2015 IEEE Intelligent Vehicles Symposium (IV)最新文献_第10页

The influence of traffic on heavy-duty vehicle platoon formation 交通对重型车辆排队形的影响

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225678

Kuo-Yun Liang, Q. Deng, J. Mårtensson, Xiaoliang Ma, K. Johansson

引用次数: 34

Map free lane following based on low-cost laser scanner for near future autonomous service vehicle 基于低成本激光扫描仪的免地图车道跟踪技术在未来自动驾驶服务车辆中的应用

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225767

Zhiwei Song, Weiwei Huang, Ning Wu, Xiaojun Wu, Chern Yuen Anthony Wong, V. B. Saputra, Benjamin Chia Hon Quan, Chen Jian Simon, Qun Zhang, Susu Yao, Boon Siew Han

{"title":"Map free lane following based on low-cost laser scanner for near future autonomous service vehicle","authors":"Zhiwei Song, Weiwei Huang, Ning Wu, Xiaojun Wu, Chern Yuen Anthony Wong, V. B. Saputra, Benjamin Chia Hon Quan, Chen Jian Simon, Qun Zhang, Susu Yao, Boon Siew Han","doi":"10.1109/IVS.2015.7225767","DOIUrl":"https://doi.org/10.1109/IVS.2015.7225767","url":null,"abstract":"This paper proposes a map free lane following solution based on low-cost 2D laser scanners for Autonomous Service Vehicle to fill the gap between future driverless car and the lane keeping assistant. The applications of autonomous service vehicle include feeder bus in a local residential area, shuttle bus in a park or playground, sprinkler car, sweeper car, and transporter in airport or container terminal. As autonomous service vehicle is running only in a limited area and its speed is slow compared to normal vehicles, we can further simplify the problem regardless of the issues of road infrastructure detection/communication and V2I maps which prevent the popularization of driverless car, and to propose a unique map free solution. The features of our approach include: 1) an innovative configuration for two 2D laser scanners to detect the lane with sharp curve; 2) a fast and accurate lane detection algorithm based on 2D laser's raw date directly; 3) a reliable and smooth path planning based on local lane fitting and prediction; and 4) a self-built unique drive-by-wire system for electronic car. We successfully tested our vehicle with autonomous driving in the testing field. The experiments show that the vehicle's trajectory matched the planned path accurately.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"10 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":"114263720","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: 12

Trajectories planning for multiple UAVs by the cooperative and competitive PSO algorithm 基于合作与竞争粒子群算法的多无人机轨迹规划

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225671

Jun Liu, T. Shi, Ping Li, X. Ren, Hongbin Ma

引用次数: 8

Development of driver-state estimation algorithm based on Hybrid Bayesian Network 基于混合贝叶斯网络的驾驶员状态估计算法研究

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225873

Dong Woon Ryu, Hyeon Bin Jeong, Sang Hun Lee, Woon-Sung Lee, J. H. Yang

引用次数: 6

Adaptive dynamic preview control for autonomous vehicle trajectory following with DDP based path planner 基于DDP路径规划器的自动驾驶车辆轨迹跟踪自适应动态预览控制

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225817

Ning Wu, Weiwei Huang, Zhiwei Song, Xiaojun Wu, Qun Zhang, Susu Yao

引用次数: 14

A method for driving control authority transition for cooperative autonomous vehicle 一种协作式自动驾驶车辆驾驶控制权限转移方法

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225717

Yongbon Koo, Jinwoo Kim, Wooyong Han

{"title":"A method for driving control authority transition for cooperative autonomous vehicle","authors":"Yongbon Koo, Jinwoo Kim, Wooyong Han","doi":"10.1109/IVS.2015.7225717","DOIUrl":"https://doi.org/10.1109/IVS.2015.7225717","url":null,"abstract":"Many researchers have reported that a decline in driving concentration caused by drowsiness or inattentiveness is one of the primary sources of serious car accidents. One of the most well-known methods to measure a driver's concentration is called driver state monitoring, where the driver is warned when he or she is falling asleep based on visual information of the face. On the other hand, autonomous driving systems have garnered attention in recent years as an alternative plan to reduce human-caused accidents. This system shows the possibility of realizing a vehicle with no steering wheel or pedals. However, lack of technical maturity, human acceptance problems, and individual desire to drive highlight the demand to keep human drivers in the loop. For these reasons, it is necessary to decide who will be responsible for driving the vehicle and adjusting the vehicle control system. This is known as the driving control authority. In this paper, we present a system that can suggest transitions in various driving control authority modes by sensing a decline of the human driver's performance caused by drowsiness or inattentiveness. In more detail, we identify the problems of the legacy driving control authority transition made only with vision-based driver state recognition. To address the shortcomings of this method, we propose a new recommendation method that combines the vision-based driver state recognition results and path suggestion of an autonomous system. Experiment results of simulated drowsy and inattentive drivers on an actual autonomous vehicle prototype show that our method has better transition accuracy with fewer false-positive errors compared with the legacy transition method that only uses vision-based driver state recognition.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"40 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":"127716452","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

Improving yaw stability control in severe instabilities by means of a validated model of driver steering 通过验证的驾驶员转向模型改进严重不稳定情况下的偏航稳定性控制

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225656

G. Markkula, Johan Eklov, L. Laine, Erik Wikenhed, Niklas Frojd

引用次数: 2

Intelligent navigation system-based optimization of the energy consumption 基于智能导航系统的能耗优化

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225780

A. Cabani, R. Khemmar, J. Ertaud, J. Mouzna

引用次数: 6

Fusion of laser and radar sensor data with a sequential Monte Carlo Bayesian occupancy filter 融合激光和雷达传感器数据与顺序蒙特卡罗贝叶斯占用滤波器

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225827

Dominik Nuss, Ting Yuan, Gunther Krehl, M. Stuebler, Stephan Reuter, K. Dietmayer

{"title":"Fusion of laser and radar sensor data with a sequential Monte Carlo Bayesian occupancy filter","authors":"Dominik Nuss, Ting Yuan, Gunther Krehl, M. Stuebler, Stephan Reuter, K. Dietmayer","doi":"10.1109/IVS.2015.7225827","DOIUrl":"https://doi.org/10.1109/IVS.2015.7225827","url":null,"abstract":"Occupancy grid mapping is a well-known environment perception approach. A grid map divides the environment into cells and estimates the occupancy probability of each cell based on sensor measurements. An important extension is the Bayesian occupancy filter (BOF), which additionally estimates the dynamic state of grid cells and allows modeling changing environments. In recent years, the BOF attracted more and more attention, especially sequential Monte Carlo implementations (SMC-BOF), requiring less computational costs. An advantage compared to classical object tracking approaches is the object-free representation of arbitrarily shaped obstacles and free-space areas. Unfortunately, publications about BOF based on laser measurements report that grid cells representing big, contiguous, stationary obstacles are often mistaken as moving with the velocity of the ego vehicle (ghost movements). This paper presents a method to fuse laser and radar measurement data with the SMC-BOF. It shows that the doppler information of radar measurements significantly improves the dynamic estimation of the grid map, reduces ghost movements, and in general leads to a faster convergence of the dynamic estimation.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"404 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":"115340990","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: 57

An overview of vehicular platoon control under the four-component framework 四组份框架下的车辆排控制综述

2015 IEEE Intelligent Vehicles Symposium (IV) Pub Date : 2015-08-27 DOI: 10.1109/IVS.2015.7225700

S. Li, Yang Zheng, Keqiang Li, Jianqiang Wang

引用次数: 170