2014 IEEE Intelligent Vehicles Symposium Proceedings最新文献_第10页

Instantaneous full-motion estimation of arbitrary objects using dual Doppler radar 利用双多普勒雷达对任意目标进行瞬时全运动估计

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856449

Dominik Kellner, M. Barjenbruch, J. Klappstein, J. Dickmann, K. Dietmayer

{"title":"Instantaneous full-motion estimation of arbitrary objects using dual Doppler radar","authors":"Dominik Kellner, M. Barjenbruch, J. Klappstein, J. Dickmann, K. Dietmayer","doi":"10.1109/IVS.2014.6856449","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856449","url":null,"abstract":"Based on high-resolution radars a new approach for determining the full 2D-motion state (yaw rate, longitudinal and lateral speed) of an extended rigid object in a single measurement is proposed. The system does not rely on any model assumptions and is independent of the exact position, expansion and orientation of the object. In comparison to related methods it is not based on temporal filtering, e.g. a Kalman Filter. These methods are subject to an initialization phase and depend heavily on compliance of the underlying dynamic model. In contrast to temporal filtering, the proposed approach reduces the time to react to critical situations that occur in many safety and advanced driving assistance applications. This paper analyzes the velocity profile (radial velocity over azimuth angles) of the object received by two Doppler radar sensors. The approach can handle white noise and systematic variations (e.g. micro-Doppler of wheels) in the signal. The proposed system is applied to predict the driving path of traffic participants. Measurement results are presented for a set-up with two 77 GHz automotive radar sensors.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130898693","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: 35

On-road PHEV power management with hierarchical strategies in vehicular networks 基于分层策略的车辆网络插电式混合动力电源管理

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856597

Bingnan Jiang, Yunsi Fei

{"title":"On-road PHEV power management with hierarchical strategies in vehicular networks","authors":"Bingnan Jiang, Yunsi Fei","doi":"10.1109/IVS.2014.6856597","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856597","url":null,"abstract":"In plug-in hybrid electric vehicles (PHEVs), the power management system coordinates powertrain operations to achieve high energy efficiency. Conventional PHEV power management systems work in either an online or offline mode. Most online systems are based on some pre-set power balancing strategies without utilizing the driving cycle or route information. Offline management strategies solved from historical driving cycles are not optimal for real specific driving routes. With the rapid development of vehicular networks and proliferation of smartphones, real-time traffic information can be collected by smartphones from a vehicular network so as to facilitate online PHEV power management. This paper proposes an on-road PHEV power management cyber-physical system (CPS) with 2-level hierarchical optimizations to minimize the fuel consumption of a trip. The high-level online stochastic optimization generates a battery energy budget for each road at runtime according to the traffic prediction and trip information. The low-level powertrain policies are solved offline from historical driving cycles. During driving, the high-level battery energy budgets and low-level policies are combined to get the optimal power decisions according to current driving states. Simulation results show that the proposed method significantly outperforms other three methods in fuel savings.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134156172","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: 6

Block-Sparse Representation Classification based gesture recognition approach for a robotic wheelchair 基于块稀疏表示分类的机器人轮椅手势识别方法

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856392

Ali Boyali, N. Hashimoto

引用次数: 15

Methodology for identifying car following events from naturalistic data 从自然数据中识别汽车跟随事件的方法

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856406

Kristofer D. Kusano, J. Montgomery, H. Gabler

{"title":"Methodology for identifying car following events from naturalistic data","authors":"Kristofer D. Kusano, J. Montgomery, H. Gabler","doi":"10.1109/IVS.2014.6856406","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856406","url":null,"abstract":"Naturalistic Driving Studies (NDS) are becoming an integral tool for development of driver assistance systems. Because of its large volume, one challenge with working with NDS data is identifying driving scenarios of interest automatically. This study introduces a methodology for identifying situations where the driver of the instrumented vehicle applied the brakes while following another vehicle. These car following events are of interest for designers of Forward Collision Warning (FCW) systems. This algorithm could be used in conjunction with a large scale NDS, such as the Virginia Tech Transportation Research Institute's 100-Car database, to generate population distributions of braking behavior during car following. These population distributions could be used to inform the design of warning thresholds for FCW. The heuristic algorithm developed in this study identifies car following events using forward looking radar (object range and range rate) and vehicle dynamics (speed, vehicle yaw rate). The proposed algorithm identified the same car following scenario as a visual inspection of the data in 91.8% of brake applications, suggesting it can automatically identify car following events.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133698926","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: 19

Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite 使用严肃游戏人为因素分析套件测试高级驾驶员辅助系统

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856618

João S. V. Gonçalves, R. Rossetti, João Jacob, Joel Gonçalves, C. Olaverri-Monreal, A. Coelho, R. Rodrigues

{"title":"Testing Advanced Driver Assistance Systems with a serious-game-based human factors analysis suite","authors":"João S. V. Gonçalves, R. Rossetti, João Jacob, Joel Gonçalves, C. Olaverri-Monreal, A. Coelho, R. Rodrigues","doi":"10.1109/IVS.2014.6856618","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856618","url":null,"abstract":"The development of Advanced Driver Assistance Systems (ADAS) is rapidly growing. However, most of the ADAS require field test, which is expensive, unpredictable and time consuming. In this paper we propose a multiagent-based driving simulator which integrates a human factor analysis suite and enables rapid and low-cost experimentation of mobile-device ADAS. Our architecture uses a microscopic simulator and a serious-game-based driving simulator. The latter allows the user to control a vehicle and change the correspondent simulation state in the microscopic simulator. The driving simulator also connects to an Android device and sends several kinds of data, such as current GPS coordinates or transportation network data. One important feature of this architecture is its suitability to serve as an appropriate means to conduct behaviour elicitation through peer-designed agents, so as to improve modelling of various driving styles accounting for different aspects of preferences and perception abilities, as well as other performance measures related to drivers' interaction with ADAS solutions. The potentials of our approach to aid experiments in human factor analysis are still to be tested, but are undoubtedly huge and encouraging.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132110644","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: 17

A behavioral planning framework for autonomous driving 自动驾驶行为规划框架

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856582

Junqing Wei, Jarrod M. Snider, Tianyu Gu, J. Dolan, B. Litkouhi

引用次数: 111

Fusion of map matching and traffic sign recognition 地图匹配与交通标志识别的融合

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856536

A. Peker, Oguz Tosun, H. L. Akin, T. Acarman

引用次数: 15

Online maneuver recognition and multimodal trajectory prediction for intersection assistance using non-parametric regression 基于非参数回归的交叉口辅助在线机动识别与多模态轨迹预测

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856480

Q. Tran, J. Firl

{"title":"Online maneuver recognition and multimodal trajectory prediction for intersection assistance using non-parametric regression","authors":"Q. Tran, J. Firl","doi":"10.1109/IVS.2014.6856480","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856480","url":null,"abstract":"Maneuver recognition and trajectory prediction of moving vehicles are two important and challenging tasks of advanced driver assistance systems (ADAS) at urban intersections. This paper presents a continuing work to handle these two problems in a consistent framework using non-parametric regression models. We provide a feature normalization scheme and present a strategy for constructing three-dimensional Gaussian process regression models from two-dimensional trajectory patterns. These models can capture spatio-temporal characteristics of traffic situations. Given a new, partially observed and unlabeled trajectory, the maneuver can be recognized online by comparing the likelihoods of the observation data for each individual regression model. Furthermore, we take advantage of our representation for trajectory prediction. Because predicting possible trajectories at urban intersection involves obvious multimodalities and non-linearities, we employ the Monte Carlo method to handle these difficulties. This approach allows the incremental prediction of possible trajectories in situations where unimodal estimators such as Kalman Filters would not work well. The proposed framework is evaluated experimentally in urban intersection scenarios using real-world data.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129442089","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: 121

Energy savings by wireless control of speed, scheduling and travel times for hauling operation 通过无线控制速度、调度和运输时间来节省能源

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856451

D. Rylander, J. Axelsson, P. Wallin

{"title":"Energy savings by wireless control of speed, scheduling and travel times for hauling operation","authors":"D. Rylander, J. Axelsson, P. Wallin","doi":"10.1109/IVS.2014.6856451","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856451","url":null,"abstract":"A Quarry and Aggregate production site consist of sequential production processes and activities to process and produce the output products. Compared to a fixed manufacturing plant, the quarry processes involve mobile machines such as wheel loaders, trucks and articulated haulers and a highly dynamic road infrastructure. Today, the mobile machines are generally not synchronized or controlled towards the overall throughput of the site in real time. This indicates a general improvement potential in increased productivity at quarry sites, but also unsolved challenges for the same reason. Assuming a wireless control system that controls speed and throughput of the different processes and activities, there would be a fuel reduction potential in controlling the mobile machines. This optimization requires models of machine fuel consumption for different applications, velocities and travel times. The main contribution of this paper is the presentation of fuel measurements based on different speeds, site application characteristics and travel times for hauling operation. The fuel measures reveal important aspects regarding how different velocities impact fuel consumption. The results of fuel measurements show a potential in fuel savings of up to 42% and a typical improvement of 20-30% depending on machine speeds, travel times, application and site characteristics. Based on this, some of the applications and challenges in wirelessly controlling machines are discussed.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114676552","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

Bayesian nonparametric modeling of driver behavior 驾驶员行为的贝叶斯非参数建模

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856580

Julian Straub, Sue Zheng, John W. Fisher III

{"title":"Bayesian nonparametric modeling of driver behavior","authors":"Julian Straub, Sue Zheng, John W. Fisher III","doi":"10.1109/IVS.2014.6856580","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856580","url":null,"abstract":"Modern vehicles are equipped with increasingly complex sensors. These sensors generate large volumes of data that provide opportunities for modeling and analysis. Here, we are interested in exploiting this data to learn aspects of behaviors and the road network associated with individual drivers. Our dataset is collected on a standard vehicle used to commute to work and for personal trips. A Hidden Markov Model (HMM) trained on the GPS position and orientation data is utilized to compress the large amount of position information into a small amount of road segment states. Each state has a set of observations, i.e. car signals, associated with it that are quantized and modeled as draws from a Hierarchical Dirichlet Process (HDP). The inference for the topic distributions is carried out using an online variational inference algorithm. The topic distributions over joint quantized car signals characterize the driving situation in the respective road state. In a novel manner, we demonstrate how the sparsity of the personal road network of a driver in conjunction with a hierarchical topic model allows data driven predictions about destinations as well as likely road conditions.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128437001","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: 9