2015 IEEE Intelligent Vehicles Symposium (IV)最新文献_第3页

Driver model with motion stabilizer for vehicle-driver closed-loop simulation at high-speed maneuvering 高速机动车辆驾驶员闭环仿真的运动稳定器驾驶员模型

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225895

Youngil Koh, Hyundong Her, Kilsoo Kim, K. Yi

引用次数: 2

A probabilistic maneuver prediction framework for self-learning vehicles with application to intersections 一种自学习车辆概率机动预测框架及其在交叉口上的应用

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225710

J. Wiest, Matthias Karg, Felix Kunz, Stephan Reuter, U. Kressel, K. Dietmayer

引用次数: 24

A stereovision based approach for detecting and tracking lane and forward obstacles on mobile devices 一种基于立体视觉的方法，用于检测和跟踪移动设备上的车道和前方障碍物

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225756

Andra Petrovai, R. Danescu, S. Nedevschi

{"title":"A stereovision based approach for detecting and tracking lane and forward obstacles on mobile devices","authors":"Andra Petrovai, R. Danescu, S. Nedevschi","doi":"10.1109/IVS.2015.7225756","DOIUrl":"https://doi.org/10.1109/IVS.2015.7225756","url":null,"abstract":"This paper presents SmartCoDrive, an Android application which performs driving assistance functions: 3D lane detection and tracking, forward obstacle detection, obstacle tracking. With this mobile application we wish to increase the adoption rate of driving assistance systems and to provide a viable and cheap solution for every driver, that will be able to use his own tablet or smartphone as a personal driving assistant. The mobile application is deployed on a tablet equipped with dual back-facing cameras. The visual information from the two cameras, along with the data received from the Controller Area Network bus of the vehicle enable a thorough understanding of the 3D environment. First, we develop the sparse 3D reconstruction algorithm. Then, using monocular vision we perform lane markings detection. Obstacle detection is done by combining the superpixel segmentation with 3D information and the tracking algorithm is based on the Kalman Filter. Since the processing capabilities of the mobile platforms are limited, different optimizations are carried out in order to obtain a real-time implementation. The Android application may be used in urban traffic that is characterized by low-speed and short-medium distances to obstacles.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116142435","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

An improved 2D cost aggregation method for advanced driver assistance systems 一种改进的二维成本聚合方法用于高级驾驶员辅助系统

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225668

JeongMok Ha, Byeongchan Jeon, WooYeol Jun, Joonho Lee, Hong Jeong

引用次数: 2

Observing behaviors at intersections: A review of recent studies & developments 观察十字路口的行为:最近的研究和发展综述

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225855

Mohammad Shokrolah Shirazi, B. Morris

引用次数: 33

Overtaking maneuvers by non linear time scaling over reduced set of learned motion primitives 基于非线性时间尺度的超车机动简化学习运动原语集

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225672

Vishakh Duggal, K. Bipin, Ashutosh Kumar Singh, Bharath Gopalakrishnan, B. Bharti, A. Khiat, K. Krishna

{"title":"Overtaking maneuvers by non linear time scaling over reduced set of learned motion primitives","authors":"Vishakh Duggal, K. Bipin, Ashutosh Kumar Singh, Bharath Gopalakrishnan, B. Bharti, A. Khiat, K. Krishna","doi":"10.1109/IVS.2015.7225672","DOIUrl":"https://doi.org/10.1109/IVS.2015.7225672","url":null,"abstract":"Overtaking of a vehicle moving on structured roads is one of the most frequent driving behavior. In this work, we have described a Real Time Control System based framework for overtaking maneuver of autonomous vehicles. Proposed framework incorporates Intelligent Planning and Modular control modules. Intelligent Planning module of the framework enables the vehicle to intelligently select the most appropriate behavioral characteristics given the perceived operating environment. Subsequently, Modular control module reduces the search space of overtaking trajectories through an SVM based learning approach. These trajectories are then examined for possible future time collision using Velocity Obstacle. It employs non linear time scaling that provides for continuous trajectories in the space of linear and angular velocities to achieve continuous curvature overtaking maneuvers respecting velocity and acceleration bounds. Further time scaling also can scale velocities to avoid collisions and can compute a time optimal trajectory for the learned behavior. The preliminary results show the appropriateness of our proposed framework in virtual urban environment.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128505758","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

A practical trajectory planning framework for autonomous ground vehicles driving in urban environments 在城市环境中自动驾驶地面车辆的实用轨迹规划框架

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225840

Xiaohui Li, Zhenping Sun, Zhen He, Q. Zhu, Daxue Liu

{"title":"A practical trajectory planning framework for autonomous ground vehicles driving in urban environments","authors":"Xiaohui Li, Zhenping Sun, Zhen He, Q. Zhu, Daxue Liu","doi":"10.1109/IVS.2015.7225840","DOIUrl":"https://doi.org/10.1109/IVS.2015.7225840","url":null,"abstract":"This paper presents a practical trajectory planning framework towards fully autonomous driving in urban environments. Firstly, based on the behavioral decision commands, a reference path is extracted from the digital map using the LIDAR-based localization information. The reference path is refined and interpolated via a nonlinear optimization algorithm and a parametric algorithm, respectively. Secondly, the trajectory planning task is decomposed into spatial path planning and velocity profile planning. A closed-form algorithm is employed to generate a rich set of kinematically-feasible spatial path candidates within the curvilinear coordinate framework. At the same time, the velocity planning algorithm is performed with considering safety and smoothness constraints. The trajectory candidates are evaluated by a carefully developed objective function. Subsequently, the best collision-free and dynamically-feasible trajectory is selected and executed by the trajectory tracking controller. We implemented the proposed trajectory planning strategy on our test autonomous vehicle in the realistic urban traffic scenarios. Experimental results demonstrated its capability and efficiency to handle a variety of driving situations, such as lane keeping, lane changing, vehicle following, and static and dynamic obstacles avoiding, while respecting traffic regulations.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130192253","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: 28

Eco-driven signal control and eco-driving of hybrid city buses 混合动力城市客车生态驱动信号控制与生态驾驶

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225779

M. Haberl, M. Fellendorf

引用次数: 2

On the prediction of future vehicle locations in free-floating car sharing systems 自由浮动汽车共享系统中未来车辆位置的预测

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225816

S. Formentin, Andrea G. Bianchessi, S. Savaresi

引用次数: 13

Fast pixelwise road inference based on Uniformly Reweighted Belief Propagation 基于均匀重加权信念传播的快速像素道路推断

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225737

Mario Passani, J. J. Torres, L. Bergasa

引用次数: 7