关于南京市街巷路整治的反思

本文阐述南京市街巷支路整治中存在的问题及其对策     

人工智能在车辆自动驾驶中的应用

提出一种新的基于人工智能的感知 计划 动作agent结构实现智能车辆自动驾驶的方案。首先通过描述该结构的原理说明该结构可以解决自动驾驶中存在的一些问题,接着通过建立自动驾驶知识库阐述如何具体实现自动驾驶,最后通过仿真实验验证该方法能够为智能车辆实现自动或辅助驾驶提供一种非常有效的机制。     

高速公路路线方案优选模型及其应用

利用灰色物元分析法,建立高速公路路线方案的优劣排序模型,对各路线方案进行多因素综合评价,为择优选择路线方案提供一种科学的评价方法。     

北京城市交通发展战略研究

本文综合分析了北京城市交通现状，运用生产力布局的理论对北京城市交通拥堵的原因进行分析，探索了国内外大城市交通发展的最新趋势，根据发展“首都经济”的要求．提出解决北京城市交通拥堵问题，必须采取标本兼治，并提出北京城市交通发展战略研究的有关建议。.     

机器人生产线在船舶智能制造中的应用研究

智能制造是“中国制造2025”的主攻方向。本文先浅谈了智能船厂，并结合国内首个智能船厂试点对智能船厂的初级发展建设等进行初步探索，主要对船舶智能制造机器人生产线应用进行梳理分析，如工艺流程及布置、生产模式改进、提质增效和人员减配等。     

Ontologies for transportation research: A survey

Transportation research relies heavily on a variety of data. From sensors to surveys, data supports day-to-day operations as well as long-term planning and decision-making. The challenges that arise due to the volume and variety of data that are found in transportation research can be effectively addressed by ontologies. This opportunity has already been recognized – there are a number of existing transportation ontologies, however the relationship between them is unclear. The goal of this work is to provide an overview of the opportunities for ontologies in transportation research and operation, and to present a survey of existing transportation ontologies to serve two purposes: (1) to provide a resource for the transportation research community to aid in understanding (and potentially selecting between) existing transportation ontologies; and (2) to identify future work for the development of transportation ontologies, by identifying areas that may be lacking.     

An optimization model for integrated planning of railway traffic and network maintenance

Railway transportation systems are important for society and have many challenging and important planning problems. Train services as well as maintenance of a railway network need to be scheduled efficiently, but have mostly been treated as two separate planning problems. Since these activities are mutually exclusive they must be coordinated and should ideally be planned together. In this paper we present a mixed integer programming model for solving an integrated railway traffic and network maintenance problem. The aim is to find a long term tactical plan that optimally schedules train free windows sufficient for a given volume of regular maintenance together with the wanted train traffic. A spatial and temporal aggregation is used for controlling the available network capacity. The properties of the proposed model are analyzed and computational experiments on various synthetic problem instances are reported. Model extensions and possible modifications are discussed as well as future research directions.     

Integrated approach to determine highway flooding and critical points of drainage

Among the natural hazards that threaten transportation infrastructure, flooding represents a major hazard to highways as it challenges their design, operation, efficiency and safety. In extreme cases, it may lead to massive obstruction of traffic and direct damages to the road structures themselves and indirect damages to the economic activity and development of the region. To enable the prevention of such consequences, and the proposition of adaptive measures for existing infrastructure, this paper presents an integrated framework to identify the most vulnerable points to flooding along a highway. This is done through the combination of remote sensing information (e.g. LiDAR based Digital Elevation Model, satellite imagery), a high-quality dataset, and a quasi-2D hydrodynamic model. The forcing condition is defined using a hyetograph associated to a storm with duration of 1 day and return period of 100 years. The selected highway is located in the Mexican state of Tabasco, where extreme precipitation events and floods are frequent. Results demonstrate the ability of the methodology to identify critical water levels along the road (h > 1.50 m) at those locations where flooding has been experienced, as well as points of inspection for the highway drainage. These locations were visited in the field and maintenance problems were detected that do increase its level of exposure. We show that this framework is useful for the generation of a flood management strategy to the analyzed highway, which includes an optimum location of adaptive measures to an anticipated more intense future climate.     

Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data.     

Agent-based simulation framework for mixed traffic of cars,pedestrians and trams

In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.