Mental models of driving and speed: biases,choices and reality

This paper provides a review of research performed by Svenson with colleagues and others work on mental models and their practical implications. Mental models describe how people perceive and think about the world including covariances and relationships between different variables, such as driving speed and time. Research on mental models has detected the time-saving bias [Svenson, O. (1970). A functional measurement approach to intuitive estimation as exemplified by estimated time savings. Journal of Experimental Psychology, 86, 204–210]. It means that drivers relatively overestimate the time that can be saved by increasing speed from an already high speed, for example, 90–130?km/h, and underestimate the time that can be saved by increasing speed from a low speed, for example, 30–45?km/h. In congruence with this finding, mean speed judgments and perceptions of mean speeds are also biased and higher speeds given too much weight and low speeds too little weight in comparison with objective reality. Replacing or adding a new speedometer in the car showing min per km eliminated or weakened the time-saving bias. Information about braking distances at different speeds did not improve overoptimistic judgments of braking capacity, but information about collision speed with an object suddenly appearing on the road did improve judgments of braking capacity. This is relevant to drivers, politicians and traffic regulators.     

Studies on emergency evacuation management for maritime transportation

Marine transportation is a vital component of the world’s economy and transportation network. The number of people using passenger ships around the globe is increasing worldwide. Similar to other transportation systems, passenger safety is critical in maritime shipment. As emergency evacuation processes for ships are highly different from and more complicated than those for buildings and other vehicles, many researchers have published a vast range of documents related to this peculiar research area. However, there is a tangible lack of sufficient literature review studies that investigate marine emergency evacuation (MEE). That being the case, the potential of marine transportation and the effect of emergency evacuation operation on life safety have inspired the proposal of this study. This paper offers a review of the available literature on MEE modelling, analysis and planning during the period from 1973 to 2017 using a systematic approach. After reviewing relevant academic journals, peer-reviewed conference papers, and technical reports of agencies, relevant literature is analysed. In addition, the literature review is extended by means of proposing a framework methodology which considers different possible conditions and situations during MEE. Finally, insights for ship managers and policymakers are discussed and potential future research directions are identified.     

Field tests of a dynamic green driving strategy based on inter-vehicle communication

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions.     

福州轨道交通建设安全管控平台的设计与应用

福州城市轨道交通建设规模不断增大，复杂的地质、环境条件以及众多工种施工的交叉作业和人员活动，给安全生产带来挑战。针对建设全过程安全管控的具体业务关系和需求分析，梳理和固化工作岗位、职责、流程、响应、整改等安全管理的事项和要求，强化对管控过程的追溯和考核管理。研究信息平台的业务需求、平台架构、网络拓扑、功能模块、数据库设计方法和实现思路，利用Ssm框架、Quartz框架、Encache技术以及SQLServer数据库技术，设计开发基于B/S模式的城市轨道交通安全管控信息系统，应用于在建的5条线路。信息平台的应用，可实现安全管理的标准化、科学化和精细化，极大地提高管理水平和工作效率。     

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.     

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。     

道路环境对交通安全的影响及对策

交通安全,涉及到人、车以及道路和环境等很多因素。近年来,因为各种原因使得有关单位以及人员将更多的将精力放在人、车、道路这几个因素上,对道路交通环境没有过多的考虑和研究。深入研究道路交通环境,有利于道路交通的安全,文章通过对其的研究和分析,得出有关道路交通环境对交通安全的影响和解决措施,对于防止道路交通安全事故具有重要意义。同时为人们的生命财产的安全提供保障、对构建社会主义和谐社会具有很大帮助。     

某型直流充电柜温度场仿真

对某型直流充电柜满负载工况下温度场进行仿真,根据实验测量数据验证仿真结果准确性,成功完成了对充电柜温度场的建模仿真工作,并实现对初始模型的简化,为对整个充电站进行温度场建模仿真奠定了基础。     

Analysis of volatility in driving regimes extracted from basic safety messages transmitted between connected vehicles

Driving volatility captures the extent of speed variations when a vehicle is being driven. Extreme longitudinal variations signify hard acceleration or braking. Warnings and alerts given to drivers can reduce such volatility potentially improving safety, energy use, and emissions. This study develops a fundamental understanding of instantaneous driving decisions, needed for hazard anticipation and notification systems, and distinguishes normal from anomalous driving. In this study, driving task is divided into distinct yet unobserved regimes. The research issue is to characterize and quantify these regimes in typical driving cycles and the associated volatility of each regime, explore when the regimes change and the key correlates associated with each regime. Using Basic Safety Message (BSM) data from the Safety Pilot Model Deployment in Ann Arbor, Michigan, two- and three-regime Dynamic Markov switching models are estimated for several trips undertaken on various roadway types. While thousands of instrumented vehicles with vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication systems are being tested, nearly 1.4 million records of BSMs, from 184 trips undertaken by 71 instrumented vehicles are analyzed in this study. Then even more detailed analysis of 43 randomly chosen trips (N = 714,340 BSM records) that were undertaken on various roadway types is conducted. The results indicate that acceleration and deceleration are two distinct regimes, and as compared to acceleration, drivers decelerate at higher rates, and braking is significantly more volatile than acceleration. Different correlations of the two regimes with instantaneous driving contexts are explored. With a more generic three-regime model specification, the results reveal high-rate acceleration, high-rate deceleration, and cruise/constant as the three distinct regimes that characterize a typical driving cycle. Moreover, given in a high-rate regime, drivers’ on-average tend to decelerate at a higher rate than their rate of acceleration. Importantly, compared to cruise/constant regime, drivers’ instantaneous driving decisions are more volatile both in “high-rate” acceleration as well as “high-rate” deceleration regime. The study contributes to analyzing volatility in short-term driving decisions, and how changes in driving regimes can be mapped to a combination of local traffic states surrounding the vehicle.     

Socially optimal electric driving range of plug-in hybrid electric vehicles

This study determines the optimal electric driving range of plug-in hybrid electric vehicles (PHEVs) that minimizes the daily cost borne by the society when using this technology. An optimization framework is developed and applied to datasets representing the US market. Results indicate that the optimal range is 16 miles with an average social cost of $3.19 per day when exclusively charging at home, compared to $3.27 per day of driving a conventional vehicle. The optimal range is found to be sensitive to the cost of battery packs and the price of gasoline. When workplace charging is available, the optimal electric driving range surprisingly increases from 16 to 22 miles, as larger batteries would allow drivers to better take advantage of the charging opportunities to achieve longer electrified travel distances, yielding social cost savings. If workplace charging is available, the optimal density is to deploy a workplace charger for every 3.66 vehicles. Moreover, the diversification of the battery size, i.e., introducing a pair and triple of electric driving ranges to the market, could further decrease the average societal cost per PHEV by 7.45% and 11.5% respectively.