在分布式交通仿真系统中,存在着众多的模拟驾驶器和教练机,而模拟中又有驾驶训练、驾驶考试、交规训练、交规模拟考试等4个大的功能.如何实现有效的网络环境下的集中管理,是系统成功开发的关键.针对分布式交通仿真系统开发中出现的网络...在分布式交通仿真系统中,存在着众多的模拟驾驶器和教练机,而模拟中又有驾驶训练、驾驶考试、交规训练、交规模拟考试等4个大的功能.如何实现有效的网络环境下的集中管理,是系统成功开发的关键.针对分布式交通仿真系统开发中出现的网络控制问题,将A gen t技术成功地应用到该系统的开发平台中.在充分地分析了各模拟驾驶器、教练机的运作特性后,建立了以教练机为主体、各模拟驾驶器为A gen t的网络通信模型.实现了教练机对各模拟驾驶器的流畅管理,为该系统的成功开发提供了有力的保障.展开更多
Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality te...Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality technology is now a promising alternative to the conventional driving simulations since it provides a more simple, secure and user-friendly environment for data collection. The driving simulator was used to assist novice drivers in learning how to drive in a very calm environment since the driving is not taking place on an actual road. This paper provides new insights regarding a driver’s behavior, techniques and adaptability within a driving simulation using virtual reality technology. The theoretical framework of this driving simulation has been designed using the Unity3D game engine (5.4.0f3 version) and programmed by the C# programming language. To make the driving simulation environment more realistic, the HTC Vive Virtual reality headset, powered by Steamvr, was used. 10 volunteers ranging from ages 19 - 37 participated in the virtual reality driving experiment. Matlab R2016b was used to analyze the data obtained from experiment. This research results are crucial for training drivers and obtaining insight on a driver’s behavior and characteristics. We have gathered diverse results for 10 drivers with different characteristics to be discussed in this study. Driving simulations are not easy to use for some users due to motion sickness, difficulties in adopting to a virtual environment. Furthermore, results of this study clearly show the performance of drivers is closely associated with individual’s behavior and adaptability to the driving simulator. Based on our findings, it can be said that with a VR-HMD (Virtual Reality-Head Mounted Display) Driving Simulator enables us to evaluate a driver’s “performance error”, “recognition errors” and “decision error”. All of which will allow researchers and further studies to potentially establish a method to increase driver safety or all展开更多
A variety of word messages are used in highways in different forms to inform drivers of traffic safety information or to influence positively drivers＇ behavior. These include direct word messages for a particular eve...A variety of word messages are used in highways in different forms to inform drivers of traffic safety information or to influence positively drivers＇ behavior. These include direct word messages for a particular event （such as road work） or general safety messages that warn drivers of risky driving behaviors （such as distracted driving and speeding）. However, it is often observed that many drivers even do not recognize the safety messages despite being displayed on roadside signs in a fairly good visibility condition. The present study focused on an engineering method, namely auditory warning sound （AWS）, which calls driver＇s attention on driving tasks and helps them comply with roadside safety signs. A driving simulator experiment was conducted to assess effects of AWS on driver compliance to roadside safety signs. AWS was implemented into driving simulator scenarios as a parameter to generate a certain level of growling warning sounds when subject vehicles are entering within a legi- bility distance of a roadside safety sign. The present study described laboratory setup and data for the driving simulator experiment, and drew conclusions on driver compliance to roadside safety signs with and without presence of AWS. The experiment results show that drivers are more compliant to roadside safety signs when AWS is used. It is expected that AWS will greatly help drivers comply with roadside safety signs where a specific safety concern is raised, such as a work-zone or a drowsy driving advisory zone.展开更多
Purpose–This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles(AVs)compared to driving among manually driven vehicles(MVs).Understanding behavioral adaptation o...Purpose–This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles(AVs)compared to driving among manually driven vehicles(MVs).Understanding behavioral adaptation of drivers when they encounter AVs is crucial for assessing impacts of AVs in mixed-traffic situations.Here,mixed-traffic situations refer to situations where AVs share the roads with existing nonautomated vehicles such as conventional MVs.Design/methodology/approach–A driving simulator study is designed to explore whether such behavioral adaptations exist.Two different driving scenarios were explored on a three-lane highway:driving on the main highway and merging from an on-ramp.For this study,18 research participants were recruited.Findings–Behavioral adaptation can be observed in terms of car-following speed,car-following time gap,number of lane change and overall driving speed.The adaptations are dependent on the driving scenario and whether the surrounding traffic was AVs or MVs.Although significant differences in behavior were found in more than 90%of the research participants,they adapted their behavior differently,and thus,magnitude of the behavioral adaptation remains unclear.Originality/value–The observed behavioral adaptations in this paper were dependent on the driving scenario rather than the time gap between surrounding vehicles.This finding differs from previous studies,which have shown that drivers tend to adapt their behaviors with respect to the surrounding vehicles.Furthermore,the surrounding vehicles in this study are more“free flow’”compared to previous studies with a fixed formation such as platoons.Nevertheless,long-term observations are required to further support this claim.展开更多
文摘在分布式交通仿真系统中,存在着众多的模拟驾驶器和教练机,而模拟中又有驾驶训练、驾驶考试、交规训练、交规模拟考试等4个大的功能.如何实现有效的网络环境下的集中管理,是系统成功开发的关键.针对分布式交通仿真系统开发中出现的网络控制问题,将A gen t技术成功地应用到该系统的开发平台中.在充分地分析了各模拟驾驶器、教练机的运作特性后,建立了以教练机为主体、各模拟驾驶器为A gen t的网络通信模型.实现了教练机对各模拟驾驶器的流畅管理,为该系统的成功开发提供了有力的保障.
文摘Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality technology is now a promising alternative to the conventional driving simulations since it provides a more simple, secure and user-friendly environment for data collection. The driving simulator was used to assist novice drivers in learning how to drive in a very calm environment since the driving is not taking place on an actual road. This paper provides new insights regarding a driver’s behavior, techniques and adaptability within a driving simulation using virtual reality technology. The theoretical framework of this driving simulation has been designed using the Unity3D game engine (5.4.0f3 version) and programmed by the C# programming language. To make the driving simulation environment more realistic, the HTC Vive Virtual reality headset, powered by Steamvr, was used. 10 volunteers ranging from ages 19 - 37 participated in the virtual reality driving experiment. Matlab R2016b was used to analyze the data obtained from experiment. This research results are crucial for training drivers and obtaining insight on a driver’s behavior and characteristics. We have gathered diverse results for 10 drivers with different characteristics to be discussed in this study. Driving simulations are not easy to use for some users due to motion sickness, difficulties in adopting to a virtual environment. Furthermore, results of this study clearly show the performance of drivers is closely associated with individual’s behavior and adaptability to the driving simulator. Based on our findings, it can be said that with a VR-HMD (Virtual Reality-Head Mounted Display) Driving Simulator enables us to evaluate a driver’s “performance error”, “recognition errors” and “decision error”. All of which will allow researchers and further studies to potentially establish a method to increase driver safety or all
基金funded by Alabama Department of Transportation (Research Project 930-856R)was carried out at the University of South Alabama
文摘A variety of word messages are used in highways in different forms to inform drivers of traffic safety information or to influence positively drivers＇ behavior. These include direct word messages for a particular event （such as road work） or general safety messages that warn drivers of risky driving behaviors （such as distracted driving and speeding）. However, it is often observed that many drivers even do not recognize the safety messages despite being displayed on roadside signs in a fairly good visibility condition. The present study focused on an engineering method, namely auditory warning sound （AWS）, which calls driver＇s attention on driving tasks and helps them comply with roadside safety signs. A driving simulator experiment was conducted to assess effects of AWS on driver compliance to roadside safety signs. AWS was implemented into driving simulator scenarios as a parameter to generate a certain level of growling warning sounds when subject vehicles are entering within a legi- bility distance of a roadside safety sign. The present study described laboratory setup and data for the driving simulator experiment, and drew conclusions on driver compliance to roadside safety signs with and without presence of AWS. The experiment results show that drivers are more compliant to roadside safety signs when AWS is used. It is expected that AWS will greatly help drivers comply with roadside safety signs where a specific safety concern is raised, such as a work-zone or a drowsy driving advisory zone.
基金the Swedish Governmental Agency for Innovation Systems(Vinnovagrant no.2018-02891).
文摘Purpose–This paper aims to explore whether drivers would adapt their behavior when they drive among automated vehicles(AVs)compared to driving among manually driven vehicles(MVs).Understanding behavioral adaptation of drivers when they encounter AVs is crucial for assessing impacts of AVs in mixed-traffic situations.Here,mixed-traffic situations refer to situations where AVs share the roads with existing nonautomated vehicles such as conventional MVs.Design/methodology/approach–A driving simulator study is designed to explore whether such behavioral adaptations exist.Two different driving scenarios were explored on a three-lane highway:driving on the main highway and merging from an on-ramp.For this study,18 research participants were recruited.Findings–Behavioral adaptation can be observed in terms of car-following speed,car-following time gap,number of lane change and overall driving speed.The adaptations are dependent on the driving scenario and whether the surrounding traffic was AVs or MVs.Although significant differences in behavior were found in more than 90%of the research participants,they adapted their behavior differently,and thus,magnitude of the behavioral adaptation remains unclear.Originality/value–The observed behavioral adaptations in this paper were dependent on the driving scenario rather than the time gap between surrounding vehicles.This finding differs from previous studies,which have shown that drivers tend to adapt their behaviors with respect to the surrounding vehicles.Furthermore,the surrounding vehicles in this study are more“free flow’”compared to previous studies with a fixed formation such as platoons.Nevertheless,long-term observations are required to further support this claim.
