Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.最新文献_第7页

Location-based ticketing in public transport 基于位置的公共交通票务

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1007/978-3-540-72621-0_6

A. Bohm, B. Murtz, G. Sommer, M. Wermuth

引用次数: 21

Implementation of traffic management using transit probes 利用交通探针实施交通管理

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520142

F. W. Cathey, D. Dailey

引用次数: 4

An integrated emergency evacuation system for real-time operations - a case study of Ocean City, Maryland under hurricane attacks 用于实时操作的综合紧急疏散系统-飓风袭击下马里兰州大洋城的案例研究

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520061

Y. Liu, N. Zou, G. Chang

{"title":"An integrated emergency evacuation system for real-time operations - a case study of Ocean City, Maryland under hurricane attacks","authors":"Y. Liu, N. Zou, G. Chang","doi":"10.1109/ITSC.2005.1520061","DOIUrl":"https://doi.org/10.1109/ITSC.2005.1520061","url":null,"abstract":"The consecutive hurricane attacks to US coastline have drawn significant attentions to evacuation operations related issues. To better prepare the state of Maryland for potential hurricanes, this study presents an emergency evacuation system that integrates both optimization and microscopic simulation methods. The optimization module applies a two-level process to generate the preliminary optimal control plans, which is based on a revised cell transmission formulation for large-scale network applications. Using the optimized results as the initial input, the simulation module takes into account various operational constraints and driver responses that are difficult to be captured realistically with mathematical formulations. The proposed system also features its flexibility for potential users to adjust the optimized plans in both the planning phase and real-time operations based on the results of simulation evaluation. The case study with the data from Ocean City, Maryland during hurricane attacks has demonstrated the potential of the proposed system for evacuation of traffic flows in large-scale networks within a given time window.","PeriodicalId":153203,"journal":{"name":"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132132972","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

Performance evaluation of an adaptive travel time prediction model 自适应行程时间预测模型的性能评价

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520187

S. Bajwa, Edward Chung, Masao Kuwahara

引用次数: 56

Adaptive space division multiplexing: an improved link layer protocol for inter-vehicle communications 自适应空分多路复用:一种用于车辆间通信的改进链路层协议

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520091

J. Blum, A. Eskandarian

引用次数: 20

Using ITS data fusion to examine traffic dynamics on a freeway with variable speed limits 使用ITS数据融合来检查可变限速高速公路上的交通动态

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520188

R. Bertini, S. Boice, K. Bogenberger

引用次数: 16

Traffic signal priority/preemption control with colored Petri nets 彩色Petri网控制交通信号优先/抢占

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520132

Lefei Li, Wei-Hua Lin, Hongchao Liu

引用次数: 18

Traffic surveillance from a safety perspective: an ITS data application 安全视角下的交通监控:ITS数据应用

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520060

M. Abdel-Aty, A. Pande, N. Uddin

{"title":"Traffic surveillance from a safety perspective: an ITS data application","authors":"M. Abdel-Aty, A. Pande, N. Uddin","doi":"10.1109/ITSC.2005.1520060","DOIUrl":"https://doi.org/10.1109/ITSC.2005.1520060","url":null,"abstract":"Reactive traffic management strategies such as incident detection are becoming less relevant with the advancement of mobile phone usage. Freeway management in the 21st century needs to shift focus toward proactive strategies that include anticipating incidents such as the crashes. \"Predicting\" crash occurrences would also be the key to traffic safety. A two-step approach to identify freeway locations with high probability of crashes through real-time traffic surveillance data is presented here. For this study historical crash and corresponding traffic data from loop detectors were gathered from a 58-km (36-mile) corridor of Interstate-4. Following an exploratory analysis two types of logistic regression models, i.e., simple and multivariate, were developed. The simple models were used to deduce time-space patterns of variation in crash risk while the multivariate model was chosen for final classification of traffic patterns. As a suggested application for the simple models, their output may be used for preliminary assessment of the crash risk. If there is an indication of high crash risk then the multivariate model may be employed to explicitly classify the data patterns as leading or not-leading to crash occurrence. A demonstration of this two-stage real-time application strategy is also provided in the paper.","PeriodicalId":153203,"journal":{"name":"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122054888","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: 2

A framework for integrating existing and novel intelligent transportation systems 一个整合现有和新型智能交通系统的框架

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520124

R. Meier, A. Harrington, V. Cahill

{"title":"A framework for integrating existing and novel intelligent transportation systems","authors":"R. Meier, A. Harrington, V. Cahill","doi":"10.1109/ITSC.2005.1520124","DOIUrl":"https://doi.org/10.1109/ITSC.2005.1520124","url":null,"abstract":"Efficient use and re-use of traffic data depends on an ITS architecture that enables information sharing across a wide variety of intelligent transportation systems and applications. Existing ITS architectures, such as KAREN or the national ITS architecture, can be used to develop systems within a given framework thereby facilitating such inter-system integration. However, these architectures typically include assumptions regarding the overall organization of system functionality that prohibit integration of previously deployed systems without major reengineering. This paper presents a framework for an ITS architecture that has been designed for integrating novel as well as existing intelligent transportation systems and applications. The iTransIT framework supports a number of possible systems interaction paradigms and proposes a layered data model to facilitate data exchange between systems with diverse service requirements and functional organizations. These data layers are defined within a common context model, may be distributed across multiple systems, and exploit the overlapping temporal and spatial aspects of information generated and used by both legacy and future systems.","PeriodicalId":153203,"journal":{"name":"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127339472","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: 35

Rule based prediction of fastest paths on urban networks 城市网络中基于规则的最快路径预测

Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005. Pub Date : 2005-10-24 DOI: 10.1109/ITSC.2005.1520183

A. Awasthi, Y. Lechevallier, M. Parent, J. Proth

{"title":"Rule based prediction of fastest paths on urban networks","authors":"A. Awasthi, Y. Lechevallier, M. Parent, J. Proth","doi":"10.1109/ITSC.2005.1520183","DOIUrl":"https://doi.org/10.1109/ITSC.2005.1520183","url":null,"abstract":"Estimation of fastest paths on large networks forms a crucial part of dynamic route guidance systems. The present paper proposes a statistical approach for predicting fastest paths on urban networks. The traffic data used for conducting the statistical analysis are the input flows, the arc states or the number of cars in the arcs and the different paths of the network. The statistical method proposed is called hybrid clustering and consists of four methods namely multiple correspondence analysis, k-means clustering, Ward's hierarchical agglomerative clustering and canonical correlation analysis. The results obtained from hybrid clustering on the traffic data are decision rules that yield the fastest path for a given set of arc states and input flows. These decision rules are stored in a huge database for performing predictive route guidance. Whenever a driver arrives at the entry point of the network, the current arc states and input flows of the network are searched in the database to extract the corresponding decision rule for finding the fastest path. When no rule is found in the database for a given set of input flow and arc states, the shortest path is predicted as the fastest path.","PeriodicalId":153203,"journal":{"name":"Proceedings. 2005 IEEE Intelligent Transportation Systems, 2005.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127902511","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: 15