基于变权可拓物元的铁路“走出去”公私合营项目风险决策

针对铁路“走出去”公私合营(PPP)项目的风险评估决策需求，提出一种基于变权可拓物元模型与累积前景理论的风险决策方法。在构建风险评价指标体系的基础上，通过经典域、节域矩阵及待评物元等级量化值综合确定各风险指标的组合权重。考虑决策者损失规避、收益偏好等心理特征，结合变权理论与贴近度准则，从损益角度综合确定风险决策参考点，基于蒙特卡洛模拟构建风险决策价值函数与概率权重函数，通过敏感性分析对不同风险指标取值下累积前景值的相应变化进行探讨，并以实际铁路“走出去”PPP项目为例进行风险评估决策。相应分析结果表明，所提出的风险决策方法能够有效识别铁路“走出去”PPP项目建设运营过程中面临的关键风 险，判别项目风险等级贴近度，并为铁路企业与政府机构进行风险决策提供参考。     

Data-driven optimization of railway maintenance for track geometry

Railway big data technologies are transforming the existing track inspection and maintenance policy deployed for railroads in North America. This paper develops a data-driven condition-based policy for the inspection and maintenance of track geometry. Both preventive maintenance and spot corrective maintenance are taken into account in the investigation of a 33-month inspection dataset that contains a variety of geometry measurements for every foot of track. First, this study separates the data based on the time interval of the inspection run, calculates the aggregate track quality index (TQI) for each track section, and predicts the track spot geo-defect occurrence probability using random forests. Then, a Markov chain is built to model aggregated track deterioration, and the spot geo-defects are modeled by a Bernoulli process. Finally, a Markov decision process (MDP) is developed for track maintenance decision making, and it is optimized by using a value iteration algorithm. Compared with the existing maintenance policy using Markov chain Monte Carlo (MCMC) simulation, the maintenance policy developed in this paper results in an approximately 10% savings in the total maintenance costs for every 1 mile of track.     

基于灰色聚类评估法的城市交通安全评价研究

根据影响城市道路交通安全的各个因素,建立一套安全评价指标体系.运用灰色聚类方法进行安全评价,建立评价模型,并运用该模型对石家庄市城市道路交通进行安全评价,得到更符合实际安全现状的评价结果.     

基于知识库的舰船应急抢修决策支持系统研究

文章针对舰船战损抢修时间紧迫、战场环境复杂的特点,研究建立了基于知识库的舰船战损抢修决策支持系统开发方案,并对系统知识库的构建方法及基于知识库的抢修决策方法等关键技术进行了深入研究,在此基础上开发了基于知识库的舰船战损抢修决策支持系统。文章可为舰船战损抢修决策水平的提高奠定一定的基础,同时也将为舰船战损抢修决策的信息化和智能化提供一定的参考。     

基于效用的目标分配贝叶斯风险决策模型研究

通过建立的贝叶斯风险决策模型并进行案例分析,将贝叶斯决策理论运用到战场目标分配决策分析中,结果表明运用贝叶斯风险可以提高决策的准确程度,降低了决策的风险程度,证明了决策模型具有实用性和有效性。     

Traffic evacuation simulation based on multi-level driving decision model

Traffic evacuation is a critical task in disaster management. Planning its evacuation in advance requires taking many factors into consideration such as the destination shelter locations and numbers, the number of vehicles to clear, the traffic congestions as well as traffic road configurations. A traffic evacuation simulation tool can provide the emergency managers with the flexibility of exploring various scenarios for identifying more accurate model to plan their evacuation. This paper presents a traffic evacuation simulation system based on integrated multi-level driving-decision models which generate agents’ behavior in a unified framework. In this framework, each agent undergoes a Strategic, Cognitive, Tactical and Operational (SCTO) decision process, in order to make a driving decision. An agent’s actions are determined by a combination, on each process level, of various existing behavior models widely used in different driving simulation models. A wide spectrum of variability in each agent’s decision and driving behaviors, such as in pre-evacuation activities, in choice of route, and in the following or overtaking the car ahead, are represented in the SCTO decision process models to simulate various scenarios. We present the formal model for the agent and the multi-level decision models. A prototype simulation system that reflects the multi-level driving-decision process modeling is developed and implemented. Our SCTO framework is validated by comparing with MATSim tool, and the experimental results of evacuation simulation models are compared with the existing evacuation plan for densely populated Beijing, China in terms of various performance metrics. Our simulation system shows promising results to support emergency managers in designing and evaluating more realistic traffic evacuation plans with multi-level agent’s decision models that reflect different levels of individual variability of handling stress situations. The flexible combination of existing behavior and decision models can help generating the best evacuation plan to manage each crisis with unique characteristics, rather than resorting to a fixed evacuation plan.     

航空公司安全管理绩效动态提升机制

为解决航空公司安全管理决策短期化、滞后化问题,有效提升其安全管理水平,在民航安全管理理论系统分析的基础上,深入挖掘安全管理绩效要素及其影响路径,构建了航空公司安全管理绩效系统动力学模型。通过专家访谈法确定了各要素指标间的影响关系及其权重,并运用VENSIM软件对模型进行了仿真,结果表明:当航空公司安全管理绩效达到某种程度后,其提升速率呈减缓趋势,需及时调整安全投入策略;此时安全政策和目标、安全监督检查、安全保障资源和安全沟通可作为未来提升安全管理绩效的最佳干预策略组合,为航空公司的安全管理决策提供科学依据。     

Analyzing the transition from a public bicycle system to bicycle ownership: A complex relationship

Despite the success achieved by Public Bicycle Sharing Systems (PBSS) across the world, several researchers provide evidence on their limitations and constraints in a medium-long term, and bicycle ownership may be considered as a complementary tool to promote a ’bicycle-culture’. This paper aims to cover the gap about the interaction between both systems (public bicycle/private bicycle) and which are the key aspects to explain the bicycle-buying decision. After a fieldwork based on surveys conducted in Seville (Spain), one of the cities currently acknowledged worldwide for its successful policy of promoting cycling, we apply a Discrete Choice Model. Our findings show that among the socio-demographic factors that favor the move from the PBSS to the private bicycle are: having a higher level of education, being more progressive ideologically-speaking, and being a resident of the city itself; while age and gender do not appear to be conclusive. Experienced users, for whom the bicycle is a part of his/her healthy lifestyle, state a greater willingness to buy a bicycle. And the main obstacles to make the jump from the PBSS to the private bicycle, and that any action plan to support private bicycle usage should take into account, are: the lack of proper parking at the origin/destination, and fear of theft.     

Categorization of the lane change decision process on freeways

Traffic operations for new road layouts are often simulated using microscopic traffic simulation packages. These traffic simulation packages usually simulate traffic on freeways by a combination of a car-following model and a lane change model. The car-following models have gained attention of researchers and are well calibrated versus data. The proposed lane change models are often representations of assumed reasonable behavior, not necessarily corresponding to reality. The current simulation packages apply solely one specific type of model for car-following or lane changing for all vehicles during the simulation. This paper investigates the decision process of lane changing maneuvers for a variety of drivers based on a two-stage test-drive. Participants are asked to take a drive on a freeway in the Netherlands in a camera-equipped vehicle. Afterwards, the drivers are asked to comment on their choices related to lane and speed choice, while watching the video. This paper reveals that different drivers have completely different strategies to choose lanes, and the choices to change lane are related to their speed choice. Four distinct strategies are empirically found. These strategies differ not only in parameter values, as is currently being modeled in most simulation packages, but also in their reasoning. Most remarkably, all drivers perceive their strategy as an obvious behavior and expect all other drivers to drive in a similar way. In addition to the interviews of the participants in the test-drive, 11 people who did not take part in the experiment were interviewed and questioned on lane change decisions. Moreover, the findings of this study have been presented to various groups of audience with different backgrounds (about 150 people). Their comments and feedback on the derived driving strategies have added some value to this study. The findings in this paper form a starting point for developing a novel lane change model which considers four different driving strategies among the drivers on freeway. This is a significant contribution in the area of driving behavior modeling, since the existing microscopic simulators consider only one type of lane change models for all drivers during the simulation. This could lead to significant changes in the way lane changes on freeways are modeled.     

A traffic accident morphology diagnostic model based on a rough set decision tree

ABSTRACT

To build a traffic safety feature model and to quantify accident influences caused by some traffic violation behaviors of drivers, an accident diagnostic decision-making model is established. For the purpose of diagnosing accident morphologies, rough set theory is applied and the influence of traffic factors of different accident morphologies is quantified through calculating the degree of attribute importance, selecting core traffic factors and adopting a C4.5 decision tree algorithm. In the paper, road traffic accident data from 2008 to 2013 in Anhui Province are used. Typical rules are selected, targeted strategy proposals are put forward, and then, a scientific and reasonable diagnostic basis is provided for the diagnosis of traffic safety risks and the prediction of potential traffic accidents.