Travel time reliability is of increasing importance for travelers, shippers, and transportation managers because traffic congestion has become worse in major urban areas in recent years. To better evaluate the urban network-wide travel time reliability, five indices based on the emerging on-demand ride service data are proposed: network free flow time rate (NFFTR), network travel time rate (NTTR), network planning time rate (NPTR), network buffer time rate (NBTR), and network buffer time rate index (NBTRI). These indices take into account the probability distribution of the travel time rate (i.e., travel time spent for the unit distance, in min/km) of each origin-destination (OD) pair in the road network. We use real-world data extracted from DiDi-Chuxing, which is the largest on-demand ride service platform in China. For demonstrative purposes, the network-wide travel time reliability of Beijing is analyzed in detail from two dimensions of time and space. The results show that the road network is more unreliable in AM/PM peaks than other time periods, and the most reliable time period is the early morning. Additionally, we can find that the central region is more unreliable than other regions of the city based on the spatial analysis results. The proposed network travel time reliability indices provide insights for the comprehensive evaluation of the road network traffic dynamics and day-to-day travel time variations.

This paper proposes an improved multi-class dynamic network traffic flow propagation model with a consideration of physical queues. Each link is divided into two areas: Free flow area and queue area. The vehicles of the same class are assumed to satisfy the first-in-first-out (FIFO) principle on the whole link, and the vehicles of the different classes also follow FIFO in the queue area but not in the free flow area. To characterize this phenomenon by numerical methods, the improved model is directly formulated in discrete time space. Numerical examples are developed to illustrate the unrealistic flows of the existing model and the performance of the improved model. This analysis can more realistically capture the traffic flow propagation, such as interactions between multi-class traffic flows, and the dynamic traffic interactions across multiple links.

列车速度曲线优化是轨道交通系统中的重要问题，在确定列车能耗和出行时间方面起着至关重要的作用。鉴于实际运行环境的复杂性，系统存在的多种因素可导致能耗的不确定性。为合理刻画不确定性并生成鲁棒的速度曲线，本文构建了站间距离速度网络，并将与能耗有关的不确定性处理为基于离散样本数据的随机变量。进一步，将该问题构建为具有旅行时间阈值约束的随机约束最短路问题，其中期望总能消耗为目标函数。为生成近似最优解，提出了基于动态规划算法的拉格朗日松弛算法求解模型。数值算例验证了所提方法的有效性。

In large cities with heavily congested metro lines, unexpected disturbances often occur, which may cause severe delay of multiple trains, blockage of partial lines, and reduction of passenger service. Metro dispatchers have taken a practical strategy of rescheduling the timetable and adding several backup trains in storage tracks to alleviate waiting passengers from crowding the platforms and recover from such disruptions. In this study, we first develop a mixed integer programming model to determine the optimal train rescheduling plan with considerations of in-service and backup trains. The aim of train rescheduling is to frequently dispatch trains to evacuate delayed passengers after the disruption. Given the nonlinearity of the model, several linearization techniques are adapted to reformulate the model into an equivalent linear model that can be easily handled by the optimization software. Numerical experiments are implemented to verify the effectiveness of the proposed train rescheduling approach.

In the EU Horizon 2020 Shift2Rail Multi-Annual Action Plan, the challenge of railway maintenance is generating knowledge from data and/or information. Therefore, we promote a novel concept called “IN2CLOUD,” which comprises three sub-concepts, to address this challenge: 1) A hybrid cloud, 2) an intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related data acquired from the intelligent hybrid cloud. The concept is developed under the assumption that organizations want/need to learn from each other (including domain knowledge and experience) but do not want to share their raw data or information. IN2CLOUD will help the movement of railway industry systems from “local” to “global” optimization in a collaborative way. The development of cutting-edge intelligent hybrid cloud-based solutions, including information technology (IT) solutions and related methodologies, will enhance business security, economic sustainability, and decision support in the field of intelligent asset management of railway assets.

私营部门参与基础设施项目的建设或运营，有利于提高项目财务的可行性。公私合作关系（PPP）可利用私营公司的实力，将某些项目风险从公共部门转移到可更好处理这些风险的私营公司。在铁路和房地产联合开发的情况下，捆绑铁路和房地产开发（R＆HD）不仅使巨大的铁路建设成本与利润丰厚的房屋租赁收入之间进行交叉补贴，而且还提高了PPP模式的灵活性。其通过分配铁路和住房收入及成本，降低了公共和私营部门的内在风险。在本研究中，基于Ng和Lo（2015）的理论框架，我们将对各种PPP模式的鲁棒性进行研究。在人口或需求增长以及铁路建设成本不确定性的情况下，利益相关者的风险和回报如何受到各种PPP模式的影响？特定PPP模式的最终结果是什么？另外，随着时间的推移，高度波动的人口和铁路建设成本会如何改变最佳PPP模式？是否存在鲁棒的PPP模式？上述研究对管控风险可起到至关重要的作用，也有助于形成适用于铁路和房地产开发的有效PPP模式。

The overlap of bus and rail transit routes is common in China. This overlap provides passengers multiple choices for one trip. However, the availability of multiple options would cause uncertainty in the travel distribution of passengers. Given that buses and rail transits are becoming increasingly common, this paper aims to present the overlapped operation condition of bus and rail transit using a bi-level model from the perspective of bus operators. Frequency optimization model is established in the upper-level model. A heuristic algorithm called shuffled complex evolution (SCE-UA) method is used to solve the established frequency optimization model, and three other heuristic methods are compared with SCE-UA. A lower-level Logit model based on Agent simulation is set for traffic mode split. Data on the transit system in Dalian city are chosen as an example to test the feasibility of the model and the algorithm. Results show that as the overlapped optimization of bus route and rail transit routes changed primary bus frequency, the use of SCE-UA to solve such problems has evident advantages and feasibility; furthermore, changed bus frequency would improve bus operations.

This paper considers multiple perspectives to explore the concept of high-speed railway (HSR), rationally abstract its value formation mechanism, and quantitatively measure its actual performance. This paper analyzes the governance potential of major countries in the high-speed railway value chain and studies the feasible ways and development strategies to enhance the high-speed railway governance in China. Findings of this paper are as follows. First, the government, as the early manager of high-speed railway governance, has given way to Siemens and other integrated enterprises. Second, the high-speed railway standard output has become the core competitiveness that embodies high-speed railway. Third, the global high-speed railway market presents a hierarchical high-speed railway governance model and changes to a modular approach to governance.

日常生活中，双向行人流常见于人行道、人行横道和购物商场等。但是，行人运动的属性会受到步行设施的影响而发生变化。近年来，嘉年华活动中人潮涌动现象受到了研究者的广泛关注。行人在嘉年华活动中的行为与平时行走于通常步行设施中的行为不同，他们会被嘉年华的活动和展示所吸引，从而放慢甚至停止脚步。春节市场是香港传统的狂欢节活动，每年均会在农历新年前一周举行。香港最大的春节市场通常在维多利亚公园举办，此处很容易观测到人群的走动。在本研究中，我们进行了一项基于视频影像的观测调查，搜集维多利亚公园农历新年市场的行人流量及速度资料。利用所收集的数据，通过现存的数学模型进行校准，以捕捉相关宏观量之间的关系，从而提供对嘉年华活动中行人行为的洞察分析。本文使用先验数据，采用贝叶斯推理来校准模型。研究结果增强了对嘉年华活动中不同条件下人群行为的理解，有助于提高未来类似事件的安全性和效率。

如今，交通服务提供者将大量的车辆数据（FCD：浮动车数据）广泛用于道路网络交通状态的创建和播报中。作为第一个处理步骤，从全球定位系统（GPS）接收的所有原始位置数据必须在数字路线图中进行地图匹配，本文描述了GPS数据匹配过程的技术问题。之后，创建显示交通空间和时间状况的详细探测数据时空图,并采用数值实例说明了交通服务质量如何取决于匹配的GPS原始数据的数量。结果显示，当总交通流中2％的连接车辆以较短的时间间隔发送其GPS数据时，可以实现对当前交通阶段的高质量和精确重构。最后,将进行交通信息的转换，这些信息可发送到车辆导航系统中用于驾驶员信息和动态路线引导。