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Future connected vehicles:Communications demands,privacy and cyber-security 认领 引用 被引量：16
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作者 Tomas Olovsson Tommy Svensson Jiaming Wu 《Communications in Transportation Research》 2022年第1期39-41,共3页
1.Introduction With the advance of data collection,data processing,telecommunication and vehicular technologies,connected vehicles(CVs)have been emerging as a crucial branch of smart mobility(Olia et al.,2015;Li et al... 1.Introduction With the advance of data collection,data processing,telecommunication and vehicular technologies,connected vehicles(CVs)have been emerging as a crucial branch of smart mobility(Olia et al.,2015;Li et al.,2021).Its basic idea is to realize real-time exchanges and processing of essential information,such as positions and destinations,among surrounding vehicles and infrastructures. 展开更多
关键词 connected branch destination
Potential impact of autonomous vehicles in mixed traffic from simulation using real traffic flow 认领 引用 被引量：6
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作者 Eleonora Andreotti Selpi Pinar Boyraz 《Journal of Intelligent and Connected Vehicles》 2023年第1期1-15,共15页
This work focuses on the potential impacts of the autonomous vehicles in a mixed traffic condition represented in traffic simulator Simulation of Urban MObility(SUMO)with real traffic flow.Specifically,real traffic fl... This work focuses on the potential impacts of the autonomous vehicles in a mixed traffic condition represented in traffic simulator Simulation of Urban MObility(SUMO)with real traffic flow.Specifically,real traffic flow and speed data collected in 2002 and 2019 in Gothenburg were used to simulate daily flow variation in SUMO.In order to predict the most likely drawbacks during the transition from a traffic consisting only manually driven vehicles to a traffic consisting only fully-autonomous vehicles,this study focuses on mixed traffic with different percentages of autonomous and manually driven vehicles.To realize this aim,several parameters of the car following and lane change models of autonomous vehicles are investigated in this paper.Along with the fundamental diagram,the number of lane changes and the number of conflicts are analyzed and studied as measures for improving road safety and efficiency.The study highlights that the autonomous vehicles’features that improve safety and efficiency in 100%autonomous and mixed traffic are different,and the ability of autonomous vehicles to switch between mixed and autonomous driving styles,and vice versa depending on the scenario,is necessary. 展开更多
关键词 automated driving autonomous vehicles(AVs) mixed-traffic traffic simulations driving style realistic conditions
Behavioral adaptation of drivers when driving among automated vehicles 认领 引用 被引量：4
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作者 Maytheewat Aramrattana Jiali Fu 《Journal of Intelligent and Connected Vehicles》 2022年第3期309-315,共7页
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
关键词 Automated vehicles Driver behaviors and assistance Human-robot interaction Behavioral adaptation Driving simulator experiment
Special Issue on HMI and Autonomous Driving 认领 引用
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作者 Fang Chen 《Automotive Innovation》 EI CSCD 2020年第1期1-2,共2页
Human-machine interaction(HMI)is about the interaction design inside the cockpit of vehicle.It takes the human-centered design approach related to systems that help driver or passengers’communication with vehicles.En... Human-machine interaction(HMI)is about the interaction design inside the cockpit of vehicle.It takes the human-centered design approach related to systems that help driver or passengers’communication with vehicles.Ensuring safer driving and more effective communication between the human and the vehicle is the central focus.Its design challenges have changed a lot due to the increasing level of autonomous driving.What kind of interaction will be the mainstream?How would a driver’s personality influence the driver’s attitude toward active safety and trust of the autonomous driving?How should HMI be designed for the handover scenarios from Level 3 to Level 5 autonomous driving?What HMI solutions make the driving safer and improve user experience? 展开更多
关键词 communication driving HMI
Size or diversity?Synthetic dataset recommendations for machine learning heating energy prediction models in early design stages for residential buildings 认领 引用
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作者 Xinyue Wang Yinan Yu +1 位作者 Robin Teigland Alexander Hollberg 《Energy and AI》 EI CSCD 2025年第3期480-501,共22页
One promising means to reduce building energy for a more sustainable environment is to conduct early-stage building energy optimization using simulation,yet today’s simulation engines are computationally intensive.Re... One promising means to reduce building energy for a more sustainable environment is to conduct early-stage building energy optimization using simulation,yet today’s simulation engines are computationally intensive.Recently,machine learning(ML)energy prediction models have shown promise in replacing these simulation engines.However,it is often difficult to develop such ML models due to the lack of proper datasets.Synthetic datasets can provide a solution,but determining the optimal quantity and diversity of synthetic data remains a challenging task.Furthermore,there is a lack of understanding of the compatibility between different ML algorithms and the characteristics of synthetic datasets.To fill these gaps,this study conducted multiple ML experiments using residential buildings in Sweden to determine the best-performing ML algorithm,as well as the characteristics of the corresponding synthetic dataset.A parametric model was developed to generate a wide range of synthetic datasets varying in size and building shape,referred to as diversity.Five ML algorithms selected through a literature review were trained using the different datasets.Results show that the Support Vector Machine performed the best overall.Multiple Linear Regression performed well with small and lowdiverse datasets,while the Artificial Neural Network performed well with large and high-diverse datasets.We conclude that developers should focus more on increasing diversity instead of size once the dataset size reaches around 1440 when generating synthetic training datasets.This study offers insights for researchers and practitioners,such as software tool developers,when developing ML building energy prediction models in early-stage optimization. 展开更多
关键词 Machine learning Early-stage optimization Building energy Synthetic data Training size Data diversity
Adapting Memory Hierarchies for Emerging Datacenter Interconnects 认领 引用 被引量：1
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作者 江涛 侯锐 +5 位作者 董建波 柴琳 Sally A. McKee 田斌 张立新 孙凝晖 《Journal of Computer Science & Technology》 SCIE EI CSCD 2015年第1期97-109,共13页
Efficient resource utilization requires that emerging datacenter interconnects support both high performance communication and efficient remote resource sharing. These goals require that the network be more tightly co... Efficient resource utilization requires that emerging datacenter interconnects support both high performance communication and efficient remote resource sharing. These goals require that the network be more tightly coupled with the CPU chips. Designing a new interconnection technology thus requires considering not only the interconnection itself, but also the design of the processors that will rely on it. In this paper, we study memory hierarchy implications for the design of high-speed datacenter interconnects particularly as they affect remote memory access -- and we use PCIe as the vehicle for our investigations. To that end, we build three complementary platforms： a PCIe-interconnected prototype server with which we measure and analyze current bottlenecks; a software simulator that lets us model microarchitectural and cache hierarchy changes; and an FPGA prototype system with a streamlined switchless customized protocol Thunder with which we study hardware optimizations outside the processor. We highlight several architectural modifications to better support remote memory access and communication, and quantify their impact and ]imitations. 展开更多
关键词 high-speed interconnect memory hierarchy time shared memory datacenter network
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