of ground-borne vibrations generated due to localised railway defects is a growing concern in urban areas. Frequency domain modelling approaches are well suited for predicting vibration levels on standard railway lines due to track periodicity. However, when considering individual, non-periodic, localised defects (e.g. a rail joint), frequency domain modelling becomes challenging. Therefore in this study, a previously validated, time domain, three-dimensional ground vibration prediction model is modified to analyse such defects. A range of different local (discontinuous) rail and wheel irregularity are mathematically modelled, including: rail joints, switches, crossings and wheel flats. Each is investigated using a sensitivity analysis, where defect size and vehicle speed is varied. To quantify the effect on railroad ground-borne vibration levels, a variety of exposure–response relationships are analysed, including: peak particle velocity, maximum weighted time-averaged velocity and weighted decibel velocity. It is shown that local irregularities cause a significant increase in vibration in comparison to a smooth track, and that the vibrations can propagate to greater distances from the line. Furthermore, the results show that step-down joints generate the highest levels of vibration, whereas wheel flats generate much lower levels. It is also found that defect size influences vibration levels, and larger defects cause greater vibration. Lastly, it is shown that for different defect types, train speed effects are complex, and may cause either an increase or decrease in vibration levels.     

Should we all just stay home? Travel,out-of-home activities,and life satisfaction

How and why travel contributes to our life satisfaction is of considerable import for transportation policy and planning. This paper empirically examines this relationship using data from the American Time Use Survey. It finds that, controlling for relevant demographic, geographic, and temporal covariates, travel time per day is significantly and positively associated with life satisfaction. This relationship is attenuated, but still significant, when the amount of time spent participating in out-of-home activities is controlled for. Time spent bicycling is strongly associated with higher life satisfaction, though it attains significance only in some models; time spent walking is also quite positive, though it is not significant. However, both walking and bicycling are positively and significantly associated with life satisfaction when time spent on purely recreational walking and bicycling is included. Life satisfaction is positively and significantly associated with time spent traveling for the purposes of eating and drinking, religious activities, volunteering, and playing and watching sports. Travel time exhibits a strong positive relationship with life satisfaction in smaller towns and cities, but in large cities the association weakens, and for very large cities travel time may actually not be associated with life satisfaction at all. This may be due to the costs of traffic congestion, which disproportionately exists in large cities. In all, while the associations between travel and life satisfaction are clear, the causal story is complex, with the positive relationships potentially being explained by (1) travel allowing us to access destinations that make us happy, (2) the act of travel itself being fulfilling, and/or (3) intrinsically happier people being more likely to travel. In all likelihood, all three factors are at play.     

A hybrid heuristic strategy for liquefied natural gas inventory routing

As liquefied natural gas (LNG) steadily grows to be a common mode for commercializing natural gas, LNG supply chain optimization is becoming a key technology for gas companies to maintain competitiveness. This paper develops methods for improving the solutions for a previously stated form of an LNG inventory routing problem (LNG-IRP). Motivated by the poor performance of a Dantzig-Wolfe-based decomposition approach for exact solutions, we develop a suite of advanced heuristic techniques and propose a hybrid heuristic strategy aiming to achieve improved solutions in shorter computational time. The heuristics include two phases: the advanced construction phase is based on a rolling time algorithm and a greedy randomized adaptive search procedure (GRASP); and the solution improvement phase is a series of novel MIP-based neighborhood search techniques. The proposed algorithms are evaluated based on a set of realistic large-scale instances seen in recent literature. Extensive computational results indicate that the hybrid heuristic strategy is able to obtain optimal or near optimal feasible solutions substantially faster than commercial optimization software and also the previously proposed heuristic methods.     

城乡快速干道车-人冲突时间窗预测模型

为了解决城乡快速干道车-人冲突和事故严重的问题，将车-人冲突点的分析方法扩展到车-人冲突时间窗的分析方法，构建一种行人运动轨迹实时监测和穿越时间预测相结合的车-人冲突时间窗组合预测模型。首先，分析行人违规穿越的实测数据，确定不同类别行人对应的穿越时间置信区间以及松弛时间；其次，根据运动学模型的预测结果判断行人的所属类别并初步确定行人的穿越时间，同时通过卡尔曼滤波算法对行人穿越过程进行实时监测；再次，融合运动学模型预测结果和卡尔曼滤波监测结果，确定最终的车-人冲突时间窗；最后，对所提出的组合预测模型进行标定和验证，并通过VISSIM仿真平台进行安全性能测试。模型验证结果表明：在正常情况下，该模型能够保障行人的安全且能兼顾松弛时间重置次数；在行人初始穿越速度过低或穿越前、中期存在持续低速的情况下，该模型可以通过多次松弛时间重置来解决模型的适用性问题。安全性能测试结果表明，在车辆行驶时间均值增加4.7%的情况下，安全车辆数占比增加了37.3%，车辆的后侵占时间(PET)测试值则增加53.8%。因此，与无松弛时间的预测模型相比，所提出的有松弛时间的车-人冲突时间窗预测模型能够在对交通效率影响较小的前提下，较大程度地提高车-人冲突的安全性。