Policy challenges of increasing automation in driving

The convergence of information and communication technologies (ICT) with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010), future developments in the medium term (level II 2010–2025) are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025 +) scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.     

Handling Cut-In Vehicles in Strings of Cooperative Adaptive Cruise Control Vehicles

Cooperative adaptive cruise control (CACC) systems are a candidate to improve highway capacity by shortening headways and attenuating traffic disturbances. Although encouraging results have been obtained until now, a wide range of traffic circumstances has to be investigated in order to get reliable CACC systems driving on real roads. Among them, handling both vehicle-to-vehicle (V2V) communications-equipped and unequipped vehicles merging into the string of CACC vehicles is a commonly mentioned challenge. In this article, an algorithm for managing the transitions in response to cut-ins from V2V- or non-V2V-equipped vehicles is developed and tested using a string of four CACC vehicles. A CACC controller is implemented in four production Infiniti M56s vehicles and tested in real traffic, where non-V2V-equipped vehicles can cut in. The effects of a vehicle performing a cut-out are also investigated. Then responses to cut-ins by equipped and nonequipped vehicles are simulated for longer strings of vehicles using car-following models for both the production adaptive cruise control (ACC) system and the newly developed CACC controller. Results demonstrate that the CACC system is able to handle cut-in vehicles without causing major perturbations, while also reducing significantly the impact of this maneuver on the following vehicles, improving traffic flow.     

工程车辆智能换挡规律的仿真

以装载机为研究对象,分析了工程车辆自动变速系统的结构及原理,建立了工程车辆电控自动变速系统组成原理图。针对工程车辆的作业特点,以适应性和在线实时性等综合性能最优为控制目标,确定了工程车辆智能换挡规律控制原则。基于仿人智能模糊控制方法,对换挡规律进行了分析研究,建立了装载机动力传动系统动态仿真模型,并应用Matlab/Simulink软件进行了仿真分析。仿真结果表明,将仿人智能模糊控制方法应用于工程车辆智能变速系统具有可行性。     

汽车驾驶人姿态监测系统研究综述（双语出版）

随着自动驾驶技术的发展,驾驶人将会参与更多的与驾驶无关的活动,从而呈现出新的姿态,这些新姿态是优化传统被动安全系统的重要切入点。而且在未来相当长的时间内,自动驾驶车辆的行驶依然依赖于人和系统的密切配合。对驾驶人姿态的观察,则可以为判断驾驶人是否有能力及时接管车辆提供帮助,从而确保安全、合理的人机交互过程。通过对大量相关文献的系统性梳理,综述了汽车驾驶人姿态监测技术的智能化发展趋势,从传感器种类以及相应的姿态监测算法出发,分析了目前不同监测系统的优缺点。研究发现,尽管传感器技术和姿态识别算法取得了明显进步,然而廉价稳定且能够在实际驾驶条件下对驾驶人姿态准确感知的监测系统依然缺乏。总体而言,目前的监测系统大多只是集中于对驾驶人局部身体部位的感知,缺乏实际驾驶条件下的性能分析,并且对驾驶人状态的实时感知和预测能力仍有待完善。最后,针对目前监测系统所面临的问题,对未来可能的研究方向进行展望,并提出主动式立体视觉系统和压力传感器阵列相融合的驾驶人姿态监测方式。研究成果将为驾驶人姿态监测系统的研究提供参考和借鉴,从而有助于道路交通安全水平的进一步提升,同时也可为人机交互界面的设计带来启发。     

New insights from fractional order skyhook damping control for railway vehicles

Active suspensions for railway vehicles have been a topic of research for a number of decades and while their applications in service operation are limited, it seems clear that they will in due course see widespread adoption. Railway suspension design is a problem of compromise on the non-trivial trade-off of ride quality versus track following (guidance), and the skyhook damping control approach has been paramount in illustrating the potential benefits. Since skyhook damping control, various advanced control studies appeared contributing to redefine the boundaries of the aforementioned trade-off. Yet there is no study on the impact of fractional order (FO) methods in the context of skyhook railway active suspensions and in particular related to skyhook damping control. This is the area to which this paper strongly contributes. We present findings from a current project on FO controllers for railway vehicles active suspensions, in particular work on the effect of FO methods in basic skyhook damping control schemes, i.e. pure and intuitively based skyhook. First, we present a brief review of conventional skyhook damping control and then proceed to a rigorous investigation of the impact of FO on the ride quality/track following trade-off. The relevant benefits from FO methods are appraised and new insights highlighted.     

Semi-active suspension systems for railway vehicles using magnetorheological dampers. Part II: simulation and analysis

In this paper, the semi-active suspension system for railway vehicles based on the controlled (MR) fluid dampers is investigated, and compared with the passive on and passive off suspension systems. The lateral, yaw, and roll accelerations of the car body, trucks, and wheelsets of a full-scale railway vehicle integrated with four MR dampers in the secondary suspension systems, which are in the closed and open loops respectively, are simulated under the random and periodical track irregularities using the established governing equations of the railway vehicle and the modelled track irregularities in Part I of this paper. The simulation results indicate that (1) the semi-active controlled MR damper-based suspension system for railway vehicles is effective and beneficial as compared with the passive on and passive off modes, and (2) while the car body accelerations of the railway vehicle integrated with semi-active controlled MR dampers can be significantly reduced relative to the passive on and passive off ones, the accelerations of the trucks and wheelsets could be increased to some extent. However, the increase in the accelerations of the trucks and wheelsets is insignificant.     

Assessing the Potential Impacts of Connected Vehicles: Mobility,Environmental, and Safety Perspectives

The connected vehicle is a rapidly emerging paradigm aimed at deploying and developing a fully connected transportation system that enables data exchange among vehicles, infrastructure, and mobile devices to improve mobility, enhance safety, and reduce the adverse environmental impacts of the transportation systems. This study focuses on micromodeling and quantitatively assessing the potential impacts of the connected vehicle (CV) on mobility, safety, and the environment. To assess the benefits of CVs, a modeling framework is developed based on traffic microsimulation for a real network located in the city of Toronto, Canada, to mimic communication between enabled vehicles. In this study, we examine the effects of providing real-time routing guidance and advisory warning messages to CVs. In addition, to take into account the rerouting in nonconnected vehicles (non-CVs) in response to varying sources of information such as apps, global positioning systems (GPS), variable message signs (VMS), or simply seeing the traffic back up, the impact of fraction of non-CV vehicles was also considered and evaluated. Therefore, vehicles in this model are divided into; uninformed/unfamiliar not connected (non-CV), informed/familiar but not connected (non-CV) that get updates infrequently every 5 minutes or so (non-CV), and connected vehicles that receive information more frequently (CV). The results demonstrate the potential of connected vehicles to improve mobility, enhance safety, and reduce greenhouse gas emissions (GHGs) at the network-wide level. The results also show quantitatively how the market penetration of connected vehicles proportionally affects the performance of the traffic network. While the presented results are pertinent to the specifics of the road network modeled and cannot be generalized, the quantitative figures provide researchers and practitioners with ideas of what to expect from vehicle connectivity concerning mobility, safety, and environmental improvements.     

基于TD3算法的人机混驾交通环境自动驾驶汽车换道研究

提高人类驾驶人的接受度是自动驾驶汽车未来的重要方向,而深度强化学习是其发展的一项关键技术。为了解决人机混驾混合交通流下的换道决策问题,利用深度强化学习算法TD3（Twin Delayed Deep Deterministic Policy Gradient）实现自动驾驶汽车的自主换道行为。首先介绍基于马尔科夫决策过程的强化学习的理论框架,其次基于来自真实工况的NGSIM数据集中的驾驶数据,通过自动驾驶模拟器NGSIM-ENV搭建单向6车道、交通拥挤程度适中的仿真场景,非自动驾驶车辆按照数据集中驾驶人行车数据行驶。针对连续动作空间下的自动驾驶换道决策,采用改进的深度强化学习算法TD3构建换道模型控制自动驾驶汽车的换道驾驶行为。在所提出的TD3换道模型中,构建决策所需周围环境及自车信息的状态空间、包含受控汽车加速度和航向角的动作空间,同时综合考虑安全性、行车效率和舒适性等因素设计强化学习的奖励函数。最终在NGSIM-ENV仿真平台上,将基于TD3算法控制的自动驾驶汽车换道行为与人类驾驶人行车数据进行比较。研究结果表明：基于TD3算法控制的车辆其平均行驶速度比人类驾驶人的平均行车速度高4.8%,在安全性以及舒适性上也有一定的提升;试验结果验证了训练完成后TD3换道模型的有效性,其能够在复杂交通环境下自主实现安全、舒适、流畅的换道行为。     

New approach for performing failure analysis of fuel cell-powered vehicles

Safety of hybrid-electric and fuel cell vehicles is a critical aspect of these new technologies, since any accident exposing occupants of such vehicles to unconventional hazards may result in significant setbacks to successful market penetration. Fuel cell and hybrid-electric drive systems are complex, and it is essential to perform a thorough analysis to determine critical failure conditions. There are several safety concerns for routine operation of such systems, particularly for hydrogen-fueled vehicles. A modified Failure Modes and Effect Analysis (FMEA) has been developed, along with a Criticality Analysis (CrA), to identify potentially hazardous conditions for crash and non-crash situations. A mathematical model of fuel cell operation has been developed and used here in conjunction with the FMEA. Component failures during the event modes are simulated using vehicle models developed with Matlab Simulink tools. Six simulation models were created using the software. In addition, a preliminary finite element model of a fuel cell vehicle, using a Ford Taurus (91′) model year sedan, has been developed and implemented. This finite element model is used as a demonstration of the crash simulation of the vehicle.     

Traffic Simulation with Consideration of Driver Models,Theory and Examples

SUMMARY

In the last five years the IKA (Institut für Kraftfahrwesen Aachen) and BMW created the microscopic traffic simulation program PELOPS. It simulates the traffic flow on motorways with a specific view on vehicle affairs. One application for PELOPS was the assessment of ACC (Adaptive Cruise Control) systems inside the PROMETHEUS program. It was shown, that PELOPS is a powerful tool for the analysis of new technologies. A new research period will extend the use of ACC about the functionality in urban areas. This requires an extension of PELOPS about some specific models. With this extension it is possible, to analyse new traffic technologies for the individual vehicles or the infrastructure. In a first step, PELOPS is extended about functions for suburban areas. This effects mainly the modelling of the driver behaviour. The driver behaviour is related to the traffic situation. In contrast to the normal traffic flow on motorways, the driver has to stop and go in the suburban area, he has to control lower distances and he has to react on other vehicles on cross-roads. New concepts for these functions are included in PELOPS and calibrated by detailed traffic data from a video observation and floating car measurements in the surrounding of Aachen. Based on the traffic measurement near Aachen, different scenarios are simulated to improve the traffic flow and to relieve the environment. These scenarios include ACC systems, inter-vehicle-communication and intelligent traffic lights. The paper shows some information's about the simulation technic and the results from the described analysis.     

Haptic interface for intuitive teleoperation of wheeled and tracked vehicles

In this paper, a novel haptic interface is proposed for general teleoperation of wheeled and tracked vehicles. The new mechanism of the proposed haptic interface, shown in Figure 1, not only allows human operators to easily teleoperate various types of target vehicles, including car-like vehicles, mobile robots, and tracked vehicles, but also improves the operator??s perception of the target vehicle??s operating status and its environment by introducing a ??cornering feel?? to the field of vehicle teleoperation. In addition, the proposed interface enables human operators to give commands to (or drive) the target vehicle in a way that is traditionally carried out by direct control or driving. Experiments were completed to carefully evaluate and test the performance of the proposed interface. The results show that the developed haptic master device is sufficient and suitable for general wheeled and tracked-vehicle teleoperation.     

人机混驾环境下无信号交叉口自动驾驶汽车左转运动规划研究

为了使自动驾驶汽车在人机混驾环境下能安全、高效地左转通过无信号交叉口,在借鉴人类驾驶人左转时会对周围车辆驾驶意图进行提前预判的基础上,提出了一种基于周围车辆驾驶意图预测的自动驾驶汽车左转运动规划模型。首先将无信号交叉口处周围车辆的驾驶意图分为左转、右转、直行3种类型,利用相关向量机预测周围车辆驾驶意图,以概率形式输出意图预测结果并实时更新,进一步界定自动驾驶汽车与周围车辆的潜在冲突区域并判断是否存在时空冲突;接着,在充分考虑他车速度、航向及车辆到达冲突区域边界距离的基础上建立基于部分可观测马尔可夫决策过程的自动驾驶汽车左转运动规划模型,生成一系列期望加速度;最后,基于Prescan-Simulink联合仿真平台搭建无信号交叉口仿真场景,对所提左转运动规划方法进行仿真验证,将基于博弈论的运动规划方法、基于人工势场理论的运动规划方法与所提出的方法进行比较,并选取行进比例达到1所用的时间和碰撞次数作为评价指标。研究结果表明：基于相关向量机的驾驶意图预测方法可在自动驾驶汽车到达交叉口之前准确预测出他车驾驶意图;基于部分可观测马尔可夫决策过程的左转运动规划方法能够通过速度调整策略实现人机混驾环境下自动驾驶汽车与周围车辆在无信号交叉口处的交互;不同算法对比效果表明,所提左转运动规划方法在自动驾驶汽车与不同数量周围车辆交互的仿真场景下均可有效避免碰撞事故发生并提高自动驾驶汽车左转通过无信号交叉口的效率。     

An adaptive lateral preview driver model

Successful modelling and simulation of driver behaviour is important for the current industrial thrust of computer-based vehicle development. The main contribution of this paper is the development of an adaptive lateral preview human driver model. This driver model template has a few parameters that can be adjusted to simulate steering actions of human drivers with different driving styles. In other words, this model template can be used in the design process of vehicles and active safety systems to assess their performance under average drivers as well as atypical drivers. We assume that the drivers, regardless of their style, have driven the vehicle long enough to establish an accurate internal model of the vehicle. The proposed driver model is developed using the adaptive predictive control (APC) framework. Three key features are included in the APC framework: use of preview information, internal model identification and weight adjustment to simulate different driving styles. The driver uses predicted vehicle information in a future window to determine the optimal steering action. A tunable parameter is defined to assign relative importance of lateral displacement and yaw error in the cost function to be optimized. The model is tuned to fit three representative drivers obtained from driving simulator data taken from 22 human drivers.     

Investigation of active torsion bar actuator configurations to reduce vehicle body roll

The increasing popularity of sport utility/light-duty vehicles has prompted the investigation of active roll management systems to reduce vehicle body roll. To minimize vehicle body roll and improve passenger comfort, one emerging solution is an active torsion bar control system. The validation of automotive safety systems requires analytical evaluation and laboratory testing prior to implementation on an actual vehicle. In this article, a computer simulation tool and accompanying hardware-in-the-loop test environment are presented for active torsion bar systems to study component configurations and performance limits. The numerical simulation illustrates that the hydraulic cylinder extension limits the active torsion system's ability to provide body roll angle reduction under various driving conditions. To compare the control system's time constant and body roll minimization capabilities for different hydraulic valve assemblies and equivalent hose lengths, an experimental test stand was created. For a typical hydraulic pressure and hose diameter, the equivalent hose length was not a key design variable that impacted the system response time. However, the servo-valve offered a quicker transient response and smoother steady-state behavior than the solenoid poppet actuators that may increase occupant safety and comfort.     

Investigation of active torsion bar actuator configurations to reduce vehicle body roll

The increasing popularity of sport utility/light-duty vehicles has prompted the investigation of active roll management systems to reduce vehicle body roll. To minimize vehicle body roll and improve passenger comfort, one emerging solution is an active torsion bar control system. The validation of automotive safety systems requires analytical evaluation and laboratory testing prior to implementation on an actual vehicle. In this article, a computer simulation tool and accompanying hardware-in-the-loop test environment are presented for active torsion bar systems to study component configurations and performance limits. The numerical simulation illustrates that the hydraulic cylinder extension limits the active torsion system’s ability to provide body roll angle reduction under various driving conditions. To compare the control system’s time constant and body roll minimization capabilities for different hydraulic valve assemblies and equivalent hose lengths, an experimental test stand was created. For a typical hydraulic pressure and hose diameter, the equivalent hose length was not a key design variable that impacted the system response time. However, the servo-valve offered a quicker transient response and smoother steady-state behavior than the solenoid poppet actuators that may increase occupant safety and comfort.     

Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control system that connects a traffic controller with in-vehicle controllers via vehicle-to-infrastructure communication. The link-level traffic controller regulates traffic speeds through variable speed limits (VSL) gantries to resolve stop-and-go waves, while intelligent vehicles control accelerations through vehicle propulsion and brake systems to optimize their local situations. It is assumed that each intelligent vehicle receives VSL commands from the traffic controller and uses them as variable parameters for the local vehicle controller. Feasibility and effectiveness of the connected control paradigm are tested with simulation on a two-lane freeway stretch with intelligent vehicles randomly distributed among human-driven vehicles. Simulation shows that the connected VSL and vehicle control system improves traffic efficiency and sustainability; that is, total time spent in the network and average fuel consumption rate are reduced compared to (uncontrolled and controlled) scenarios with 100% human drivers and to uncontrolled scenarios with the same intelligent vehicle penetration rates.     

Semi-active Damping with an Electromagnetic Force Generator

The main shortcoming of vehicle suspension systems is the amplification of input vibrations at the resonant frequency. A non-amplifying suspension system with a semi-active damping is being developed. The use of an electronically controlled rotational damper has been studied theoretically. A new sprung seat is being designed for the improvement of the working conditions for drivers of road and terrain vehicles.     

Development of an errorable car-following driver model

An errorable car-following driver model is presented in this paper. An errorable driver model is one that emulates human driver’s functions and can generate both nominal (error-free), as well as devious (with error) behaviours. This model was developed for evaluation and design of active safety systems. The car-following data used for developing and validating the model were obtained from a large-scale naturalistic driving database. The stochastic car-following behaviour was first analysed and modelled as a random process. Three error-inducing behaviours were then introduced. First, human perceptual limitation was studied and implemented. Distraction due to non-driving tasks was then identified based on the statistical analysis of the driving data. Finally, time delay of human drivers was estimated through a recursive least-square identification process. By including these three error-inducing behaviours, rear-end collisions with the lead vehicle could occur. The simulated crash rate was found to be similar but somewhat higher than that reported in traffic statistics.     

智能网联环境下的混合交通流LWR模型

LWR（Lighthill,Whitham and Richards,LWR）模型可推演交通流宏观状态演化过程,在智能网联环境下混有协同自适应巡航控制（Cooperative Adaptive Cruise Control,CACC）车辆混合交通流LWR模型的研究,可为该混合交通流的宏观动力学特性分析提供理论工具。应用加州伯克利PATH真车试验验证的CACC模型作为CACC车辆跟驰模型,采用智能驾驶人模型（Intelligent Driver Model,IDM）模拟驾驶人在智能网联环境中的"智能"驾驶特性。基于不同CACC车辆比例下的混合交通流基本图,证明混合交通流基本图的切线斜率为交通波在混合车队中传播的波速,建立混合交通流LWR模型的一般性解析框架,得到混有CACC车辆的混合交通流LWR模型。最后,针对LWR模型冲击波特性,在6组平衡态条件下进行数值仿真试验。研究结果表明：所建立的混合交通流LWR模型可较好地描述不同CACC车辆比例时冲击波在混合车队中的传播波速;冲击波波速理论值与仿真均值的相对误差基本控制在10%以内,当冲击波处于由正向波转变为反向波的过渡阶段时,相对误差较大,为19%~26%,但绝对误差仍然较小。研究结果一方面可为混有CACC车辆的交通流宏观状态演化提供理论参考,具有推动该混合交通流其他宏观模型研究进展的积极作用;另一方面,建立的混合交通流LWR模型解析框架能够适应CACC车辆与人工-网联车辆跟驰模型选取的多样性,同时可为其他类型混合交通流LWR模型的建立提供理论支撑。     

Development of a fail-safe control strategy based on evaluation scenarios for an FCEV electronic brake system

This study presents a few fail-safe control strategies based on reliability evaluation scenarios for the electronic brake systems of green cars in several critical cases. CarSim and MATLAB Simulink were used to develop the FCEV model with regenerative braking involving EWBs and EMBs. The proposed reliability evaluation scenarios were simulated, and a few fail-safe control algorithms were verified using the proposed reliability evaluation scenarios with the developed FCEV simulation model. The reliability evaluation scenarios were developed using a combination of driving modes and FMEA results for these electronic brake systems.