Customizing driving cycles to support vehicle purchase and use decisions: Fuel economy estimation for alternative fuel vehicle users

Wider deployment of alternative fuel vehicles (AFVs) can help with increasing energy security and transitioning to clean vehicles. Ideally, adopters of AFVs are able to maintain the same level of mobility as users of conventional vehicles while reducing energy use and emissions. Greater knowledge of AFV benefits can support consumers’ vehicle purchase and use choices. The Environmental Protection Agency’s fuel economy ratings are a key source of potential benefits of using AFVs. However, the ratings are based on pre-designed and fixed driving cycles applied in laboratory conditions, neglecting the attributes of drivers and vehicle types. While the EPA ratings using pre-designed and fixed driving cycles may be unbiased they are not necessarily precise, owning to large variations in real-life driving. Thus, to better predict fuel economy for individual consumers targeting specific types of vehicles, it is important to find driving cycles that can better represent consumers’ real-world driving practices instead of using pre-designed standard driving cycles. This paper presents a methodology for customizing driving cycles to provide convincing fuel economy predictions that are based on drivers’ characteristics and contemporary real-world driving, along with validation efforts. The methodology takes into account current micro-driving practices in terms of maintaining speed, acceleration, braking, idling, etc., on trips. Specifically, using a large-scale driving data collected by in-vehicle Global Positioning System as part of a travel survey, a micro-trips (building block) library for California drivers is created using 54 million seconds of vehicle trajectories on more than 60,000 trips, made by 3000 drivers. To generate customized driving cycles, a new tool, known as Case Based System for Driving Cycle Design, is developed. These customized cycles can predict fuel economy more precisely for conventional vehicles vis-à-vis AFVs. This is based on a consumer’s similarity in terms of their own and geographical characteristics, with a sample of micro-trips from the case library. The AFV driving cycles, created from real-world driving data, show significant differences from conventional driving cycles currently in use. This further highlights the need to enhance current fuel economy estimations by using customized driving cycles, helping consumers make more informed vehicle purchase and use decisions.     

Delivering improved alerts,warnings, and control assistance using basic safety messages transmitted between connected vehicles

When vehicles share their status information with other vehicles or the infrastructure, driving actions can be planned better, hazards can be identified sooner, and safer responses to hazards are possible. The Safety Pilot Model Deployment (SPMD) is underway in Ann Arbor, Michigan; the purpose is to demonstrate connected technologies in a real-world environment. The core data transmitted through Vehicle-to-Vehicle and Vehicle-to-Infrastructure (or V2V and V2I) applications are called Basic Safety Messages (BSMs), which are transmitted typically at a frequency of 10 Hz. BSMs describe a vehicle’s position (latitude, longitude, and elevation) and motion (heading, speed, and acceleration). This study proposes a data analytic methodology to extract critical information from raw BSM data available from SPMD. A total of 968,522 records of basic safety messages, gathered from 155 trips made by 49 vehicles, was analyzed. The information extracted from BSM data captured extreme driving events such as hard accelerations and braking. This information can be provided to drivers, giving them instantaneous feedback about dangers in surrounding roadway environments; it can also provide control assistance. While extracting critical information from BSMs, this study offers a fundamental understanding of instantaneous driving decisions. Longitudinal and lateral accelerations included in BSMs were specifically investigated. Varying distributions of instantaneous longitudinal and lateral accelerations are quantified. Based on the distributions, the study created a framework for generating alerts/warnings, and control assistance from extreme events, transmittable through V2V and V2I applications. Models were estimated to untangle the correlates of extreme events. The implications of the findings and applications to connected vehicles are discussed in this paper.     

考虑收益管理的高铁平行车次动态差别定价

基于RP(Revealed Preference)和SP(Stated Preference)调查数据，利用潜在类别模型对高铁旅客进行细分，得到旅客对平行车次不同服务属性，如列车运行时间、发车时段和舒适度的偏好程度，并对其进行量化；引入收益管理，以多列车整体收益最大为目标，构建平行车次动态差别定价模型，并设计模拟退火算法进行求解；最后，通过京沪高铁进行实例验证.结果表明：与固定票价进行客票销售相比，所提方案能够适应高峰期和平峰期不同客流特点，提高铁路客票总收益，为高铁平行车次灵活定价提供参考.     

船舶低硫柴油系统设计的分析与优化

就新辟航线首制船“汉亚直达”集装箱船的低硫柴油系统,叙述了船舶低硫柴油系统的设计经验,从当前国内外对船用燃油硫含量的要求、应对方案到船舶低硫柴油冷却方式选择、低硫柴油冷却系统设计、高/低硫柴油转换、使用低硫柴油风险分析及处理等方面进行详细叙述,为业内同行提供参考。     

CACC车头时距与混合交通流稳定性的解析关系

研究协同自适应巡航控制(Cooperative Adaptive Cruise Control，CACC)车头时距对不同CACC比例下混合交通流稳定性的影响关系，进而为CACC车头时距设计提供参考. 应用优化速度模型(Optimal Velocity Model，OVM)作为手动车辆的跟驰模型，PATH真车实验标定的模型作为CACC车辆的跟驰模型. 基于传递函数理论，推导混合交通流稳定性判别条件，计算关于CACC比例与平衡态速度的混合交通流稳定域. 分析混合交通流在任意速度下稳定所需满足的临界CACC比例与CACC车头时距的解析关系，提出随CACC比例增加的可变 CACC车头时距设计策略，并通过数值仿真实验验证所提可变CACC车头时距策略的正确性. 研究结果表明：在所提可变CACC车头时距策略下，CACC车头时距随CACC比例增加而逐渐降低，避免取值较大影响混合交通流通行能力的提升；当CACC比例大于35%时，混合交通流在任意速度下稳定.研究结果可为大规模CACC真车实验的实施提供理论设计参考.     

船用厨房和具有烹调设备的配餐室的通风计算及空气处理方法

本文介绍了ISO 9943-2009国际标准和GBT 20846-2007中国国家标准中对船用厨房和具有烹调设备的配餐室的通风计算及空气处理中提出的送风量的计算方法，提出另一种更易于大家理解和接受的简易计算方法和空气处理过程，供工程技术及设计研究人员参考。     

Time-variant bulk carrier reliability analysis in pure bending intact and damage conditions

Time-variant reliability analysis of a corroded bulk carrier in intact and damage conditions is performed by First-Order (FORM), Second-Order (SORM) Reliability Methods and Importance Sampling simulation. Annual failure probabilities are determined up to 25-year ship lifetime, accounting for time-variant corrosion wastage of structural members contributing to hull girder strength. Statistical properties of hull girder capacity are determined by Monte Carlo simulation, applying three correlation models among corrosion wastages of structural members contributing to hull girder strength, namely no correlation, full correlation and full correlation among wastages of structural members belonging to the same category of compartments. A modified incremental-iterative method is applied, to account for instantaneous neutral axis rotation, in case of asymmetrical damage conditions, as for collision and grounding events. Incidence of intact/damage condition, as well as correlation among corrosion wastages, on annual sagging/hogging time-variant failure probability is investigated and discussed. Time-variant sensitivity analyses for intact and damage conditions are also performed, to investigate the incidence of random variables' uncertainties on the attained failure probability. Finally, the bulk carrier section scheme, benchmarked in the last ISSC Report, is applied as test case.     

BIM技术在清华珠三角公建项目施工中的应用研究

随着科技的进步及项目管理水平的提高,BIM技术应运而生。本文以清华珠三角研究院粤港澳大湾区创新基地项目为依托,从应用目标、应用前准备工作、前期策划管理、技术管理、质量安全管理、物资设备管理、进度管理、经济成本管理等方面开展BIM技术在公建项目施工中的应用研究,结果表明:使用BIM技术,使项目管理走向精细化、全面化、高效化,并提高质量标准,增加安全保障,减少项目成本,提高项目利润率;同时与AI技术相结合,使BIM技术更加具有简便性,产出更大效益。     

一种基于动态分析的突变和异常波动预警方法

针对模拟量的突变和异常波动预警,给出一种基于动态分析的、可以应用于各种模拟量的统一预警方法,该方法已被应用于CSM-TH型集中监测程序和智能分析系统中,在多条线700余站现场运行的7年中,收到良好效果,得到用户认可。     

绿色公路技术LCA评价体系及效益分析

针对各类绿色公路技术难以横向比较的问题,文章从技术可行性、经济效益、节能减排效益等方面,提出建立绿色公路技术LCA评价体系,并以G312苏州西段工程为例进行综合效益分析,其综合效益最为显著,具备规模化、资源化、投资适宜的绿色公路技术;技术瓶颈问题的突破和创新,是推进绿色公路发展的根本动力;将绿色理念融入公路建设的全生命周期的前提,是因地制宜的前期规划布局研究,也是合理选择适宜绿色公路技术的基础。