2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)最新文献

Overlay coding for road-to-vehicle visible light communication using LED array and high-speed camera 利用LED阵列和高速摄像机实现道路与车辆可见光通信的覆盖编码

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2012-12-01 DOI: 10.1109/GLOCOMW.2012.6477757

Sayaka Nishimoto, T. Yamazato, Hiraku Okada, T. Fujii, T. Yendo, Shintaro Arai

{"title":"Overlay coding for road-to-vehicle visible light communication using LED array and high-speed camera","authors":"Sayaka Nishimoto, T. Yamazato, Hiraku Okada, T. Fujii, T. Yendo, Shintaro Arai","doi":"10.1109/GLOCOMW.2012.6477757","DOIUrl":"https://doi.org/10.1109/GLOCOMW.2012.6477757","url":null,"abstract":"This paper aims to improve the visible light communication system using LED array and high-speed camera by proposing what we call “overlay coding”. “Overlay coding” is a new coding method to realize a hierarchical coding, through which a high-priority data can be received even if the receiver is far from a transmitter. Conventionally, the hierarchical coding has been realized through the wavelet transform that has a limitation of number and disposition of LEDs, and as a result it does not always match with the design of the transmitters (e.g. traffic lights, etc.) used in real life. To solve the limitation problem, we propose a more flexible way of designing the application of LEDs depending on the transmitters. In particular, overlay coding is realized through the procedures of coding and decoding. In coding, we replace one LED with a flexible number of LEDs, and the number depends on whether the data is high-priority or low-priority, then high-priority data and low-priority data are overlaid (section III-B1). In decoding, we first obtain the high-priority data, and then the low-priority data using retrieved high-priority data (section III-B2). The experimental result shows that the distance for receiving error-free data is extended from 30m to 70m in the overlay coding (section IV-B).","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129902647","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: 43

Real-time implementation of a novel safety function for prevention of loss of vehicle control 实时实现新颖的安全功能，防止车辆失控

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6083082

Mohammad Ali, C. Olsson, J. Sjöberg

引用次数: 0

A method of vehicle dynamics prediction to anticipate the risk of future accidents: Experimental validation 一种预测未来事故风险的车辆动力学预测方法:实验验证

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6082888

Raymond Ghandour, Felipe H. R. da Cunha, A. Victorino, A. Charara, D. Lechner

引用次数: 8

Estimation of measures of effectiveness based on Connected Vehicle data 基于车联网数据的有效性度量估计

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6083020

J. Argote, Eleni Christofa, Yiguang Xuan, A. Skabardonis

引用次数: 26

Multivariate spatial clustering of traffic accidents for local profiling of risk factors 基于多变量空间聚类的交通事故危险因素局部分析

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6082946

C. Figuera, J. Lillo, I. Mora-Jiménez, J. Rojo-álvarez, A. Caamaño

{"title":"Multivariate spatial clustering of traffic accidents for local profiling of risk factors","authors":"C. Figuera, J. Lillo, I. Mora-Jiménez, J. Rojo-álvarez, A. Caamaño","doi":"10.1109/ITSC.2011.6082946","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082946","url":null,"abstract":"According to previous studies, traffic accident data have a spatial dependence which should be taken into account when analyzed. For this purpose, a proper spatial segmentation of accidents should be carried out so that subsequent spatial analysis can provide significant results. In this work, we propose a method for spatial clustering of multiple variables in order to make a new spatial characterization of the different road stretches and then to assign them into a small set of typical accidents according to their risk profile. First, every road is segmented according to an estimation of the corresponding spatial accident density. Then, each segment is characterized with a numerical vector representing accident attributes. The spatial clustering is performed in the third stage by applying a k-means clustering algorithm. Traffic accident data from Comunidad Valenciana, in Spain, have been used for testing our method. Results show that our approach is a flexible and intuitive way for spatially characterizing the roads of the region under study, and even for finding relationships between values of the analyzed risk factors.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115540127","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: 1

Kernel-based modeling and optimization for density estimation in transportation systems using floating car data 基于核的交通系统密度估计建模与优化

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6083098

Arash Tabibiazar, O. Basir

{"title":"Kernel-based modeling and optimization for density estimation in transportation systems using floating car data","authors":"Arash Tabibiazar, O. Basir","doi":"10.1109/ITSC.2011.6083098","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6083098","url":null,"abstract":"Traffic congestion is one of major problems in numerous cities especially in urban areas. An appropriate solution comes from the modeling of traffic data and understanding the congestion characteristics. Various methods were developed to solve this problem, however, still necessary to develop new approaches. In this paper, a kernel-based density estimation method is utilized to extract the congestion spots in urban areas based on collected position samples with time-stamp from floating car data. A probabilistic framework is developed to model the traffic data with generalized Gaussian density and then to find optimized weights of kernels in an approximation function, centered at points-of-interest by minimizing the Cramer-von Mises distance between localized cumulative distributions of mixture of Dirac distributions of position samples and Gaussian mixtures of points-of-interest in a pre-defined time window. The approximation density function by optimized kernels' weights can be used to estimate the mobile vehicles density in a specific time and space. Modeling the traffic data to extract the required parameters improves the performance significantly. The proposed method is applied to real measurements and can be implemented in real time in traffic management systems.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116039113","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

Real-time freeway traffic state prediction: A particle filter approach 实时高速公路交通状态预测:一种粒子滤波方法

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6082873

Hao Chen, H. Rakha, Shereef Sadek

{"title":"Real-time freeway traffic state prediction: A particle filter approach","authors":"Hao Chen, H. Rakha, Shereef Sadek","doi":"10.1109/ITSC.2011.6082873","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082873","url":null,"abstract":"The research presented in this paper develops a multi-step traffic state prediction algorithm using spot speed measurements. The traditional Lighthill-Whitham-Richards (LWR) flow continuity equation is combined with the Van Aerde traffic stream model to generate a new partial differential equation (PDE) named the Van Aerde flow continuity model. The numerical solution of the PDE is obtained using the Godunov discretization scheme to generate a time series equation that characterizes the temporal and spatial relationship of traffic speed data. Because of the strong nonlinearity of the discretized speed update equation, a robust particle filter is applied to conduct a muti-step speed prediction using speed measurements. The prediction accuracy of the proposed approach is compared to the state-of-the-art Ensemble Kalman filter with the Greenshields traffic stream model using simulated loop detector data from Interstate 66. The results demonstrate that the proposed particle filter approach in combination with the discretized Van Aerde flow continuity model produces the lowest prediction error of 4.3 km/h for a five-minute prediction horizon, and accurately predicts the spatial and temporal propagation of shockwaves.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116559292","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: 42

A maritime ITS architecture for e-Navigation and e-Maritime: Supporting environment friendly ship transport 面向电子导航和电子海事的海上智能交通系统架构:支持环境友好型船舶运输

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6082963

Ø. Rødseth

{"title":"A maritime ITS architecture for e-Navigation and e-Maritime: Supporting environment friendly ship transport","authors":"Ø. Rødseth","doi":"10.1109/ITSC.2011.6082963","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082963","url":null,"abstract":"Ship transport can be said to be the original Intelligent Transport System and developments in this sector should be of interest for ITS research in other modes. This paper will investigate the requirements to a Maritime ITS architecture and describe elements of a possible solution. A driving force behind this architecture is the international nature of ship transport and the need to establish standards for information exchanges to further increase efficiency, reduce greenhouse gas (GHG) emissions and improve the security in the sector. Obviously, reduction of GHG emissions through operational measures can also reduce costs. This has been realized by the shipping community and the e-Navigation (by International Maritime Organization — IMO) and e-Maritime (by European Union — EU) initiatives testify to this. Both initiatives have identified the information architecture as critical for the future development of the ship transport area. The development of a maritime ITS architecture needs to consider legacy systems, the international nature of shipping, international legislation and standards as well as highly varying quality of service on available communication channels.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122637392","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: 16

Analysis of network-level traffic states using locality preservative non-negative matrix factorization 基于局域保留非负矩阵分解的网络级流量状态分析

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6083060

Yufei Han, F. Moutarde

引用次数: 24

Relevance estimation of traffic elements using Markov logic networks 基于马尔可夫逻辑网络的交通要素相关性估计

2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC) Pub Date : 2011-11-18 DOI: 10.1109/ITSC.2011.6082903

Dennis Nienhüser, T. Gumpp, Johann Marius Zöllner

{"title":"Relevance estimation of traffic elements using Markov logic networks","authors":"Dennis Nienhüser, T. Gumpp, Johann Marius Zöllner","doi":"10.1109/ITSC.2011.6082903","DOIUrl":"https://doi.org/10.1109/ITSC.2011.6082903","url":null,"abstract":"Complex traffic situations e.g. at intersections consist of many traffic participants, traffic elements and relations between them. The behavior of participants is constrained by implicit and explicit traffic rules. We are interested in estimating whether a given traffic element — a traffic sign, a traffic light — is relevant in the current driving situation, i.e. affects the set of possible legal actions. A wide variety of properties influences the relevance. The route to take for example affects which traffic lights are relevant and the current weather situation affects whether a speed limit restricted by a supplementary sign is in effect. We use first-order logic to model such relations and apply reasoning to decide upon the relevance of static traffic elements. The need for perfect information is alleviated with the help of Markov logic networks, reconciling hard decision rules on the one hand and uncertainty intrinsic to the environment perception process on the other hand. The evaluation of twelve intersection scenes shows very promising results for the relevance estimation of traffic lights: Markov logic networks are able to judge whether enough information is available and determine the relevant traffic lights reliably in such cases.","PeriodicalId":186596,"journal":{"name":"2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114398857","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: 13