International Conference on Intelligent Transportation Systems最新文献_第4页

Semantic Hierarchy Based Reasoning Chain Algorithm for Event Detection on an Intersection 基于语义层次的交叉口事件检测推理链算法

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC.2006.1706765

S. Kamijo, Xiaolu Liu

引用次数: 0

Research on Fuzzy Adaptive H∞ Robust Filter for Integrated Navigation System 组合导航系统模糊自适应H∞鲁棒滤波器研究

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC.2008.4732653

Jiang Liu, Jian Wang, B. Cai

引用次数: 2

Method of Multi-lane Vehicles Speed Continuously Perceiving Based on Single Roadside Camera 基于单个路边摄像头的多车道车辆速度连续感知方法

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC55140.2022.9921759

Linguo Chai, Haojie Pang, W. Shangguan, B. Cai

{"title":"Method of Multi-lane Vehicles Speed Continuously Perceiving Based on Single Roadside Camera","authors":"Linguo Chai, Haojie Pang, W. Shangguan, B. Cai","doi":"10.1109/ITSC55140.2022.9921759","DOIUrl":"https://doi.org/10.1109/ITSC55140.2022.9921759","url":null,"abstract":"Roadside camera has been widely applied to detect the traffic status and now it is an important component composing the digital road infrastructure. A novel method of multi-lane vehicles speed continuously perceiving based on single roadside camera is proposed in this paper. Firstly, extended Haar feature is adopted by identifying objects of roadside camera video to achieve the training data set. Then, an AdaBoost cascade classifier is designed and optimized based on iterative learning of the data set for accurately vehicle identifying. Thirdly, an association tracker is proposed based on MOSSE to realize multi-vehicle tracking in consecutive video frames, and average pixel and Euclidean distance are applied to locate the vehicle position and calculate the vehicle trajectory. At last, a transformation relation of image pixel to physical distance is proposed to obtain the vehicle real time speed. The proposed method has been verified with real roadside camera data. The experimental results show that the vehicle recognizing accuracy is above 98.02%, the vehicle speed perceiving error is within $pm 2%$, and the proposed method can deal with real time roadside camera data with good.","PeriodicalId":184458,"journal":{"name":"International Conference on Intelligent Transportation Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122981508","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: 0

The Analysis of Traffic Variables for EV's Driving Efficiency in Urban Traffic Condition 城市交通条件下电动汽车行驶效率的交通变量分析

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC55140.2022.9921918

Dongmin Kim, H. Ng, K. Jang

{"title":"The Analysis of Traffic Variables for EV's Driving Efficiency in Urban Traffic Condition","authors":"Dongmin Kim, H. Ng, K. Jang","doi":"10.1109/ITSC55140.2022.9921918","DOIUrl":"https://doi.org/10.1109/ITSC55140.2022.9921918","url":null,"abstract":"This paper presents the influential factors on the driving efficiency of electric vehicles (EV s) under different urban traffic conditions. By formulating the energy consumption and recharge model based on EV's vehicle dynamics, a simulation is then carried out to observe the effects of traffic variables on EV driving efficiency. EV driving efficiency maps are plotted from different traffic conditions, and traffic variables that includes headways, vehicle speeds and acceleration are identified to have significant effects on EV driving efficiency. The outcome also showed that the link speed, which is widely used as a predictor for EV efficiency, has limitations in estimating the efficiency as it spatiotemporally aggregates the individual vehicle driving conditions. This paper found that, based on the efficiency plots, the quantitative relationship between EV driving efficiency and other traffic characteristic variables, and suggested the effective speed range as a new indicator for EV driving energy efficiency. This paper provides a framework that can be used to estimate the EV efficiency under various traffic conditions and to reduce energy consumption during trips in their corresponding roadway networks.","PeriodicalId":184458,"journal":{"name":"International Conference on Intelligent Transportation Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128571057","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: 0

RTAS: Road Test with Artificial Scenarios RTAS:模拟场景的道路测试

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC55140.2022.9922464

Lidan Zhang, Fei Li, Xinxin Zhang, Xiangbin Wu

{"title":"RTAS: Road Test with Artificial Scenarios","authors":"Lidan Zhang, Fei Li, Xinxin Zhang, Xiangbin Wu","doi":"10.1109/ITSC55140.2022.9922464","DOIUrl":"https://doi.org/10.1109/ITSC55140.2022.9922464","url":null,"abstract":"The decision making module in self-driving cars requires extensive performance testings and safety evaluations on real roads. While providing a naturalistic driving environment, the road test poses several problems, including uncontrollable risks, rare complex and dangerous scenarios, and higher costs. Testing in a simulator could provide unrestricted scenarios, but it lacks real-time dynamic feedback from either vehicle or road. To bridge the gap between physical and virtual testing, we propose a novel test and evaluation system, called Road Test with Artificial Scenarios (RTAS), which injects generated virtual scenarios to the physical VUT (Vehicle Under Test) in real time. For virtual scenarios, we propose a deep generative network with the road structure, layout of traffic participants and expected safety critical measurement as inputs. Meanwhile, the VUT is driving in a controlled physical environment (e.g. a test track) and its motion planner is modified by directly taking generated scenarios as inputs. Furthermore, the motion of the VUT is captured by localization devices and passed to the scenario generation as the instant feedback of the VUT. To demonstrate the feasibility of our proposal, we implement a prototype based on a scaled indoor test field, which integrates our scenario generation with Carla simulator and a 1/18 scale vehicle running on a scale indoor test field.","PeriodicalId":184458,"journal":{"name":"International Conference on Intelligent Transportation Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116040242","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: 0

Emotion modeling of the driver based on fuzzy logic 基于模糊逻辑的驾驶员情感建模

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC.2009.5309644

Zhenlong Li, Xiaoxi Wang

引用次数: 9

A Flow Volumes Data Compression Approach for Traffic Network Based on Principal Component Analysis 基于主成分分析的交通网络流量数据压缩方法

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC.2007.4357668

Li Qu, Jianming Hu, Yi Zhang

引用次数: 40

Cluster Analysis on Evaluation Indicators of Driver Characteristics 驾驶员特征评价指标的聚类分析

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC.2007.4357771

Yuepeng Cui, Yaping Zhang, Yanli Ma, Yuqin Feng

引用次数: 1

Vehicle-in-the-Loop Intelligent Connected Vehicle Simulation System Based on Vehicle-Road-Cloud Collaboration 基于车-路-云协同的车在环智能网联仿真系统

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC55140.2022.9922190

Shuguang Li, Zhonglin Luo, Wenbo Wei, Yang Zhao, Jierui Hu, Hong Cheng

{"title":"Vehicle-in-the-Loop Intelligent Connected Vehicle Simulation System Based on Vehicle-Road-Cloud Collaboration","authors":"Shuguang Li, Zhonglin Luo, Wenbo Wei, Yang Zhao, Jierui Hu, Hong Cheng","doi":"10.1109/ITSC55140.2022.9922190","DOIUrl":"https://doi.org/10.1109/ITSC55140.2022.9922190","url":null,"abstract":"Autonomous driving test technology is an important guarantee for the large-scale commercialization of autonomous vehicles(AV). The existing test methods are mainly based roads and simulations. Traditional vehicle road test has real traffic environment, but the diversity of test scenarios is limited. It is difficult to customize corner case scenarios safely and efficiently. Simulation testing is flexible and efficient, but the lack of a real traffic flow test environment separates the strong coupling relationship between the vehicle and the environment in practical application scenarios. In view of above, a novel Vehicle-in-the- Loop(ViL) verification method based on vehicle-road-cloud collaboration is proposed in this paper. (1) On the roadside, we propose a road real-time traffic flow element perception method based on monocular camera, and apply the real traffic flow to autonomous driving simulation testing. (2) On cloud platform, we independently develop a simulation platform based on Open- SceneGraph(OSG), which can quickly simulate different weather, lighting and other disturbance factors such as virtual pedestrians and vehicles based on real scenes. (3) On the vehicle, we build a closed-loop test system that combine intelligent connected vehicle(ICV) and mixed environments. This paper takes the autonomous driving obstacle avoidance algorithm in the campus road scene as an example, and completes the system test in the mixed scene. Experiments show that our proposed method can be used as a safer and more efficient test method before autonomous vehicle road test.","PeriodicalId":184458,"journal":{"name":"International Conference on Intelligent Transportation Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125318122","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: 0

A Smart vision system for advanced LGV navigation and obstacle detection 用于先进轻型车辆导航和障碍物检测的智能视觉系统

International Conference on Intelligent Transportation Systems Pub Date : 1900-01-01 DOI: 10.1109/ITSC.2012.6338760

M. Bertozzi, L. Bombini, A. Broggi, A. Coati

引用次数: 2