Short-Term Traffic Flow Forecasting for Freeway Incident-Induced Delay Estimation

Freeway incidents not only threaten travelers’ safety but also cause severe congestion. Incident-induced delay (IID) refers to the extra travel delay resulting from incidents on top of the recurrent congestion. Quantifying IID would help people better understand the real cost of incidents, maximize the benefit-cost ratio of investment on incident remedy actions, and develop active traffic management and integrated corridor management strategies. By combining a modified queuing diagram and short-term traffic flow forecasting techniques, this study proposes an approach to estimate the temporal IID for a roadway section, given that the incidents occurs between two traffic flow detectors. The approach separates IID from the total travel delay, estimates IID for each individual incident, and only takes volume as input for IID quantification, avoiding using speed data that are widely involved in previous algorithms yet are less available or prone to poor data quality. Therefore, this approach can be easily deployed to broader ranges where only volume data are available. To verify its estimation accuracy, this study captures two incident videos and extracts ground-truth IID data, which is rarely done by previous studies. The verification shows that the IID estimation errors of the proposed approach are within 6% for both cases. The approach has been implemented in a Web-based system, which enables quick, convenient, and reliable freeway IID estimation in the Puget Sound region in the state of Washington.     

Identification and interpretation of spatial–temporal mismatch between taxi demand and supply using global positioning system data

Taxis provide a type of on-demand mobility service in urban transportation. There are growing concerns regarding the level of service of taxis in satisfying residents’ mobility demand. However, the mismatch between demand and supply of taxi services has not been resolved even with the introduction of app-based vehicle services. In this study, three indicators are constructed using the Shanghai taxi global positioning system (GPS) dataset to reveal the spatial–temporal mismatch pattern. The issue is further analyzed via a case study, in which seven regions with frequent mismatch patterns are identified in the time period from 21:00 to 22:00. Then, a multinomial logistic regression model is employed to identify the demographic and built-environment factors contributing to the taxi mismatch problem. The study results show that population density, residential areas, the number of points of interest, and road density have significant relationships with the taxi undersupply. In contrast, the areas of commercial lands, as well as the other two transportation-related factors, that is, the number of bus stops and the distance to nearest subway station, are observed to be statistically significant for both “oversupply” and “undersupply” conditions. This study provides valuable insights for identifying mismatch patterns and interpreting the mismatch problem as a function of spatially explicit factors that are of great use for urban governance, especially in the improvement of taxi efficiency, taxi management, and urban planning.     

铁路客运服务需求的模糊聚类分析

为了掌握客运服务各要素在铁路客运服务需求中的重要程度,提出按其重要程度归类的ISODATA模糊聚类方法。根据近期客运市场调查数据,确定客运服务要素的4个特征指标。运用ISODATA模糊聚类方法对21个客运服务要素进行聚类,并对聚类效果进行评价。把21个服务要素按其重要程度分成5类,由21个客运服务要素归类结果,分析确定要素在客运服务市场中的地位。     

大型造船企业成本核算系统的设计与实现

本文根据中国船舶工业集团公司所属四大造船企业的特点，对造船成本核算系统具有共性的需求进行了研究分析，设计和实现了对工资、辅助生产、制造费用、制造管理费等费用的分配，对系统软件结构、数据间的关联和业务处理时序进行了论述。     

跨国公司—当今国际海运市场需求的主要来源

当今以国际贸易来调剂或弥补国与国间各自资源稀缺状况的手段已不能完全适应世界经济发展的需要，对外直接投资及其组织形态——跨国公司能使资源在全世界范围内得到有效配置。跨国公司生产和经营特性决定了其对国际运输，特别对国际海运的作用，也决定了国际贸易的构成。本文在此认识上，分析了国际海运与国际贸易、跨国公司之间的关系；论述了跨国公司对国际海运需求的主要来源，归纳了由此需求而产生的对国际海运发展模式和趋势的影响。     

The Added Value of Accounting For Users’ Flexibility and Information on the Potential of a Station-Based One-Way Car-Sharing System: An Application in Lisbon,Portugal

Car-sharing systems are an alternative to private transportation whereby a person may use an automobile without having to own the vehicle. The classical systems in Europe are organized in stations scattered around the city where a person may pick up a vehicle and afterward return it to the same station (round trip). Allowing a person to drop off the vehicle at any station, called one-way system, poses a significant logistics problem because it creates a significant stock imbalance at the stations, which means that there will be times when users will not have a vehicle available for their trip. Previous mathematical programming formulations have tried to overcome this limitation by optimizing trip selection and station location in a city in order to capture the best trips for balancing the system. But there was one main limitation: The users were assumed to be inflexible with respect to their choice of a station, and held to use only the one closest to their origin and destination. If the user is willing to use the second or even the third closest station the user could benefit from using real-time information on vehicle stocks at each station and be able to select the one with available capacity. In this article we extend a previous model for trip selection and station location that takes that aspect into account by considering more vehicle pick-up and drop-off station options and then apply it to a trip origin–destination matrix from the Lisbon region in Portugal. Through the extended formulation we were able to conclude that user flexibility allied with having information on vehicle stocks increases the profit of the company, as people will go directly to a station with a vehicle available, thus making the use of the fleet more efficient. Observing the size of the stations resulting from the model, we also concluded that the effect of information is enhanced by large car-sharing systems consisting of many small stations.     

基于需求响应的铁路集装箱班列始发时刻优化

依据铁路运输生产实际,充分考虑集装箱货物与集装箱班列在时间和数量方面的匹配关系,以集装箱货物在集装箱办理站的总停留时间最小为优化目标,以集装箱货物装车唯一性、班列编成箱数、作业时间和发车间隔为约束条件,构建铁路集装箱班列始发时刻优化的非线性混合整数规划模型。根据模型的特点,设计基于遗传算法的求解方法。由随机产生和"先到先服务"方案结合的方法生成初始种群,并运用启发式策略修复进化过程中出现的不可行解。以胶州-黄岛之间的铁路集装箱班列为例进行仿真计算。结果表明:模型和算法具有较高的计算效率;利用模型及算法得到的集装箱班列始发时刻与集装箱货物的数量、到达时间分布之间具有较好的匹配性,使集装箱在办理站停留时间最短,制定的班列开行计划响应了用户需求。     

北京局集团公司“三港三区域三品类”货运增量对策

在“公转铁”机遇带动下,北京局集团公司将货运增量重点由煤炭转向“三港三品类”,进行运力资源倾斜。分析“三港三区域三品类”货运量、装车卸车,从运输价格、运距结构、运力匹配、装卸车组织、环保政策、路企双方设备能力等方面分析货运增量影响因素,提出“三港三区域三品类”货运增量对策,即:增强货运市场营销策略积极参与市场竞争、加强运输组织释放“三港、三区域”运能、调整作业方案实现效率提升、依托“公转铁”政策支持优化运输结构、落实专用线扩能改造助力货运上量,提升“三港三区域三品类”市场竞争力,满足货运增量需求,实现北京局集团公司货运量持续增长。     

布达佩斯停车管理中的TDM实践

中国目前的交通情况与过去的欧洲有很多相似之处,可借鉴其相关经验教训.以匈牙利布达佩斯为例,探讨其如何利用交通需求管理措施进行城市停车管理.首先指出停车管理的目标应为降低小汽车的使用需求、强化公共交通相对于私人交通的竞争力.然后,在路内停车管理层面,剖析中国停车管理存在的问题,分别从政策及标准、运营管理模式、技术应用三方...