2014 IEEE Intelligent Vehicles Symposium Proceedings最新文献

GPS precise positioning with pseudorange evaluation using 3-dimensional maps GPS精确定位与伪距评估利用三维地图

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-07-17 DOI: 10.1109/IVS.2014.6856423

S. Miura, Feiyu Chen, S. Kamijo

引用次数: 0

Towards a cross-layer based MAC for smooth V2V and V2I communications for safety applications in DSRC/WAVE based systems 在基于DSRC/WAVE系统的安全应用中实现顺畅的V2V和V2I通信的跨层MAC

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856579

K. A. Rahman, K. Tepe

引用次数: 21

Prediction of Next Contextual Changing Point of Driving Behavior Using Unsupervised Bayesian Double Articulation Analyzer 基于无监督贝叶斯双发音分析器的驾驶行为下一个情境变化点预测

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856468

Shogo Nagasaka, T. Taniguchi, K. Hitomi, Kazuhito Takenaka, T. Bando

{"title":"Prediction of Next Contextual Changing Point of Driving Behavior Using Unsupervised Bayesian Double Articulation Analyzer","authors":"Shogo Nagasaka, T. Taniguchi, K. Hitomi, Kazuhito Takenaka, T. Bando","doi":"10.1109/IVS.2014.6856468","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856468","url":null,"abstract":"Future advanced driver assistance systems (ADASs) should observe a driving behavior and detect contextual changing points of driving behaviors. In this paper, we propose a novel method for predicting the next contextual changing point of driving behavior on the basis of a Bayesian double articulation analyzer. To develop the method, we extended a previously proposed semiotic predictor using an unsupervised double articulation analyzer that can extract a two-layered hierarchical structure from driving-behavior data. We employ the hierarchical Dirichlet process hidden semi-Markov model [4] to model duration time of a segment of driving behavior explicitly instead of the sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) employed in the previous model [13]. Then, to recover the hierarchical structure of contextual driving behavior as a sequence of chunks, we use the Nested Pitman-Yor Language model [6], which can extract latent words from sequences of latent letters. On the basis of the extension, we develop a method for calculating posterior probability distribution of the next contextual changing point by marginalizing potentially possible results of the chunking method and potentially successive words theoretically. To evaluate the proposed method, we applied the method to synthetic data and driving behavior data that was recorded in a real environment. The results showed that the proposed method can predict the next contextual changing point more accurately and in a longer-term manner than the compared methods: linear regression and Recurrent Neural Networks, which were trained through a supervised learning scheme.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"1 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":"116867729","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: 8

Autonomous emergency stop system 自动急停系统

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856482

S. Kwon, Changyoung Jung, T. Choi, Y. Oh, B. You

引用次数: 5

Vehicle localization enhancement with VANETs 利用VANETs增强车辆定位

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856576

A. Peker, T. Acarman, Cagdas Yaman, E. Yüksel

引用次数: 19

Impact of reduced visibility from fog on traffic sign detection 雾造成能见度降低对侦测交通标志的影响

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856535

R. Belaroussi, D. Gruyer

引用次数: 27

A performance test for a new reactive-cooperative filter in an ego-vehicle localization application 一种新的反应-协同滤波器在自驾车定位应用中的性能测试

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856472

A. R. A. Bacha, D. Gruyer, A. Lambert

{"title":"A performance test for a new reactive-cooperative filter in an ego-vehicle localization application","authors":"A. R. A. Bacha, D. Gruyer, A. Lambert","doi":"10.1109/IVS.2014.6856472","DOIUrl":"https://doi.org/10.1109/IVS.2014.6856472","url":null,"abstract":"This paper presents the Optimized Kalman Particle Swarm (OKPS) filter. This filter is a new robust data fusion approach adapted for ego-vehicle localization in degraded signal conditions. The OKPS is the improved version of the hybridization of the Particle Filter (PF) by Particle Swarm Optimization notions (PSO). Taking also some features from the Extended Kalman filter (EKF), the OKPS is designed for being more robust to noises such as GPS multipaths and also more reactive. The OKPS has the challenge of merging reactivity and resistance to noises. For high dynamic on-road vehicles localization, the balance between reactivity and robustness is critical. This paper introduces an intelligent collaborative localization algorithm inspired by PSO techniques that addresses this challenge. The OKPS filter outline integrates Particle Filter (PF) tracking, PSO evolutionary optimization and EKF self-diagnose. Using real world data, the OKPS is tested in comparison to the EKF and PF approaches performances. The comparison is done following new specific criteria, designed for ego-localization filter performances analysis. Competitive results are reached for a high dynamic on-road vehicle localization application.","PeriodicalId":254500,"journal":{"name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","volume":"79 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":"126966810","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

LAPS-II: 6-DoF day and night visual localisation with prior 3D structure for autonomous road vehicles LAPS-II:用于自动驾驶道路车辆的六自由度昼夜视觉定位，具有预先的3D结构

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856471

William P. Maddern, Alexander D. Stewart, P. Newman

引用次数: 35

A margin-based approach to threat assessment for autonomous highway navigation 基于边际的公路自主导航威胁评估方法

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856584

Alexandre Constantin, Junghee Park, K. Iagnemma

引用次数: 8

Multiple exposure images based traffic light recognition 基于多重曝光图像的交通灯识别

2014 IEEE Intelligent Vehicles Symposium Proceedings Pub Date : 2014-06-08 DOI: 10.1109/IVS.2014.6856541

C. Jang, Chansoo Kim, Dongchul Kim, Minchae Lee, M. Sunwoo

引用次数: 45