A roadside simulation of road crossing for children

A simple and safe method is proposed for giving children practical experience similar to crossing the road and for assessing their performance. The method comprises a ‘pretend road’ laid out on the pavement, which the child crosses as if crossing the adjacent road in the face of oncoming vehicles. A comparison of adult performances in crossing through gaps in traffic on pretend and real roads indicates that the pretend task adequately simulates real road crossing. Similar experiments on pretend roads with 5-10 year olds crossing through gaps in traffic indicated that children are able to understand the simulation task and perform sensibly on it. Moreover, there were children of all ages who consistently performed at close to an adult level indicating that the visual timing required in the skill is not beyond young children. The results suggest that children should be trained in crossing in the presence of traffic at an early age. The pretend task could prove a valuable aid to training.     

基于电涡流传感器的车辆超速检测研究

车辆超速行驶是引发交通事故的重要因素。本文以单车道为例,在公路上相距一段距离埋设两个电涡流传感器,当汽车通过电涡流传感器时,产生脉冲信号,通过单片机编程对信号进行实时处理,最终得到汽车的行驶速度。实验表明,此方法可有效检测和记录各路段超速行驶的车辆,最终达到让驾驶员自觉遵纪守法、遵章驾驶和降低交通事故发生率,提高安全和畅通行车能力的目的。     

An empirical study of subjective road categorization

Abstract

Driver behaviour will partially be a function of the cognitive schemata by which drivers represent features, functions and operations of traffic system components. This paper uses the Repertory Grid Technique to address the questions: (1) How do drivers internally represent different categories of road? (2) How are those representations mapped on to ‘official’ road categories?

A factor analysis of data obtained from 40 subjects revealed, in answer to question (1), that four factors, namely, ‘safety’; ‘urban/rural’; ‘road boundaries/slip-roads’; and ‘markings’; accounted for 82·3% of the variance. Multidimensional scaling and clustering analyses showed that subjective categorizations of roads are closely related to their objective physical characteristics, but less-well determined by ‘official’ road categories.

Certain features (e.g. slip-roads, markings, obstacle-free boundaries) appear to contribute little to the subjective safety of roads. This suggests that the potential benefits of these safety features may be fully achieved since risk compensation mechanisms will not operate.     

Road-edge delineation in rural areas: effects on driving behaviour

When driving on lower-category Dutch rural roads without any delineation, drivers are likely to drift off the road with their right-side wheels, thus incurring damage to the pavement edge or even leading to accidents. In two experiments, two types of road-edge delineation, with continuous or dashed edge lines, were compared with two control roads without lines or with only a dashed line on the road axis. The first experiment consisted of non-obtrusive video recordings of passing traffic. Vehicle position on the experimental roads was more to the road's centre than on the control roads. The second experiment was a driving test with an instrumented vehicle, during daytime lighting and during darkness. Again, vehicle lateral position was more central on the experimental roads, especially during darkness. Subjects could safely pass oncoming vehicles. Driving speed increased on the experimental roads compared with the unlined control road, but not beyond speeds found on the axis-lined control road. Driver's mental effort while driving over the experimental roads did not differ from the effort while driving over the control roads. Subjectively rated effort was higher for the unlined control road than for the three other roads. Subjects preferred the edge-lined roads to the unlined control road, but not more than the axis-lined control road. It was concluded that edge-lines may provide a simple and effective way of inducing a more favourable lateral position on rural roads without having negative effects on subjective appraisal, driving performance or mental workload.     

Road-edge delineation in rural areas: effects on driving behaviour

When driving on lower-category Dutch rural roads without any delineation, drivers are likely to drift off the road with their right-side wheels, thus incurring damage to the pavement edge or even leading to accidents. In two experiments, two types of road-edge delineation, with continuous or dashed edge lines, were compared with two control roads without lines or with only a dashed line on the road axis. The first experiment consisted of non-obtrusive video recordings of passing traffic. Vehicle position on the experimental roads was more to the road's centre than on the control roads. The second experiment was a driving test with an instrumented vehicle, during daytime lighting and during darkness. Again, vehicle lateral position was more central on the experimental roads, especially during darkness. Subjects could safely pass oncoming vehicles. Driving speed increased on the experimental roads compared with the unlined control road, but not beyond speeds found on the axis-lined control road. Driver's mental effort while driving over the experimental roads did not differ from the effort while driving over the control roads. Subjectively rated effort was higher for the unlined control road than for the three other roads. Subjects preferred the edge-lined roads to the unlined control road, but not more than the axis-lined control road. It was concluded that edge-lines may provide a simple and effective way of inducing a more favourable lateral position on rural roads without having negative effects on subjective appraisal, driving performance or mental workload.     

Driver information system: a combination of augmented reality,deep learning and vehicular Ad-hoc networks

Improving traffic safety is one of the important goals of Intelligent Transportation Systems (ITS). In vehicle-based safety systems, it is more desirable to prevent an accident than to reduce severity of injuries. Critical traffic problems such as accidents and traffic congestion require the development of new transportation systems. Research in perceptual and human factors assessment is needed for relevant and correct display of this information for maximal road traffic safety as well as optimal driver comfort. One of the solutions to prevent accidents is to provide information on the surrounding environment of the driver. Augmented Reality Head-Up Display (AR-HUD) can facilitate a new form of dialogue between the vehicle and the driver; and enhance ITS by superimposing surrounding traffic information on the users view and keep drivers view on roads. In this paper, we propose a fast deep-learning-based object detection approaches for identifying and recognizing road obstacles types, as well as interpreting and predicting complex traffic situations. A single convolutional neural network predicts region of interest and class probabilities directly from full images in one evaluation. We also investigated potential costs and benefits of using dynamic conformal AR cues in improving driving safety. A new AR-HUD approach to create real-time interactive traffic animations was introduced in terms of types of obstacle, rules for placement and visibility, and projection of these on an in-vehicle display. The novelty of our approach is that both global and local context information are integrated into a unified framework to distinguish the ambiguous detection outcomes, enhance ITS by superimposing surrounding traffic information on the users view and keep drivers view on roads.     

Effects of experience and processing demands on visual information acquisition in drivers

This study investigated the differences between novices and experienced drivers in their distribution of visual attention under different levels of cognitive load imposed by different types of road, and as reflected in their visual search strategies. The task involved a 20-min drive on various roads while the drivers' eye movements were recorded. The measures taken included fixation durations, as an indicator of the time taken to assimilate fixated objects, and the variance of fixation co-ordinates to describe the spread of search in both the horizontal and vertical axes. Differences were found between novices and experienced drivers according to the type of road being driven. The results suggested that experienced drivers select visual strategies according to the complexity of the roadway, and that the strategies of novices are too inflexible to meet changing demands.     

DRIVERS' GALVANIC SKIN RESPONSE AND THE RISK OF ACCIDENT

Galvanic skin responses of 20 drivers were measured in two studies covering a wide range of roads and road conditions. Accident histories wore obtained for the roads in one of the studies. It is shown that the level of GSR activity does not depend primarily on the nature of the road or conditions. Consistent sources of variation in the GSR are observed, one of them apparently being the subject's experience of driving. The distribution of GSR per unit distance travelled was found to be similar to the distribution of accidents per unit total distance of vehicle travel (the accident rate). The results support a view that driving is a self-paced task governed' by the level of emotional tension or anxiety which the driver wishes to tolerate. The possible effects of this on the distribution of accidents is discussed.     

时间递推耦合神经网络的交通路径动态诱导技术

通过"人—机—环境"耦合关系,对路况与时间变化关系进行研究。综合车辆运行过程中不同时段的路况差异和人因作用、突发道路事故随机性,以神经网络有师学习作为经验累积方法,提出时间递推预测方法确定路径最短时间,从而实现对交通路径的动态诱导。递推预测以知识库累积经验与实时路况信息作比较,为驾驶者提供实时有效的路况信息支撑。结果表明,该诱导技术可辅助驾驶者及时对路况作出正确判断,减少因经验不足和突发事件造成的时间损失,适用于安装有GPS导航的车辆。实例分析表明,所构建模型与实际数据结合收到良好效果。     

Older people, driving and new technology

There are increasing numbers of older car users on the roads today. This paper examines the particular problems that older people experience as drivers and evaluates the role of road transport informatics (RTI) as a means for enhancing driver capabilities and improving road safety. Implications for product design are also discussed.     

VIPER: an adaptive guidance and notification service system in internet of vehicles

In recent years, Internet of Vehicles has attracted increasing research attention, especially from the viewpoint of establishing effective information transmission methods to aid drivers and road users. Drivers can currently receive numerous types of assisted information. However, too much and cluttered information may affect their driving performance. Thus, effective guidance and notification services should be provided to drivers according to time, location, and events. For this purpose, we propose a Message Queue Telemetry Transport-based adaptive guide and notification service system called VIPER to provide driving assistance information. VIPER adaptively provides information to drivers and road users based on five conditions: Vehicle, points of Interest, People, Environment, and Roads. First, we establish a hierarchical grid architecture that is used to provide location-based services. Second, we collect information from the vehicles, roads, and environmental sensors to produce a weighted road network. Then, guide and notification services are provided based on this network. Thus, we can provide real-time driving assistance and help drivers to increase their safety and avoid traffic jams. We also analyze historical traffic data collected from vehicle detectors and accident data to estimate the safety and accident risk degrees of roads. To verify the feasibility of the proposed system, a system prototype is implemented to provide guidance and notification services. The experimental results show that our system can effectively assist drivers and road users and that it has a low system response time.

     

Drivers’ Performance Examination using a Personalized Adaptive Curve Speed Warning: Driving Simulator Study

ABSTRACT

A great number of traffic accidents occur during curve negotiation maneuvers. Most of these accidents could be avoided if drivers are provided with information that better guide them through the maneuver. Advanced Driver Assistance Systems (ADAS) such as Curve Speed Warning (CSW) have shown to be effective to improve safety on curve maneuvers by warning drivers of the speed required to make a safe curve maneuver. The effectiveness of such warning systems can potentially improve if the warnings are not only adapted to road and traffic condition but also adapted to individual drivers’ behavior. In this study, an Adaptive Curve Speed Warning (ACSW) system is developed that presents drivers a two-level visual and audio warning considering the variation in individual drivers’ perception-reaction time (PRT). The warning timing is adjusted according to a reward/punishment function to reinforce safer actions while providing an individualized in-time warning. Next, within a driving simulator environment, drivers’ performance using ACSW is compared to a CSW that does not consider PRT variation among drivers. Further, variation in drivers’ performance on curve maneuvers is discussed with respect to drivers’ approaching speed, variation in PRT, and braking behavior. Results show that drivers’ interaction with warning systems varies significantly based on their age and gender. In addition, results show how drivers approaching speed to a curve varies significantly based on road characteristics such as curve advisory speed and curve direction. Results from this study contribute to the development of more intelligent ADAS that could improve drivers’ comfort and safety.     

Increasing wide-area download throughputs on the roads by trunking multiple cellular channels over a vehicular ad hoc network

To obtain infotainment services (e.g., traffic, maps, accidents, weather, etc.) on the roads, vehicle drivers and back-seat passengers may want to use wide-area networks (e.g., GPRS) to download useful information from the Internet when needed. In this paper, we design and implement a scheme to increase GPRS download throughput for a vehicle user while he (she) is moving on the roads. This scheme integrates inter-vehicle communication with trunking mechanisms to achieve this goal. This scheme can be readily deployed for any real-world GPRS network or any 3G network without any support from the network operator. Our field trial results show that when this scheme is applied in a motorcade of four vehicles and all of the GPRS channel provided by each vehicle are used to download a file simultaneously, the download speed is 3.92 times faster than that achieved when only one GPRS channel is used.     

The relation between driving experience and recognition of road signs relative to their locations

OBJECTIVES: Examine how driving experience and expectations affect the ability of experienced drivers to identify traffic signs--specifically, no right turn (NRT) and no left turn (NLT) at intersections. BACKGROUND: Failure to heed signs is a frequent cause of accidents, and the authors focused on the contributions of experience and expectancy to sign identification. METHOD: Inexperienced and experienced drivers were connected to an eye tracker system and briefly exposed to various traffic scenes. Some of the pictures included an NRT sign at the expected location (on the right), and some included the same sign at an unexpected location (on the left). The same procedure was used with an NLT traffic sign. RESULTS: Experienced drivers identified traffic signs better than inexperienced drivers did when the signs were posted at the expected location but identified them worse than did inexperienced drivers when they were at unexpected locations. CONCLUSIONS: With experience, drivers' expectations regarding the expected location of traffic signs become so strong that violating these expectancies results in more identification errors among experienced drivers than among inexperienced drivers. To optimize experienced drivers' traffic sign identification, signs must be located in accordance with drivers' expectations--specifically, on the right side of the road. APPLICATIONS: When signs are misplaced, crashes can be caused by inappropriate placement rather than inappropriate driving. Highway designers should ensure that their design conforms to standards that shape experienced drivers' expectations.     

基于VR的驾驶仿真及安全教育系统开发

针对全国道路交通事故高发现状及传统驾驶安全教育方式单一、培训效果差的缺点,基于虚拟现实技术（VR）,在引发交通事故人为因素理论基础上,开发驾驶仿真及安全教育系统。系统基于Unity3D引擎,构建了基于道路实景数据的虚拟场景,并联合SUMO实现了道路交通流仿真,通过VR技术仿真驾驶环境及驾驶行为;基于碰撞检测原理,建立了关卡违规触发机制,编码自定义屏幕空间渲染方式模拟驾驶员视觉效果,并构建了基于图像的交通事故现场三维全景,从认知、感知层面培训驾驶员安全驾驶。实用性测试结果表明,系统实现了不同道路场景、气象条件与交通状况下的驾驶模拟及安全培训,增强了使用者的学习兴趣,提高了使用者驾驶安全素养,具有较强的实用性。     

A localization method for stagnant water in city road traffic image

Stagnant water on roads has always been a major cause of traffic jams and accidents. Traditional urban waterlogging monitoring and warning system is mainly based on a large amount of historical data and predictive network, which has low accuracy and weak generalization ability. Considering the deep neural network algorithms have demonstrated strong capabilities in computer vision tasks such as object detection, we aim to apply them to road stagnant water detection. In this paper, a novel automatic stagnant water localization method under weak supervision based on visual image is proposed. First, the template matching method is applied to extract road information from the traffic image. Then, due to the complexity of data annotation, we locate stagnant water in image based on Class Activation Maps (CAM) mechanism, which is a weakly supervised method. The detection model consists of the ResNet-18 and the Grad-CAM++ mechanism. Finally, based on the heat map and template, we set a suitable threshold to segment stagnant water area in image. In the experiments, the precision and recall for road stagnant water classification by the proposed model are 99.39% and 99.60%, while the Intersection over Union (IoU) for stagnant water area segmentation is up to 63%. These show that our method is effective for road stagnant water localization.

     

基于数字图像的汽车驾驶员行驶状态判别

通过车载CCD图像传感器摄取图像，在利用中值滤波、边缘检测等图像处理技术去除噪声和获取道路标线的基础上，建立了摄像机的透视投影模型和汽车驾驶员行驶状态模型，研究了车辆行驶过程中相对道路标线的行驶状态参数，以监控驾驶员行车状况。实验证明，该方法获得的行驶状态参数曲线能有效判别驾驶员的行驶状态，为减少驾驶员人为因素导致的交通事故作了有益的探索。     

Visual attention while driving: sequences of eye fixations made by experienced and novice drivers

Eye fixations were recorded while novice and experienced drivers drove along three types of roads (rural, suburban and dual-carriageway). An analysis of the content of those fixations was performed in order to identify differences in the scanpaths that can be associated with skill acquisition and that can indicate a sensitivity to road type. This analysis itemized the part of the visual scene that was inspected with each fixation, and identified what the driver looked at as a function of what they had looked at previously. Single-fixation, two-fixation, and three-fixation patterns of eye-movements were identified. Differences in sequences of fixations were found between novice and experienced drivers on the three types of roads, with experienced drivers showing greater sensitivity overall, and with some stereotypical transitions in the visual attention of the novices. A number of individual sequences were identified, including a roadway preview pattern (alternating fixations between near and far views of the road ahead), and patterns involving mirror inspections that varied according to the road type.     

Visual attention while driving: sequences of eye fixations made by experienced and novice drivers

Eye fixations were recorded while novice and experienced drivers drove along three types of roads (rural, suburban and dual-carriageway). An analysis of the content of those fixations was performed in order to identify differences in the scanpaths that can be associated with skill acquisition and that can indicate a sensitivity to road type. This analysis itemized the part of the visual scene that was inspected with each fixation, and identified what the driver looked at as a function of what they had looked at previously. Single-fixation, two-fixation, and three-fixation patterns of eye-movements were identified. Differences in sequences of fixations were found between novice and experienced drivers on the three types of roads, with experienced drivers showing greater sensitivity overall, and with some stereotypical transitions in the visual attention of the novices. A number of individual sequences were identified, including a roadway preview pattern (alternating fixations between near and far views of the road ahead), and patterns involving mirror inspections that varied according to the road type.     

Insurance Classifications and Drivers' Galvanic Skin Response

Drivers' galvanic skin responses were recorded in town traffic and on country roads. Two groups of drivers were compared, those who would pay higher insurance premiums, by reason of their ago or occupation, and the rest. The high insurance group did not differ from the rest in the magnitude of the GSR. but when the ratio of the GSR in town traffic to that on a country road was considered there was a significant difference such that the high insurance group had a relatively greater GSR on the country road.

It is suggested that in town traffic most of the GSR arc generated by the actions of other drivers, whereas on the open road the GSRs are self generated by the subjects' driving. The GSR on the open road will therefore be more affected by the individual method of driving and by the risks the driver takes. The ratio of town GSR to country GSR can be used to eliminate the large unexplained differences between subjects and to expose the differences in driving behaviour