基于驾驶模拟的自动驾驶接管行为研究

为探索有条件自动驾驶对非驾驶相关任务的允准边界,基于实车驾驶模拟器,设计自动驾驶接管试验典型场景,招募30名被试者开展驾驶模拟试验;要求驾驶人执行3种分心形式的驾驶次任务,系统发出接管请求提示后,驾驶人接管车辆控制权以避免险情发生,并分析驾驶人接管反应时间、驾驶负荷以及驾驶绩效等相关数据.结果表明:驾驶次任务涉及的分心...     

Test procedure for evaluating the human–machine interface of vehicles with automated driving systems

Abstract

Objective: The human–machine interface (HMI) is a crucial part of every automated driving system (ADS). In the near future, it is likely that—depending on the operational design domain (ODD)—different levels of automation will be available within the same vehicle. The capabilities of a given automation level as well as the operator’s responsibilities must be communicated in an appropriate way. To date, however, there are no agreed-upon evaluation methods that can be used by human factors practitioners as well as researchers to test this.

Methods: We developed an iterative test procedure that can be applied during the product development cycle of ADS. The test procedure is specifically designed to evaluate whether minimum requirements as proposed in NHTSA’s automated vehicle policy are met.

Results: The proposed evaluation protocol includes (a) a method to identify relevant use cases for testing on the basis of all theoretically possible steady states and mode transitions of a given ADS; (b) an expert-based heuristic assessment to evaluate whether the HMI complies with applicable norms, standards, and best practices; and (c) an empirical evaluation of ADS HMIs using a standardized design for user studies and performance metrics.

Conclusions: Each can be used as a stand-alone method or in combination to generate objective, reliable, and valid evaluations of HMIs, focusing on whether they meet minimum requirements. However, we also emphasize that other evaluation aspects such as controllability, misuse, and acceptance are not within the scope of the evaluation protocol.     

Improvement of driver active interventions during automated driving by displaying trajectory pointers—A driving simulator study

Abstract

Objective: The handover of vehicle control from automated to manual operation is a critical aspect of interaction between drivers and automated driving systems (ADS). In some cases, it is possible that the ADS may fail to detect an object. In this event, the driver must be aware of the situation and resume control of the vehicle without assistance from the system. Consequently, the driver must fulfill the following 2 main roles while driving: (1) monitor the vehicle trajectory and surrounding traffic environment and (2) actively take over vehicle control if the driver identifies a potential issue along the trajectory. An effective human–machine interface (HMI) is required that enables the driver to fulfill these roles. This article proposes an HMI that constantly indicates the future position of the vehicle.

Methods: This research used the Toyota Dynamic Driving Simulator to evaluate the effect of the proposed HMI and compares the proposed HMI with an HMI that notifies the driver when the vehicle trajectory changes. A total of 48 test subjects were divided into 2 groups of 24: One group used the HMI that constantly indicated the future position of the vehicle and the other group used the HMI that provided information when the vehicle trajectory changed.

The following instructions were given to the test subjects: (1) to not hold the steering wheel and to allow the vehicle to drive itself, (2) to constantly monitor the surrounding traffic environment because the functions of the ADS are limited, and (3) to take over driving if necessary.

The driving simulator experiments were composed of an initial 10-min acclimatization period and a 10-min evaluation period. Approximately 10?min after the start of the evaluation period, a scenario occurred in which the ADS failed to detect an object on the vehicle trajectory, potentially resulting in a collision if the driver did not actively take over control and manually avoid the object.

Results: The collision avoidance rate of the HMI that constantly indicated the future position of the vehicle was higher than that of the HMI that notified the driver of trajectory changes, χ² = 6.38, P < .05. The steering wheel hands-on and steering override timings were also faster with the proposed HMI (t test; P < .05).

Conclusions: This research confirmed that constantly indicating the position of the vehicle several seconds in the future facilitates active driver intervention when an ADS is in operation.     

Functional decomposition—A contribution to overcome the parameter space explosion during validation of highly automated driving

Abstract

Objective: Particular testing by functional decomposition of the automated driving function can potentially contribute to reducing the effort of validating highly automated driving functions. In this study, the required size of test suites for scenario-based testing and the potential to reduce it by functional decomposition are quantified for the first time.

Methods: The required size of test suites for scenario-based approval of a so-called Autobahn-Chauffeur (SAE Level 3) is analyzed for an exemplary set of scenarios. Based on studies of data from failure analyses in other domains, the possible range for the required test coverage is narrowed down and suitable discretization steps, as well as ranges for the influence parameters, are assumed. Based on those assumptions, the size of the test suites for testing the complete system is quantified. The effects that lead to a reduction in the parameter space for particular testing of the decomposed driving function are analyzed and the potential to reduce the validation effort is estimated by comparing the resulting test suite sizes for both methods.

Results: The combination of all effects leads to a reduction in the test suites’ size by a factor between 20 and 130, depending on the required test coverage. This means that the size of the required test suite can be reduced by 95–99% by particular testing compared to scenario-based testing of the complete system.

Conclusions: The reduction potential is a valuable contribution to overcome the parameter space explosion during the validation of highly automated driving. However, this study is based on assumptions and only a small set of exemplary scenarios. Thus, the findings have to be validated in further studies.     

体系安全性分析的双层次框架

为识别体系(So S)中的薄弱环节、评价威胁风险并提高体系安全性,根据安全系统工程和体系工程理论,提出体系安全性基本概念。基于复杂网络科学和传统安全分析技术,提出一种双层次分析框架,从脆弱性角度和威胁风险角度研究体系安全性。脆弱性分析可从拓扑结构和非拓扑因素2方面识别对体系安全较关键的脆弱点;威胁风险分析能得到脆弱点面临的任意威胁组合,并识别后果较严重的威胁风险。结果表明:体系安全性包括宏观的脆弱性应对能力,和微观的威胁风险控制能力。体系安全性分析需宏观和微观双层次相结合,全面考虑体系安全性诸因素。基于识别结果的威胁评价将提高安全分析的针对性和效率。     

Multi-agent traffic simulations to estimate the impact of automated technologies on safety

Abstract

Objective: The objective of this article was to develop a multi-agent traffic simulation methodology to estimate the potential road safety improvements of automated vehicle technologies.

Methods: We developed a computer program that merges road infrastructure data with a large number of vehicles, drivers, and pedestrians. Human errors are induced by modeling inattention, aimless driving, insufficient safety confirmation, misjudgment, and inadequate operation. The program was applied to simulate traffic in a prescribed area in Tsukuba city. First, a 100% manual driving scenario was set to simulate traffic for a total preset vehicle travel distance. The crashes from this simulation were compared with real-world crash data from the prescribed area from 2012 to 2017. Thereafter, 4 additional scenarios of increasing levels of automation penetration (including combinations of automated emergency braking [AEB], lane departure warning [LDW], and SAE Level 4 functions) were implemented to estimate their impact on safety.

Results: Under manual driving, the system simulated a total of 859 crashes including single-car lane departure, car-to-car, and car-to-pedestrian crashes. These crashes tended to occur in locations similar to real-world crashes. The number of crashes predicted decreased to 156 cases with increasing level of automation. All of the technologies considered contributed to the decrease in crashes. Crash reductions attributable to AEB and LDW in the simulations were comparable to those reported in recent field studies. For the highest levels of automation, no assessment data were available and hence the results should be carefully treated. Further, in modeling automated functions, potentially negative aspects such as sensing failure or human overreliance were not incorporated.

Conclusions: We developed a multi-agent traffic simulation methodology to estimate the effect of different automated vehicle technologies on safety. The crash locations resulting from simulations of manual driving within a limited area in Japan were preliminary assessed by comparison with real-world crash data collected in the same area. Increasing penetration levels of AEB and LDW led to a large reduction in both the frequency and severity of rear-end crashes, followed by car-to-car head-on crashes and single-vehicle lane departure crashes. Preliminary estimations of the potential safety improvements that may be achieved with highly automated driving technologies were also obtained.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

The use and safety of medications known to affect driving in Jordan: A cross-sectional study

Objectives: The aim of this study was to estimate the main driving-impairing medications used by drivers in Jordan, the reported frequency of medication side effects, the frequency of motor vehicle crashes (MVCs) while using driving-impairing medicines, as well as factors associated with MVCs.

Methods: A cross-sectional study involving 1,049 individuals (age 18–75 years) who are actively driving vehicles and taking at least one medication known to affect driving (anxiolytics, antidepressants, hypnotics, antiepileptics, opioids, sedating antihistamines, hypoglycemic agents, antihypertensives, central nervous system [CNS] stimulants, and herbals with CNS-related effects) was conducted in Amman, Jordan, over a period of 8 months (September 2013–May 2014) using a structured validated questionnaire.

Results: Sixty-three percent of participants noticed a link between a medicine taken and feeling sleepy and 57% stated that they experience at least one adverse effect other than sleepiness from their medication. About 22% of the participants reported having a MVC while on medication. Multiple logistic regression analysis showed that among the participants who reported having a crash while taking a driving-impairing medication, the odds ratios were significantly higher for the use of inhalant substance (odds ratio [OR] = 2.787, P = .014), having chronic conditions (OR = 1.869, P = .001), and use of antiepileptic medications (OR = 2.348, P = .008) and significantly lower for the use of antihypertensives (OR = 0.533, P = .008).

Conclusion: The study results show high prevalence of adverse effects of medications with potential for driving impairment, including involvement in MVCs. Our findings highlight the types of patient-related and medication-related factors associated with MVCs in Jordan, such as inhalant use, presence of chronic conditions, and use of antiepileptics.     

Comparing safety climate factors as predictors of work-related driving behavior

INTRODUCTION: Research suggests safety climate (SC) is a strong predictor of safety-related outcomes in organizations. This study explores the relationship between six SC dimensions and four aspects of work-related driving. METHOD: The SC factors measured were "communication and procedures," "work pressures," "relationships," "safety rules," "driver training," and "management commitment." The aspects of self-reported occupational driving measured were traffic violations, driver error, driving while distracted, and pre-trip vehicle maintenance. RESULTS: Hierarchical regression analyses revealed that the SC factors accounted for significant amounts of variance in all four aspects of work-related driving, over and above the control factors of age, sex, and work-related driving exposure. However, further investigation indicated certain SC factors (particularly safety rules, communication, and management commitment) were more strongly related to specific aspects of work-related driving behavior than others. Together, the SC factors were better able to predict self-reported distraction from the road than the other aspects of driving behavior measured. Implications for occupational safety, particularly for the management of work-related drivers are discussed.     

Stability and safety evaluation of mixed traffic flow with connected automated vehicles on expressways

Introduction: Connected automated vehicles (CAVs) technology has deeply integrated advanced technologies in various fields, providing an effective way to improve traffic safety. However, it would take time for vehicles on the road to vehicles from human-driven vehicles (HDVs) progress to CAVs. Moreover, the Cooperative Adaptive Cruise Control (CACC) vehicle would degrade into the Adaptive Cruise Control (ACC) vehicle due to communication failure. Method: First, the different car-following models are used to capture characteristics of different types of vehicles (e.g., HDVs, CACC, and ACC). Second, the stability of mixed traffic flow is analyzed under different penetration rates of CAVs. Then, multiple safety measures, such as standard deviation of vehicle speed (SD), time exposed rear-end crash risk (TER), time exposed time-to-collision (TET), and time-integrated time-to-collision (TIT) are used to evaluate the safety of mixed traffic flow on expressways. Finally, the sensitivity of traffic demand, the threshold of time-to-collision (TTC), and the parameters of car-following models are analyzed based on a numerical simulation. Results: The results show that the ACC vehicle has no significant impact on the SD of mixed traffic flows, but it leads to the deterioration of TET and TIT, making the reduction proportion of TER slower. When the penetration rate exceeds 50%, the increase of CACC vehicles reduces traffic safety risks significantly. Furthermore, the increase in traffic demand and car-following parameters worsens traffic safety on expressways. Conclusions: This paper suggests that the CACC vehicles degenerate into ACC vehicles due to communication failure, and the safety risk of mixed traffic flow increases significantly. Practical Applications: The application of CAVs can improve the stability and safety of traffic flow.     

Deterioration of the useful visual field with ageing during simulated driving in traffic and its possible consequences for road safety

A previous study has shown that the useful visual field deteriorates in a simulated road traffic situation as a function of the driver’s age and of the vehicle’s speed under monotonous conditions [Rogé, J., Pébayle, T., Lambilliotte, E., Spitzenstetter, F., Giselbrecht, D., Muzet, A., 2004. Influence of age, speed and duration of monotonous driving task in traffic on the driver’s useful visual field. Vision Research 44 (23), 2737–2744]. The aim of this new experiment is to study the effects of traffic density and age on the useful visual field of the driver during a simulated driving task with controlled traffic characteristics (speed, number of cars) for all participants. In total, 10 young drivers (m = 28.2 years) and 10 older drivers (m = 51.2 years) followed a car in road traffic at an average speed of 126 km h⁻¹ during two 2 h sessions corresponding to two conditions of traffic (light traffic, with five vehicles around the participant; and heavy traffic, with nine vehicles). While following this vehicle, the driver had to detect changes in the colour of a signal located in the central part of his or her visual field and a signal that appeared at different eccentricities on the rear lights of other vehicles in the traffic. Analysis of the data indicated that age interacted with the location of the peripheral signal and density of traffic interacted with the duration of driving. The implications of these results are discussed in terms of road safety and in terms of models of deterioration of the useful visual field (general interference and tunnel vision).     

基于云模型的城轨信号系统安全保障能力评价方法

为准确评价城轨信号系统安全保障能力及影响因素,基于云理论对定性与定量因素的良好融合优点,构建城轨信号系统安全保障能力评价云模型及评价指标体系,采用组合赋权法对各指标赋予权重,并基于专家意见,利用正向云发生器生成标准云.结果表明:该云模型具有一定稳定性和可靠性,可对城轨信号系统安全保障能力进行有效测评,同时能够发现安全运...     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.     

视觉记忆型次任务对驾驶绩效及安全的影响

为研究视觉记忆型次任务对驾驶绩效及安全的影响,采用对未知内容的记忆任务和对已知内容的再认任务分别表征工作记忆和长时记忆过程,构建多组不同难度的次任务,基于标准换道试验环境LCT进行双任务研究。提取并分析驾驶人执行不同任务时车道保持、换道控制等指标的差异以及次任务绩效,基于主客观数据构建综合评判模型。结果表明:双任务驾驶条件下,车辆平均路径偏差、方向盘平均转向角、车道偏移次数指标增大,正确换道比例减小,感知负荷增大,总绩效下降。困难工作记忆组与简单工作记忆组相比,随着任务难度增大,换道控制绩效下降,感知负荷增大,总绩效下降36.1%;困难再认组与工作记忆组相比,车道保持绩效、换道控制绩效提高,感知负荷下降,总绩效提高50%;简单再认组与工作记忆组相比,总绩效变化不大;困难工作记忆组综合绩效最低。上述结果说明:随着次任务难度增大,总绩效下降,但将对未知内容的工作记忆过程转化为对已知内容的再认过程时,总绩效明显提升,这一特点在任务难度较大时更为显著。     

安全生产规划体系框架探讨

阐述了建立安全生产规划体系的必要性,探讨了安全生产规划的定义、研究对象、目的和内容,指出安全生产规划是为使安全生产与经济社会协调发展而预先对未来一段时间内各项安全生产工作所做的时间和空间的合理安排,具有整体性、综合性、动态性、前瞻性、信息密集和政策性强等特征。同时设计了"四级、三层"的安全生产规划体系,即在行政层级上分为国家级、省级、市级和县级四个层级,在协调作用上分为宏观指导层、项目布局层和方案实施层三个层次。国家安全生产规划从宏观上对全国安全生产工作做出谋划与部署,省级安全生产规划要接受国家安全生产规划宏观指导性的引导和要求,并结合各地实际进行项目布局,同时借助专项规划分解内容,制定市、县级规划实施方案。     

高速公路交通流实时安全性评价

根据多条高速公路近3年的事故数据及实时交通流数据,分析了高速公路运营安全性的相关影响因素,在此基础上提出了车速变异系数指标及其分级标准,建立了考虑交通流量、平均车速、车速变异系数、天气条件等多因素的高速公路交通流运行风险预测多元模型,并提出了高速公路交通流实时行车风险指数TRI指标,制定了交通流状态实时安全性评价标准,最后给出了高速公路交通流混合交通状态下的实时安全风险评价流程。通过西攀高速公路的交通流实时数据,验证了模型的有效性。     

2006年促进职业安全与健康框架公约和建议书介绍及相关问题探讨

《2006年促进职业安全与健康框架公约》(C187,2006)和《职业安全与健康框架建议书》(R197,2006)的公布是为了进一步减少全球发生的大量职业性伤病和死亡,保护工人免受因就业而引发的病患和伤害,降低职业性伤病和死亡对劳动生产率和经济与社会发展的负面影响。本文对《公约》及《建议书》的主要内容,包括《公约》中的定义、《公约》制定的目标、国家政策、国家制度、国家计划等进行了详细的介绍和分析,以期继续推广预防性安全健康文化建设。     

A油气田公司安全文化评价指标体系初探

深入研究了国内外学者安全文化与安全文化评价指标体系相关成果,结合油气田企业的安全生产实际,从定量、定性分析两个方面构建了适合A油气田公司安全文化评价体系.同时采用层次分析法确定安全文化评价体系各指标的权重,结合专家定性评价、员工问卷调查、安全生产定量指标多种赋分方式,客观和全面的评价了油气田公司安全文化建设现状.评价结果对指导油气田企业安全文化建设和提升企业安全文化水平具有现实意义.     

Enhancing older driver safety: A driving survey and evaluation of the CarFit program

Objective

To evaluate CarFit, an educational program designed to promote optimal alignment of driver with vehicle.

Methods

A driving activity survey was sent to 727 randomly selected participants living in retirement communities. Drivers (n = 195) were assigned randomly to CarFit intervention (n = 83, M age = 78.1) or Comparison (n = 112, M age = 79.6) groups. After 6 months, participants completed a post-test of driving activity and CarFit recommendations.

Results

Nonconsenting drivers were older and participated in fewer driving activities. CarFit participation was moderate (71%) with 86% of the participants receiving recommendations. 60% followed the recommendations at the 6-month re-evaluation). The CarFit (67.6%) and Comparison (59.3%) groups reported at least one type of self-regulation of driving activity at baseline. There was no significant change in the driving behaviors at the six-month follow-up.

Conclusion

CarFit was able to detect addressable opportunities that may contribute to the safety of older drivers.

Impact on industry

CarFit recommendations may need stronger reinforcement in order to be enacted by a participant.     

航空公司安全信息管理水平评价方法研究

分析了目前我国航空公司在安全信息管理和安全信息管理水平综合评价方面存在的问题.从航空公司安全信息管理的实际工作出发,结合安全管理体系(SMS)中对于安全信息管理的要求,建立了航空公司安全信息管理水平评价指标体系,并针对每个评价指标建立了4个等级的评价标准.基于主成分分析方法建立了航空公司安全信息管理水平综合评价模型.按照建立的指标体系和评价标准对5家航空公司进行了安全信息管理水平评分,并以此数据为基础,利用建立的综合评价模型对5家公司的安全信息管理水平进行了综合评价和排序,针对评价结果对各航空公司提高安全信息管理水平提出了具体的建议措施.