快速路可变限速与匝道控制协同优化策略

可变限速控制和匝道控制是快速路交通控制的主要手段,本文对两者的协同优化策略进行了研究.借助智能车路协同系统强大的信息感知能力,通过引入微观交通流信息,对经典METANET模型进行了改造,构建了可变限速控制影响下的微观METANET模型,实现了一种新的可变限速控制策略,同时,采用ALINEA算法,对入口匝道进行了优化控制,实现了两者的协同优化.最后,基于实际道路和交通流数据搭建了仿真平台,对微观METANET模型和协同优化策略的有效性进行了验证.仿真结果表明,微观METANET模型具有良好的交通流预测效果,协同优化策略能有效地改善快速路交通流状态.     

Public protests against the Beijing–Shenyang high-speed railway in China

With the rapid expansion of the high-speed railway infrastructure in China, conflicts arise between the interests of local citizens living along the planned tracks and the national interests of governmental authorities and project developers. This paper addresses questions of why and how Chinese citizens mobilize for and participate in protests against high-speed railway projects and to what effect. To this end, a comprehensive study was conducted on the decision-making process, public opinions, and protest actions regarding the plans and site choices for the Beijing–Shenyang high-speed railway from 2008 to 2013, combining quantitative and qualitative methods. In general, local residents are supportive of high-speed railway project construction, but they contest the closed decision-making process and the poor design and siting choices for the track by governmental authorities and companies. After four years of resident protests through formal complaints, lobbying, protest demonstrations, organizing alternative opinion polls, and discussions with authorities, citizens were partially successful in changing the siting of the track, adding protective measures (e.g., tunnels and sound screens), and saving green belts. Two conclusions can be drawn from this case study. First, regardless of the growing legal requirements, public participation in major projects in China is far from a standard practice. Final citizen participation is often preceded by serious conflict. Second, with defined good governance boundaries, there is increasing room for public participation in environmental movements, which does influence final decisions.     

Expertise in decision-making for large infrastructure projects: from UK trunk roads to High Speed Rail 2

At the decision-making stage, a large-scale infrastructure project is essentially a broad concept, and this means the expert analyses will differ from each other and become contested over time, leading to the emergence of rival narratives. It is only where there is a limited range of expert analyses that the bases for decision-making will remain relatively clear-cut. Over time the contested nature of expertise can significantly inhibit the construction of effective narratives, either for or against the project, and also make decision-making more complex and problematic. Decision makers may also seek greater clarification through the construction of narratives that rise above these disputed areas of expertise, and the scientific evidence becomes less important. This paper examines the changing nature of contested expertise through a comparative analysis of political decision-making between UK trunk roads policy and the case of High Speed Rail 2, through the framework of epistemic communities.     

Challenges and Benefits in the Design of Coastal Walking and Cycling Amenities: Toward a More Integrated Coastal Management Approach

The planning and development of pedestrian and cycling amenities in coastal urban environments is a challenging process because a wide range of policies and considerations must be taken into account. Among these, the concepts of sustainability and more recently, resilience, have been gaining prominence. Green Infrastructure design approaches can integrate aspects of both sustainability and resilience, providing multiple services within single development projects. This study focuses on Dublin and examines a range of amenity projects at various stages of development that relate to the provision of new coastal walking and/or cycle routes. These are initially contextualized at the city level before focusing specifically on challenges and benefits associated with the design and implementation of such projects. Based on our findings, recommendations are made for optimizing the potential of future projects to effectively integrate with other initiatives so as to deliver broader policy objectives. A simple sequential model is presented that should assist developers and decision-makers to take a more integrated, multidisciplinary approach to meeting policy goals when planning and developing coastal amenities. Finally, this is remodeled into a set of considerations that are generally applicable to coastal development proposals of significant scale.     

Estimating economic and resilience consequences of potential navigation infrastructure failures: A case study of the Monongahela River

The paper examines the potential effects of failure of heavily used, outdated locks and dams on the Monongahela River in southwestern Pennsylvania. Catastrophic failure would result in lengthy outage of barge traffic. The displaced volume of coal shipments from mines to power plants is estimated using Energy Information Administration survey data. The resilience of the impacted facilities, the viability of their shipping alternatives, and their ability to re-organize into new markets is assessed. Lost revenues are estimated for facilities that close due to an inability to adapt, as well as the replacement cost of towboats and barges trapped by a catastrophic and sudden failure. The aggregate costs to these facilities as a result of a year-long closure are estimated at $0.56-1.7 billion.     

The price of uncertainty in pavement infrastructure management planning: An integer programming approach

Currently there is a true dichotomy in the pavement maintenance and rehabilitation (M&R) literature. On the one hand, there are integer programming-based models that assume that parameters are deterministically known. On the other extreme, there are stochastic models, with the most popular class being based on the theory of Markov decision processes that are able to account for various sources of uncertainties observed in the real-world. In this paper, we present an integer programming-based alternative to account for these uncertainties. A critical feature of the proposed models is that they provide – a priori – probabilistic guarantees that the prescribed M&R decisions would result in pavement condition scores that are above their critical service levels, using minimal assumptions regarding the sources of uncertainty. By construction of the models, we can easily determine the additional budget requirements when additional sources of uncertainty are considered, starting from a fully deterministic model. We have coined this additional budget requirement the price of uncertainty to distinguish from previous related work where additional budget requirements were studied due to parameter uncertainties in stochastic models. A numerical case study presents valuable insights into the price of uncertainty and shows that it can be large.     

A competing Markov model for cracking prediction on civil structures

Cracks on the surface of civil structures (e.g. pavement sections, concrete structures) progress in several formations and under different deterioration mechanisms. In monitoring practice, it is often that cracking type with its worst damage level is selected as a representative condition state, while other cracking types and their damage levels are neglected in records, remaining as hidden information. Therefore, the practice in monitoring has a potential to conceal with a bias selection process, which possibly result in not optimal intervention strategies. In overcoming these problems, our paper presents a non-homogeneous Markov hazard model, with competing hazard rates. Cracking condition states are classified in three types (longitudinal crack, horizontal crack, and alligator crack), with three respective damage levels. The dynamic selection of cracking condition states are undergone a competing process of cracking types and damage levels. We apply a numerical solution using Bayesian estimation and Markov Chain Monte Carlo method to solve the problem of high-order integration of complete likelihood function. An empirical study on a data-set of Japanese pavement system is presented to demonstrate the applicability and contribution of the model.     

旅游交通融合发展研究——以福建省为例

为深入落实"交通强国"战略和实现"全域旅游"目标,推动旅游与交通深度融合发展,需做好旅游交通体系发展的顶层设计。通过分析旅游交通面临的问题,提出了旅游交通融合发展的理念。将福建省作为案例,针对福建旅游交通网络面临的问题,提出了"快旅慢游"旅游交通体系的建设目标、实施方案及保障措施。依托高铁、民航、邮轮和公路等综合立体交通网络,提出了"一带三环多放射"旅游交通"快旅"通道的发展思路;通过特色旅游产品开发、旅游服务质量提升等方面,规划了"慢游"微循环旅游交通的发展方案,构建了福建省多层次、综合立体的旅游交通体系发展新格局。以期通过福建省旅游交通融合发展案例研究,为其他省市旅游交通融合发展借鉴参考。     

Analyzing passenger train arrival delays with support vector regression

We propose machine learning models that capture the relation between passenger train arrival delays and various characteristics of a railway system. Such models can be used at the tactical level to evaluate effects of various changes in a railway system on train delays. We present the first application of support vector regression in the analysis of train delays and compare its performance with the artificial neural networks which have been commonly used for such problems. Statistical comparison of the two models indicates that the support vector regression outperforms the artificial neural networks. Data for this analysis are collected from Serbian Railways and include expert opinions about the influence of infrastructure along different routes on train arrival delays.