Energy and emissions impacts of a freeway-based dynamic eco-driving system

Surface transportation consumes a vast quantity of fuel and accounts for about a third of the US CO₂ emissions. In addition to the use of more fuel-efficient vehicles and carbon-neutral alternative fuels, fuel consumption and CO₂ emissions can be lowered through a variety of strategies that reduce congestion, smooth traffic flow, and reduce excessive vehicle speeds. Eco-driving is one such strategy. It typically consists of changing a person’s driving behavior by providing general static advice to the driver (e.g. do not accelerate too quickly, reduce speeds, etc.). In this study, we investigate the concept of dynamic eco-driving, where advice is given in real-time to drivers changing traffic conditions in the vehicle’s vicinity. This dynamic strategy takes advantage of real-time traffic sensing and telematics, allowing for a traffic management system to monitor traffic speed, density, and flow, and then communicates advice in real-time back to the vehicles. By providing dynamic advice to drivers, approximately 10–20% in fuel savings and lower CO₂ emissions are possible without a significant increase in travel time. Based on simulations, it was found that in general, higher percentage reductions in fuel consumption and CO₂ emission occur during severe compared to less congested scenarios. Real-world experiments have also been carried out, showing similar reductions but to a slightly smaller degree.     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.

模糊控制在港口机械上的应用研究

分析模糊控制工程在港口机械控制中的应用,并从模糊控制的特点和模糊控制与常规控制的关系出发,就促进模糊控制工程在港口机械中的推广应用,提出了自己的见解。     

扰动模糊逻辑算子组

在扰动模糊逻辑命题及其算子的基础上,定义了扰动模糊逻辑算子组的概念,讨论了扰动模糊逻辑算子组的性质.从而使经典模糊逻辑的概念及性质得到进一步的推广,同时也揭示了在这种由一维到二维的推广中存在的问题.最后,从代数观点研究了扰动模糊逻辑算子组与经典模糊逻辑算子组之间的同态关系.     

模糊模式识别在交通量预测模型选择中的应用

本文将模糊模式识别应用于交通规划预测模型的评价．以出行受约束的重力模型与双约束重力模型为例,说明常用的一些检测方法存在的不严密性,并用模糊模式识别方法定量确定预测结果与实际出行量的拟合程度．本文的分析结果能为交通规划预测模型的选择提供可靠的依据,并为预测结果的评价提供新的方法．     

综合交通枢纽客运站布局评价的定量优化方法研究

为了评价综合交通枢纽中客运站的布局优劣、服务水平,进而优化规划方案,从规划的协调性、枢纽的需求性、枢纽的社会性以及枢纽的便利性四个方面,采用层次分析法建立综合评价体系,用定量与定性相结合的方法给出各指标的定义及计算方法。并运用模糊综合评价法以及交通影响分析进行评价。应用结果表明,该评价体系能较好地评价综合变通枢纽客运站的布局情况及枢纽的需求原则,具有广泛的实用性和良好的可操作性,可以用于综合变通枢纽客运站的规划。     

基于集成学习算法的航路网络航段交通拥挤识别方法研究

基于航路网络ADS-B航迹数据定义航路网络航段交通流量、航段交通密度、航段交通饱和度、航段交通接近率4 项交通拥挤状态评价指标;采用模糊C均值聚类算法和航段历史交通拥挤状态评价指标参数划分航段交通拥挤状态等级;结合集成学习算法构建航路网络航段交通拥挤状态识别模型,实现航段交通拥挤状态的识别. 实证分析表明：航路网络交通拥挤状态集成学习识别模型对实验航路网络航段交通拥挤状态识别准确率达到98.34%,采用决策树基学习器优于k 近邻基学习器,且增加的集成学习基学习器数量可提升模型的识别精度;集成学习识别模型的识别性能优于BP神经网络模型,识别方法符合实际且具有应用价值.     

城市中心商业区停车场ETC系统应用与评价

ETC不停车收费系统不仅应用在高速公路,同样也可以在城市中心商业区停车场发挥作用。借鉴高速公路ETC收费系统的工作原理,设计城市中心商业区停车场ETC系统架构。采用定性分析和模糊层次综合评价方法进行评价,商业区停车场ETC系统的社会经济效益体现在停车场收费经营者的效益、停车使用者的效益以及非使用者的效益上,当前城市中心商业区停车场ETC系统的应用评价为良好水平。该系统是对高速公路ETC的创新应用,还有待进一步提高。     

基于模糊约束的空中交通流量预测模型研究

鉴于传统流量预测模型存在预测精度差、耗时长、效率低的不足,将模糊约束引入空中交 通系统,用于表示人工智能领域中一些不确定的信息,构建了基于模糊约束的空中交通流量预测模型。通过分析影响模糊约束的决策向量、模糊参数向量及模糊约束集三个因素,提出预测模型 的构建流程,选取空中交通路线多转折点,并获取模糊矩阵,建立了空中交通流量预测模型。实验结果表明,对空中交通流量进行预测时,采用改进的预测模型相比传统预测模型的预测结果较 优、耗时较短、精度较高。     

收费公路PPP项目运营期收益调节的期权价值分析

收费公路PPP项目在项目运营过程中,CPI的变化影响项目的收益.在项目谈判阶段,分析CPI对项目收益的影响方式,依据PPP项目的风险共担、收益共享原则,对CPI影响下的社会资本收益不足或超额收益设定收益调节方法,能保障政府和社会资本双方收益、实现双方共赢.本文研究CPI对收费公路PPP项目运营期间收益的影响,提出能体现PPP项目投资回报机制的收益补偿和超额收益分享要求的应对CPI变化的收益调节模型,并用实物期权理论评价模型的期权价值.实证表明,收益调节模型能保障社会资本在收费公路PPP项目运营中的收益,并可以为政府和社会资本的合理决策提供参考,实现合作共赢.