电梯上行的超速保护

在众多的事故类型中,电梯上行超速事故是比较常见的,也是产生危害较大的一种。下面就结合检验工作实际,围绕电梯上行超速事故的原因分析、电梯上行超速保护装置的要求、电梯上行超速保护装置的类型及选择、电梯夹绳器选用和改进的建议和电梯上行超速保护装置的检验等问题进行探讨,提出自己浅显的见解,确保电梯上行超速保护装置更加安全、可靠。     

恐惧诉求对职业驾驶员安全驾驶态度和行为意向的影响

研究以EPPM模型作为理论框架,探讨恐惧诉求对危险驾驶行为(超速和不系安全带)态度和行为意向的作用。54名职业驾驶员在观看交通安全恐惧诉求录像后,完成安全驾驶行为问卷。回归分析表明恐惧诉求的交通事故录像能够改变驾驶员对超速及不系安全带驾驶的态度和行为意向,但作用不完全一致。恐惧情绪唤起通过恐惧情感所引发的威胁评估过程中介对不超速行为意向的影响。最后,对研究的局限和未来的研究进行讨论。     

电梯轿厢上行超速保护装置检验方法探讨

电梯的上行超速保护装置是电梯重要的安全部件，通过对上行超速保护装置配置及动作速度的要求分析，阐述了各类上行超速保护装置的试验方法以及动作速度的校验方法，电梯安装维保和电梯法定检验时应对电梯的上行超速保护装置进行检验，确保电梯上行超速保护装置动作可靠有效，防止电梯冲顶事故的发生。     

起重机械超速保护开关检测装置设计及应用

针对起重机械超速保护开关定期检验无定量检测手段的问题,设计了一种超速保护开关检测装置。该装置由测试台、安装架和测控系统组成。超速保护开关固定在安装架上,通过联接器与变频电动机联接并同步旋转。测控系统通过微处理器处理超速保护开关转速信号和触头动作信号,实现对其整定值的检测。试验表明,该检测装置可以准确测定超速保护开关整定值,为检验人员判定超速保护开关合格性提供定量标准。     

起重机械超速保护的应用

针对起重机械中如何设置超速保护的问题,本文介绍国家标准、技术规范对起重机械超速保护的相关要求,提出可以在起重机械上应用的超速保护形式以及加装和检验超速保护的方法,加强超速保护在起重机械中的应用。     

在用电梯上行超速保护急待解决的几个问题

电梯超速保护包括下行超速保护和上行超速保护,对上行超速问题（包括冲顶事故）,虽然设置了井道上行限位和上极限开关,但起不到有效的保护作用,本文就此问题展开讨论,并提出有效的控制措施。     

机动车绿灯倒计时对交叉口交通安全的影响研究

在总结国内外研究的基础上,通过问卷调查、现场观测等方法对机动车绿灯倒计时对我国驾驶员的心理及驾驶行为进行调查,解析机动车绿灯倒计时信号对驾驶员心理与驾驶行为的影响机理,研究结果显示机动车绿灯倒计时既不利于交叉口的交通安全,又降低了通行效率,因此得出应谨慎使用机动车绿灯倒计时的结论。同时建议采取道路交通安全法中对黄灯的含义进行修改,并在闯红灯抓拍系统中增设闯黄灯超速自动抓拍功能,以减少信号过渡期间超速抢灯现象的发生,保障交叉口的交通安全。     

关于电梯上行超速保护的思考

电梯是人们日常生产和生活中不可缺少的交通工具，电梯的上行超速保护装置是电梯重要的安全部件。1电梯上行超速保护的定义解释及其要求轿厢上行超速保护装置是安装在曳引驱动电梯上，在电梯上行超速到一定程度时用来使轿厢制停或有效减速的一种安全保护装置。它一般由速度监控装置和减速装置两部分组成。通常采用双向限速器作为速度监控装置检测轿厢速度是否失控。     

关于永磁同步电梯上行超速保护的探讨

在分祈常用上行超速保护装置动作过程的基础上，提出了这些装置的缺点。介绍了永磁同步电机的基本原理和短路发电机特性及该特性在永磁同步电梯中松闸放人上的应用，并提出了通过改进永磁同步电机的控制电路可以实现上行超速的保护。     

上行超速保护装置的安全检验

介绍几种常见的电梯轿厢上行超速保护装置及检验方法和注意事项。     

Taxi driver speeding: Who,when, where and how? A comparative study between Shanghai and New York City

Objective: The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?)

Methods: This study proposes a driver–road–environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC.

Results: The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0–1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities.

Conclusions: Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.     

Measures of speeding from a GPS-based travel behavior survey

Objective: Lacking information about actual driving speed on most roads in the Minneapolis–St. Paul region, we determine car speeds using observations from a Global Positioning System (GPS)-based travel survey. Speed of travel determines the likelihood and consequences of collisions. We identify the road segments where speeding occurs. This article then analyzes the relationship between link length, traveler characteristics, and speeding using GPS data collected from 152 individuals over a 7-day period as part of the Minneapolis–St. Paul Travel Behavior Inventory.

Methods: To investigate the relationship, we employed an algorithm and process to accurately match the GPS data with geographic information system (GIS) databases. Comparing actual travel speed from GPS data with posted speed limits, we measure where and when speeding occurs and by whom. We posit that link length and demographics shape the decision to speed.

Results: Speeding is widespread under both high speed limits (e.g., 60?mph [97?km/h]) and low speed limits (less than 25?mph [40?km/h]); in contrast, speeding is less common at 30–35?mph (48–56?km/h). The results suggest that driving patterns depend on the road type. We also find that when there are many intersections, the average link speed (and speeding) drops. Long links are conducive to speeding. Younger drivers and more educated drivers also speed more, and speeding occurs more often in the evening.

Conclusions: Road design and link length (or its converse, frequency of intersections) affect the likelihood of speeding. Use of increasingly available GPS data allows more systematic empirical analysis of designs and topologies that are conducive to road safety.     

行人过街空间违章行为特性及安全影响分析

为探究提前右转车道处不同因素与人车冲突的相关性,以及行人空间违章对过街安全的影响。采集2 062个行人及人车冲突的样本数据,获取行人和机动车的时空信息,对比分析不同类型行人过街轨迹的特征;综合考虑人车冲突时间和速度指标构建人车冲突严重度指标,从行人生理特征、车流条件、道路环境等方面选取8个因素作为自变量,构建人车冲突严重度的多元有序Logistic模型。研究结果表明：空间违章过街的行人平均过街速度和速度离散程度都明显高于其他行人;年龄、车速、人行横道长度、车辆到达率以及过街轨迹类型都是影响人车冲突严重程度的重要因素。各类型空间违章行为使严重冲突占比均提升75%以上。研究结果有助于交管部门采取措施保障行人过街安全。     

Are sociodemographic characteristics and attitude good predictors of speeding behavior among drivers on Malaysia federal roads?

Objective: The increasing number of road crashes and fatalities on Malaysian federal roads is a cause for concern. The main causes of road crashes and fatalities on federal roads have been attributed to the speeding behavior among drivers. As such, this research investigates the possible predictors from sociodemographic characteristics and attitudes in predicting speeding behavior among drivers on Malaysia federal roads.

Methods: A face-to-face survey was conducted via purposive sampling on 300 drivers at rest areas at 6 crash hotspots on Malaysian federal roads. A set of questions related to speeding behavior was developed. The questionnaire consisted of 10 questions related to sociodemographic characteristics of the participants, 37 questions regarding attitudes toward speeding, and 1 question regarding speeding behavior. Subsequently, the sociodemographics were analyzed using binary logistic regression and the attitude variable was analyzed using factor analysis and binary logistic regression.

Results: The findings from the sociodemographic data revealed that male gender, single/separated status, broad driving experience, crash experience, and leisure/vacation trip purposes emerged as significant predictors for speeding behavior. Additionally, the results of factor analysis for the attitude variable revealed 3 components: Affective, behavioral, and cognitive. These 3 components are originally derived from the ABC model of attitude (affective, behavioral, and cognitive) that was adapted in this study. Furthermore, the findings from binary logistic regression appeared consistent with the model assumption, signifying that behavioral aspects significantly influenced speeding behavior among drivers. Nevertheless, affective and cognitive components were insignificant predictors. Furthermore, strong agreement with speeding countermeasures was observed among the participants.

Conclusion: In conclusion, sociodemographic characteristics and attitude have been proven to affect speeding behavior among drivers on Malaysian federal roads. The findings have important implications in designing driver risk profiles on federal roads to develop suitable countermeasures based on the 4E approach (engagement, education, enforcement, and engineering) to enhance road safety.     

Spatial relationships between alcohol outlet densities and drunk driving crashes: An empirical study of Tianjin in China

Introduction: Numerous studies have demonstrated the close relationship between alcohol availability and alcohol-related crashes. However, there is still a lack of spatial empirical analysis regarding this relationship, particularly in large cities of developing countries. Differences in alcohol outlets and drinking patterns in these cities may lead to quite different patterns of crash outcomes. Method: 3356 alcohol-related crashes were collected from the blood-alcohol test report of a forensic institution in Tianjin, China. Density of alcohol outlets such as retail locations, entertainment venues, restaurants, hotels, and companies were extracted based on 2114 Traffic Analysis Zones (TAZ) together with the residential and demographic characteristics. After applying the exploratory spatial data analysis, this research developed and compared the traditional Ordinary Least Square model (OLS), Spatial Lag Model (SLM), Spatial Error Model (SEM) and Spatial Durbin Model (SDM) to explore spatial effects of all the variables. Results: The results of incremental spatial autocorrelation show that the most significant distance threshold of alcohol-related roadway traffic crashes is 3 km. The SDM is found to be the optimal spatial model to characterize the relationship between alcohol outlets and crashes. The number of alcohol-involved traffic crashes is positively related to population density and retail density, but negatively related to the company density, hotel density, and residential density within the same TAZ. Meanwhile, dense population and hotels have reverse spillover effects in adjacent zones. Conclusions: The significant spatial direct effect and spillover effect of alcohol outlet densities on drunk driving crashes should not be neglected. These findings could help improve transportation planning, traffic law enforcement and traffic management for large cities in developing countries.     

Road traffic accident severity analysis: A census-based study in China

Background: In China, despite the decrease in average road traffic fatalities per capita, the fatality rate and injury rate have been increasing until 2015. Purpose: This study aims to analyze the road traffic accident severity in China from a macro viewpoint and various aspects and illuminate several key causal factors. From these analyses, we propose possible countermeasures to reduce accident severity. Method: The severity of traffic accidents is measured by human damage (HD) and case fatality rate (CFR). Different categorizations of national road traffic census data are analyzed to evaluate the severity of different types of accidents and further to demonstrate the key factors that contribute to the increase in accident severity. Regional data from selected major municipalities and provinces are also compared with national traffic census data to verify data consistency. Results: From 2000 to 2016, the overall CFR and HD of road accidents in China have increased by 19.0% and 63.7%, respectively. In 2016, CFR of freight vehicles is 33.5% higher than average; late-night accidents are more fatal than those that occur at other periods. The speeding issue is severely becoming worse. In 2000, its CFR is only 5.3% higher than average, while in 2016, the number is 42.0%. Conclusion and practical implementation: A growing trend of accident severity was found to be contrasting to the decline of road traffic accidents. From the analysis of casual factors, it was confirmed that the release way of the impact energy and the protection worn by the victims are key variables contributing to the severity of road traffic accidents.     

Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data

IntroductionDriving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction.MethodCrash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models.ResultsModel estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood.ConclusionsThe study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated.     

Effect of pavement condition and geometrics at signalised intersections on casualty crashes

IntroductionThis study investigated the effects of pavement surface condition and other control factors on casualty crashes at signalized intersections. It involved conducting a before and after study for road surface condition and situational factors. It also included assessing the effects of geometric characteristics on safety performance of signalized intersections post resurfacing to control for the effect of pavement surface condition. Pavement surface condition included roughness, rutting, and skid resistance. The control factors included traffic volume, light and surface moisture condition, and speed limit. The geometric characteristics included approach width, number of lanes, intersection depth, presence of median, presence of shared lane, and presence of bus stop.MethodTo account for the repeated observations of the effect of light and surface moisture conditions in four occasions (day-dry, day-wet, night-dry and night-wet) Generalized Estimating Equation (GEE) with Negative Binomial (NB) and log link function was applied. For each signalized intersection in the sample, condition data are collected for the year before and after the year of surface treatment. Crash data, however, are collected for a minimum of three and maximum of five years before and after treatment years.ResultsThe results show that before treatment, light condition, road surface moisture condition, and skid resistance interaction with traffic volume are the significant contributors to crash occurrence. For after treatment; light condition, road surface moisture condition, their interaction product, and roughness interaction with light condition, surface moisture condition, and traffic volume are the significant contributors. The geometric variables that were found to have significant effects on crash frequency post resurfacing were approach width interactions with presence of shared lane, bus stop, or median.ConclusionsThe findings confirm that resurfacing is significant in reducing crash frequency and severity levels.Practical Applications: The study findings would help for better understanding of how geometric characteristics can be improved to reduce crash occurrence.     

Investigation of speed and trajectory of motorcycle riders at curved road sections of two-lane rural roads under diverse lighting conditions

Introduction: Vehicular accidents at horizontal curves are over-represented compared to accidents that occur at tangent sections. Investigations have been conducted aimed at identifying the major causes that result in higher accident risk, both in terms of severity and rate, at curved road sections. Excessive or abrupt changes in speeding and improper vertical position are cited as major factors of lane departure, whereas other factors (either human or environmental) have also been documented. However, most research involves 4-wheel vehicles rather than other modes of transport that behave differently. More specifically, while motorcyclist fatalities occur more frequently than passenger vehicles, when accounting for vehicle distance traveled only a limited number of research studies address their behavior at curved road sections. Method: This paper presents the findings of field operational tests carried out by motorcyclists along two-lane rural roads with a wide range of horizontal curves using an instrumented motorcycle. Key objectives of the research included the conditions under which the motorcyclists differentiate their trajectory in regards to the direction of the horizontal curves, the correlation between the trajectory and the geometry of the road, and the impact of the lighting conditions on riders’ behavior. Results: The research showed that motorcyclists tend to ride closer to the centerline of the road, neglect the hazards associated with dim lighting conditions, and maintain constant speed in the left hand and the right-hand horizontal curves.