2022 IEEE Intelligent Vehicles Symposium (IV)最新文献_第6页

Comparison of Video-based Driver Gaze Region Estimation Techniques 基于视频的驾驶员注视区域估计技术比较

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827145

Hans-Joachim Bieg, Simon Strobel, M. Fischer, Paula Laßmann

引用次数: 0

Stochastic lateral noise and movement by Brownian differential models 布朗微分模型的随机横向噪声和运动

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827388

Hongsheng Qi, Yuyan Ying, Jiahao Zhang

{"title":"Stochastic lateral noise and movement by Brownian differential models","authors":"Hongsheng Qi, Yuyan Ying, Jiahao Zhang","doi":"10.1109/iv51971.2022.9827388","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827388","url":null,"abstract":"The microscopic behavior of the vehicle can be decomposed into car following and lane changing, and can be described by the longitudinal and lateral movement. The longitudinal movement has long been studied, while the lateral counterpart, especially the stochastic lateral movement, has rarely been investigated. The lacking of an understanding of the lateral behavior makes current microscopic simulation results deviate from real-world observations. Besides, many behavior identification algorithms which rely on lateral displacement are not robust, if the lateral stochastic nature is not well studied. To fill in this gap, a stochastic differential equation approach is employed. Firstly, the lateral noise is modeled by a transformed Brownian motion. Then the noise is embedded into a differential lateral movement model. The parameters in the lateral noise and movement models all have clear physical meaning. The Fokker-Planck equation, which describes the distribution evolution of the lateral displacement, is derived. A parameters calibration procedure is derived using the Euler discretization scheme. The model is calibrated using real world data. The results show that the proposed model can well describe the lateral movement distribution.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128696151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Energy Management Strategy for Hybrid Energy Storage System using Optimized Velocity Predictor and Model Predictive Control 基于优化速度预测器和模型预测控制的混合储能系统能量管理策略

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827322

Zhiwu Huang, Pei Huang, Yue Wu, Heng Li, Hui Peng, Jun Peng

引用次数: 0

INS/Odometer/Trackmap-aided Railway Train Localization under GNSS Jamming Conditions GNSS干扰条件下的INS/Odometer/ trackmap辅助铁路列车定位

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827385

Zhuojian Cao, Jiang Liu, Wei Jiang, B. Cai, J. Wang

{"title":"INS/Odometer/Trackmap-aided Railway Train Localization under GNSS Jamming Conditions","authors":"Zhuojian Cao, Jiang Liu, Wei Jiang, B. Cai, J. Wang","doi":"10.1109/iv51971.2022.9827385","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827385","url":null,"abstract":"GNSS (Global Navigation Satellite System) is virtually becoming an autonomous train localization technology for the next-generation train control system. However, potential threats from the intentional interference may severely degrade the availability of GNSS due to its vulnerability. It is of great significance to detect and isolate the negative effects from GNSS interference for the Train Control System (TCS) in the railway field. For the protection against GNSS jamming, extra information from the Inertial Navigation System (INS) and odometer are involved, and an INS/odometer/trackmap-aided GNSS localization method for railway trains is raised in this paper. While the GNSS receiver cannot identify the real signals under a high-power jamming attack condition, a prediction deduced train position generation approach is proposed. In this strategy, velocity from the odometer and the geospatial constraint from the trackmap are involved to calibrate INS, with which continuous positioning is realized under a GNSS-denied situation. Furthermore, while the measurements degradation occurs caused by a relatively low power jamming, a residual-test-based detection solution based on the deviation between the predicted reference pseudo-ranges and the real ones is proposed to isolate degraded measurements. Results from an experiment under a GPS jamming condition demonstrate that the proposed solution outperforms the GPS Single Point Positioning (SPP) and the conventional GPS/INS method. The jamming protection and continuous positioning performance under specific jamming conditions enhance the capability of resilient train positioning.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122594337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Augmented Reality on LiDAR data: Going beyond Vehicle-in-the-Loop for Automotive Software Validation 基于激光雷达数据的增强现实:超越车辆在环的汽车软件验证

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827351

Thomas Genevois, Jean-Baptiste Horel, A. Renzaglia, C. Laugier

引用次数: 6

Public Expectations Regarding the Longer-term Implications of and Regulatory Changes for Autonomous Driving: A Contribution to the Debate on its Social Acceptance 公众对自动驾驶的长期影响和监管变化的期望:对其社会接受度辩论的贡献

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827210

T. Fleischer, M. Puhe, J. Schippl, Yukari Yamasaki

引用次数: 1

Cooperative Platooning with Mixed Traffic on Urban Arterial Roads 城市主干道混合交通协同队列

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827105

Zeyu Mu, Zheng Chen, Seunghan Ryu, S. Avedisov, Rui Guo, B. Park

{"title":"Cooperative Platooning with Mixed Traffic on Urban Arterial Roads","authors":"Zeyu Mu, Zheng Chen, Seunghan Ryu, S. Avedisov, Rui Guo, B. Park","doi":"10.1109/iv51971.2022.9827105","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827105","url":null,"abstract":"In this paper, we showcase a framework for cooperative mixed traffic platooning that allows the platooning vehicles to realize multiple benefits from using vehicle-to-everything (V2X) communications and advanced controls on urban arterial roads. A mixed traffic platoon, in general, can be formulated by a lead and ego connected automated vehicles (CAVs) with one or more unconnected human-driven vehicles (UHVs) in between. As this platoon approaches an intersection, the lead vehicle uses signal phase and timing (SPaT) messages from the connected intersection to optimize its trajectory for travel time and energy efficiency as it passes through the intersection. These benefits carry over to the UHVs and the ego vehicle as they follow the lead vehicle. The ego vehicle then uses information from the lead vehicle received through basic safety messages (BSMs) to further optimize its safety, driving comfort, and energy consumption. This is accomplished by the recently designed cooperative adaptive cruise control with unconnected vehicles (CACCu). The performance benefits of our framework are proven and demonstrated by simulations using real-world platooning data from the CACC Field Operation Test (FOT) Dataset from the Netherlands.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133611706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Action Inference of Rear Seat Passenger for In-Vehicle Service 车载服务中后座乘客的行为推理

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827225

Jingo Adachi, Hiroshi Tsukahara, N. Mizuno, Akira Yoshizawa

引用次数: 0

Dynamic Conflict Mitigation for Cooperative Driving Control of Intelligent Vehicles 智能汽车协同驾驶控制的动态冲突缓解

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827379

Mohamed Radjeb Oudainia, C. Sentouh, Anh‐Tu Nguyen, J. Popieul

{"title":"Dynamic Conflict Mitigation for Cooperative Driving Control of Intelligent Vehicles","authors":"Mohamed Radjeb Oudainia, C. Sentouh, Anh‐Tu Nguyen, J. Popieul","doi":"10.1109/iv51971.2022.9827379","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827379","url":null,"abstract":"The work described in this paper proposes a new dynamic conflict attenuation strategy in driving shared control for intelligent vehicles lane keeping systems (LKS). This strategy takes into account the activity and availability of the driver as well as the external risk and conflict between the driver and the control system in order to manage and adapt the level of assistance in real time. The design of an adaptive shared controller is based on a dynamic multi-objective cost function that changes according to the level of assistance. Based on Lyapunov stability arguments, the global asymptotical stability of the closed-loop control system with the adaptive cost function and the variation in vehicle speed is proven and an LMI optimization is used to formulate the control design. The simulation results, conducted with the SHERPA dynamic car simulator under real-world driving situations, for different scenarios show the importance of adapting the controller in real time in order to decrease the conflict between the driver and the lane keeping system and to ensure the safety of the vehicle as well as to increase the confidence and acceptability of the driver.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"108 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113969412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Real-to-Synthetic: Generating Simulator Friendly Traffic Scenes from Graph Representation 真实合成:从图形表示生成模拟器友好的交通场景

2022 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2022-06-05 DOI: 10.1109/iv51971.2022.9827441

Yafu Tian, Alexander Carballo, Rui Li, K. Takeda

{"title":"Real-to-Synthetic: Generating Simulator Friendly Traffic Scenes from Graph Representation","authors":"Yafu Tian, Alexander Carballo, Rui Li, K. Takeda","doi":"10.1109/iv51971.2022.9827441","DOIUrl":"https://doi.org/10.1109/iv51971.2022.9827441","url":null,"abstract":"Reproducing real-world traffic scenes in the simulator is fundamental to training self-driving systems. Creating a simulation scenario is a complex task, generally done manually: the ego-vehicle and other entities are placed and their trajectories defined, trying to recreate some situation found in real traffic. To reduce the manual burden, here we propose the Real-to-Synthetic toolset. This toolset provides synthetic traffic scene in openDrive format, which can be directly simulated in many simulators such as SUMO or CARLA. Also, we provide a scene generator which generates near-realistic scene from minimum user effort. To maintain the similarity between real-world scene and generated one, here we introduce the concept “Road Scene Graph”(RSG). In this graph, nodes represent entities while edges stand for pairwise relationships. These relationships could be maintained in the scene generation process while the actor is generated according to the distribution sampled from real-world data. Experiments proved that by using “Road Scene Graph”, our scene generator proposes a much more convenient way to conFigure traffic scenes rather than manually defining every actor’s initial status and trajectories.","PeriodicalId":184622,"journal":{"name":"2022 IEEE Intelligent Vehicles Symposium (IV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121478529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4