Development of a telematics evaluation environment based on a driving simulator and its application

For developing telematics devices, traditional development methods include the unit function test, compatibility test and T-Car, which have some limitations. Telematics devices have various functions that require accounting for the interactions among three major elements of automotive electronics: the vehicle, the device unit and driver. The KAAS (KATECH Advanced Automotive Simulator) system is a virtual-reality-based test environment designed to test and analyze the three elements in one place. One of the difficult functions when constructing such VR (Virtual Reality)-based telematics test environment is to develop a test method for the LBS (Location-Based Service) function such as a car navigation demanding the GPS (Global Positioning System) satellite signals because KAAS is in a fixed laboratory. To overcome these problems, a real-time GPS simulation system, which can be integrated with KAAS, is needed because the location of the vehicle in virtual space is determined purely by the driver’s personal intention while driving virtually. This paper presents new concepts needed to construct a VR-based telematics test environment to generate a GPS RF signal, which reflects the continuously changing vehicle location during virtual driving in real-time. To construct this system, the coordinate transform must be conducted from a rectangular coordinate system that is compatible with a virtual 3D DB that is used to construct a 3D image for KAAS using a WGS84 and a longitude-latitude coordinate system compatible with a GPS simulator. Moreover, the real-time HILS (Hardware In Loop Simulation) systems and the CDMA (Code Division Multiple Access) simulation system are developed to evaluate telematics devices. Finally, we show its applications and results.     

Application of a driving simulator to the development of in-vehicle human-machine-interfaces

The use of a driving simulator in the development of human-machine-interfaces (HMI) such as a navigation, information or entertainment system is discussed. Such use addresses the need to study and evaluate the characteristics of a candidate HMI early in the R&D and design stage to ensure that it is likely to meet various objectives and requirements, and to revise the HMI as may be necessary. Those HMI requirements include such things as usability, driver comfort, and an acceptable level of attentional demand in dual task conditions (driving while using an HMI). Typically, such an HMI involves an information display to the driver, and a means for driver input to the HMI. Corresponding simulator requirements are discussed, along with typical simulator features and components. The latter include a cab, control feel systems, visual image generator, real time scenario control (task definitions), a motion system (if provided), and data acquisition. Both fixed and moving base systems are described, together with associated benefits and tradeoffs. Considerations in the design of the evaluation experiment are discussed, including definition of primary and secondary tasks, and number of driver subjects (experimental participants). Possible response and performance measures for the primary and secondary tasks are noted, together with subjective measures such as task difficulty and ease of using the HMI. The advantages of using a driving simulator to support R&D are summarized. Some typical and example simulator uses are noted.     

In-vehicle display HMI safety evaluation using a driving simulator

Recently, telematics services and in-vehicle display devices such as the CNS (Car Navigation System) have become new causes of traffic accidents. These accidents are caused by ‘Inattention’ from the increase of the driver’s mental workload while he/she is driving. The driver of a vehicle (except for emergency or police vehicles) must not use a hand-held mobile phone while the vehicle is moving. To address this problem, Australia, England, Italy, Brazil and some states in the US have banned the use of hand-held mobile devices during driving. However, there are no restrictions on the use of in-vehicle displays or on the display’s positions. The position of a navigation system in a vehicle should be assessed objectively, and the effect of the position on the driver’s attention should be studied. Some existing research reports that in-vehicle distraction not only leads to reduced speeds and more frequent lane switching, but also more gazing by the driver to the centre of the road. In this study, to develop an assessment method and to propose the proper position of a CNS, an experiment is carried out in a driving simulator environment. Different methods to track the gaze and physical parameters of the driver are used for HMI (Human-Machine Interface) assessment. The experiment is carried out in a driving simulator to observe the glancing distribution during driving according to the position of the navigation system. Fourteen subjects participated in this experiment. Changes in subjects’ physiological signals and glancing distribution rates were collected.     

汽车驾驶模拟器在交通安全中的应用综述

汽车驾驶模拟器是1种研究“人‐车‐路‐环境”交通特性的重要工具,由于具有重现性好、安全性高、成本低等优势,被广泛应用于交通研究方面,尤其因其能够在危险场景中采集多种车辆数据,近年来汽车驾驶模拟器在交通安全方面的研究进展飞速。文中简要介绍了汽车驾驶模拟器的国内外发展历史,从驾驶分心、道路设计、交通设计、交通事故和驾驶疲劳5个方面梳理出汽车驾驶模拟器在交通安全领域的应用研究,并分析了这5个方面研究领域中驾驶模拟器实验的其中利弊,探讨了汽车驾驶模拟器在中国交通安全研究中的应用前景及存在的问题。      

Urban driving cycle for performance evaluation of electric vehicles

Nowadays, a number of environmental issues have seriously come to the fore. For this reason, the R & D spending on eco-friendly vehicles that use electric power has been gradually increasing. In general, fuel economy and pollutant emissions of both conventional and eco-friendly vehicles are measured through chassis dynamometer tests that are performed on a variety of driving cycles before an actual driving test. There are a number of driving cycles that have been developed for the for performance evaluation of conventional vehicles. However, there is a lack of research into driving cycle for EV. Because large differences exist between the drive system and driving charateristics of EV and that of CV, a study on driving cycle for EV should be conducted. In this study, the necessity of an urban driving cycle for the performance evaluation of electric vehicles is confirmed by developing the driving cycle. First, the Gwacheon-city Urban Driving Cycle for Electric Vehicles (GUDC-EV) is developed by using driving data obtained through actual driving experiments and statistical analysis. Second, GUDC-EV is verified by constructing EV simulators and performing simulations that use the actual driving data. The simulation results are then compared against existing urban driving cycles, such as FTP-72, NEDC, and Japan 10–15. These results confirm that GUDC-EV can be used as an urban driving cycle to evaluate the performance of electric vehicles and validate the necessity of development of the driving cycle for electric vehicles.     

Tuning and objective performance evaluation of a driving simulator to investigate tyre behaviour in on-centre handling manoeuvres

Driving simulation aims at reproducing, within a safe and controlled environment, sensorial stimuli as close to those perceived during the actual drive as possible, in order to induce driving behaviour similar to the real one. This paper illustrates an activity carried out on the driving simulator Virtual Environment for Road Safety, bound for system performance optimisation while dealing with subjective and objective tyres evaluation in the field of on-centre manoeuvres. Such activity can be divided into two main steps. The first one, described herewith, has been focusing on platform motion algorithms tuning and has led to driving simulator objective validation within the on-centre range. Device capability of reproducing dynamics, worked out by the vehicle model, has been thoroughly examined. Simulator sensitivity to a few tyre parameters influencing vehicle lateral dynamics has been analysed too. The second step – calling for the support of experienced drivers – will pursue subjective validation.     

A Trajectory-Based Map-Matching System for the Driving Road Identification in Vehicle Navigation Systems

Driving road identification is the key issue of a vehicle navigation system that supports various services of intelligent transportation systems. The method for driving road identification is also known as map matching (MM). In spite of the development of MM algorithms, limitations still exist in obtaining the positioning data and preparing candidate roads (CRs) that may result in mismatches in some special difficult road configurations such as flyovers and parallel roads. To overcome the limitations, an integrated trajectory-based MM (tbMM) system is proposed based on the trajectory similarity evaluation method. The system can fuse the information from global positioning systems (GPS) and inertial sensors to generate the vehicle trajectory that represents the vehicle continuous movement in three dimensions. The elevation data of vehicle and roads are involved to enhance the trajectory-based matching process. Also the method employs an optimized mechanism for generating and maintaining CRs. Using the mechanism, separated road segments in a digital map are reorganized in the form of possible driving roads and the topology among them is guaranteed. Moreover, the CRs are obtained considering all the possibilities in determining the driving road so that the valuable historical information can be effectively reserved to provide more reliable matches in ambiguous situations. The tbMM system was evaluated using a number of real-world vehicle-level test datasets in urban areas in Beijing. Also a comparison test was performed to evaluate the driving road identification accuracy against existing MM algorithms. The results show that the tbMM system can provide reliable matches with about 99% accuracy in all the difficult scenarios and outperforms the existing algorithms.     

驾驶模拟器在自动驾驶系统中的应用研究

自动驾驶车辆在实际道路上行驶之前的测试阶段是一个至关重要的环节。一个低成本、高效率以及高精度测量的自动驾驶车辆的测试方式,对于自动驾驶车辆的开发具有重要意义。将驾驶模拟器运用到研究自动驾驶车辆测试已是近年来的一个研究热点。基于虚拟驾驶场景的自动驾驶车辆的检测,通过组合虚拟驾驶场景的背景车辆、行人、交通灯、建筑、指示标牌等元素,研究将驾驶模拟器与虚拟驾驶场景的联合应用来测试自动驾驶车辆。设计了典型的交通场景,通过自动驾驶车辆和背景车辆的实时交互,研究自动驾驶车辆的各项性能指标。研究结果表明:该驾驶模拟器可以高度拟合人类驾驶体验,驾驶员通过驾驶模拟器控制背景车辆能够很好的模拟现实中的驾驶行为,对自动驾驶车辆的仿真测试起到了促进作用。     

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.     

LED主动发光交通标志视认性能研究（双语出版）

为了给道路交通标志的设计与应用提供参考,针对LED点阵式发光标志、LED半透式发光标志和传统逆反射标志,考虑光照强度、闪烁频率、发光形式等因素的影响,进行了交通标志视认性能的驾驶试验研究。采用方差分析研究各个因素对标志视认距离影响的显著性及其交互作用。基于驾驶模拟器进行视认性能对比试验,采用配对样本t检验比较了半透式发光标志与逆反射标志的视认距离,并根据试验数据分析不同光照强度下半透式发光标志的最佳亮度区间。结果表明：在光照强度为200 lx的下午,LED主动发光标志相对于逆反射标志只增加了2~4 m的视认距离;而在光照强度为0.5 lx的晚间,视认效果则提升显著,点阵式和半透式发光标志的视认距离相比逆反射标志分别提升了39.7%和80.4%。闪烁发光无论快慢,对于LED主动发光标志的视认效果均无提升。另外,半透式发光标志的亮度过高时会产生眩光效应,不利于驾驶人辨识标志内容,且最佳亮度区间随着环境光照强度的变化而变化。因此,在光照条件较差的情况下,推荐采用常亮LED半透式发光标志。     

Vehicle dynamics testing in motion based driving simulators

ABSTRACT

This article investigates the potential of a motion-based driving simulator in the field of vehicle dynamics testing, specifically for heavy vehicles. For this purpose, a case study was prepared embodying the nature of a truck dynamics test setup. The goal was to investigate if the drivers in the simulator could identify the handling differences owed to changes in vehicle parameters, while driving the simulated trucks. Results show that the drivers could clearly identify the differences in vehicle behaviour for most of the performed tests, which motivates further investigative work in this area and exposes the feasibility of heavy vehicle dynamics testing in simulators.     

Vehicle sensor data-based analysis on the driving style differences between operating indoor simulator and on-road instrumented vehicle

Abstract

Indoor simulator and on-road instrumented vehicle are the most popular ways to analyze driving behaviors by using collected Vehicle Sensor Data (VSD). However, for a same driver, the driving performance could be different in the real world and in the simulated world. Even though many studies have been conducted to discover the differences of driving behaviors in these two circumstances, little research has focused on analyzing the differences in driving style, which can provide more integrated knowledge of a driver from the natural structure, stimulus–response mechanism, of driving behaviors. Therefore, in this paper, the driving styles in both the real world and the simulated world are extracted by implementing the nonnegative matrix factorization method on the collected VSD data. Through this analysis, the driving style differences can be quantitatively described and discussed in detail. It is found that the drivers tend to be more unstable and sometimes aggressive when driving the simulator and the deviation in the perception of temporal gap in two circumstances is also discovered. The research findings are particularly valuable to calibrate the driving simulator and construct more reliable driving behavior models.     

考虑道路平曲线设计的驾驶疲劳对车道保持能力影响研究

不同的道路平面线形几何设计对于驾驶人车道保持能力的需求是有差异的,驾驶人受疲劳程度影响也会呈现车道保持能力下降的趋势,当前的研究未综合考虑以上2个因素:线形和疲劳程度对驾驶横向表现的交互影响.邀请41位被试者分别开展550 km的实车实验,获取车辆位置信息GPS以匹配道路线形类型,基于问卷调查方法获取驾驶过程疲劳等级.分析不同疲劳程度、不同平面线形类型以及弯道半径条件下的车道偏离标准差参数,构建了多元线性回归模型.数据分析结果表明,相同疲劳程度下驾驶人在圆曲线段驾驶的偏离值要超过直线段以及缓和曲线段;当弯道半径超过5 500 m时,曲线段弯道半径越大,车道偏离差值越高.同时,考虑了线形影响的多元线性回归模型对疲劳程度的预测精度要高于未考虑线形因素的模型,进一步说明在针对驾驶疲劳行为表现开展研究时,有必要对道路设计参数加以考虑以提高疲劳辨识精度.      

Study on behavior of cab-over truck driver looking at a display while driving

This paper discusses how a cab-over truck driver looks at information shown in a display while driving, to give information to the driver safely and securely. The authors investigated a driver's behavior in changing focus to an information display while driving an actual truck and a driving simulator. Relation between distribution of attention and individual lengths of time to change focus to the display was examined. Average diversion time away from road was found to be approximately 1.7 s, longer than that for passenger cars under similar traffic conditions. Driving skills do not have any influence on individual lengths of time.     

主被动式网络化汽车驾驶模拟器的研究及应用

本文介绍主、被动式网络化的汽车驾驶模拟器。该模拟器除采用了先进的计算机虚拟现实技术和汽车动力学模型外，还具有模拟器间的网络交互、主被动驾驶模式、运动约束、语音提示、驾驶评价等方面的特点，在应用上具有显著的特色。     

智能网联汽车人机交互场景测评方法研究

汽车座舱内的人机交互智能系统一定程度决定了用户的智能体验,对人机交互进行测试研究,形成一套完整的人机交互测试评价方法,可以指导人机交互的设计开发,实现人机交互的迭代和优化。汽车座舱内功能日益增加,给用户带来更丰富的体验,然而功能相同,人机交互不同,给用户带来的驾驶体验却大相径庭。基于典型使用场景,从客观角度,分析不同车型相同场景下车机系统的响应、驾驶员眼部活动和驾驶员手部活动的差异,进一步量化评价参数,形成评价指标,同时根据五感和五觉,设计主观评价表对人机交互进行测评。测评结果表明,该方法具备可操作性和合理性,能从客观和主观角度全面评估人机交互的优劣。     

Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.     

Human driving data-based design of a vehicle adaptive cruise control algorithm

This paper presents a vehicle adaptive cruise control algorithm design with human factors considerations. Adaptive cruise control (ACC) systems should be acceptable to drivers. In order to be acceptable to drivers, the ACC systems need to be designed based on the analysis of human driver driving behaviour. Manual driving characteristics are investigated using real-world driving test data. The goal of the control algorithm is to achieve naturalistic behaviour of the controlled vehicle that would feel natural to the human driver in normal driving situations and to achieve safe vehicle behaviour in severe braking situations in which large decelerations are necessary. A non-dimensional warning index and inverse time-to-collision are used to evaluate driving situations. A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC system. Using a simulation and a validated vehicle simulator, vehicle following characteristics of the controlled vehicle are compared with real-world manual driving radar sensor data. It is shown that the proposed control strategy can provide with natural following performance similar to human manual driving in both high speed driving and low speed stop-and-go situations and can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.     

山区公路爬坡车道的交通特性及驾驶安全性模拟评价

以山区公路上设置的某一爬坡车道为试验对象,利用驾驶模拟试验对其交通特性及驾驶安全性进行仿真。根据设计图和现场环境构建了三维虚拟试验场景,通过VISSIM生成试验路段交通流;32名受试者在4种交通条件下进行了驾驶模拟试验;模拟过程中记录车辆的速度、轨迹、加速度、制动力等数据;通过VISSIM仿真试验确定了该爬坡车道的交通量阈值。分析结果表明,在常规交通流情况下,该爬坡车道可提高主路上的车速及其平稳性,同时可减少来自对向车道的冲突;但随着交通流量趋于饱和,其有效性逐渐减弱甚至产生负面影响。     

Dynamic stability of forklift trucks in cornering situations: parametrical analysis using a driving simulator

This paper describes the examination of the vehicle dynamics and stability of four-wheeled forklift trucks (FLTs) in cornering situations. Cornering at excessive speed is one major reason for fatal accidents with forklifts caused by lateral tipover. In order to increase the lateral stability of this kind of working machinery, the influence of certain important design properties has been studied using an appropriate vehicle simulation model and a driving simulator. The simulation model is based on a multi-body system approach and includes submodels for the propulsion system and the tyres. The driving behaviour of the operator has not been modelled. Instead, a driving simulator has been built up and a real human driver was employed for ensuring adequate and realistic model input. As there have not been any suitable standardised test manoeuvres available for FLTs, a new driving test has been developed to assess the lateral stability. This test resembles the well-known J turn/Fishhook turn, but includes a more dynamic counter-steering action. Furthermore, the dimensions of the test track are defined. Therefore, the test is better adapted to the driving dynamics of forklifts and reflects the real driver behaviour more closely. Finally, a parametrical study has been performed, examining the influence of certain important technical properties of the truck such as the maximum speed, the position of centre of gravity, rear axle design features and tyre properties. The results of this study may lead to a better understanding of the vehicle dynamics of forklifts and facilitate goal-oriented design improvements.