2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)最新文献

Fuzzy logic based localization for vehicular ad hoc networks 基于模糊逻辑的车载自组织网络定位

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009487

Lina Altoaimy, I. Mahgoub

{"title":"Fuzzy logic based localization for vehicular ad hoc networks","authors":"Lina Altoaimy, I. Mahgoub","doi":"10.1109/CIVTS.2014.7009487","DOIUrl":"https://doi.org/10.1109/CIVTS.2014.7009487","url":null,"abstract":"Recent advances in wireless communications have led to the development of vehicular ad hoc networks (VANETs). It has attracted the interest of both industrial and academic communities due to its potential in reducing accidents and saving lives. In VANETs, vehicles can communicate with each other to exchange traffic and road information. One of the challenges in VANETs is to determine the location of a vehicle in the network. In this paper, we propose an intelligent localization method, which is based on fuzzy logic and neighbors' location information. The main objective of our proposed method is to estimate the location of a vehicle by utilizing the location information of its neighboring vehicles. To achieve accurate localization, we model vehicles' weights using fuzzy logic system, which utilizes the distance and heading information in order to obtain the weight values. By assigning weights to neighboring vehicles' coordinates, we expand the concept of centroid localization (CL). We evaluate our proposed method via simulation and compare its performance against CL. Results obtained from the simulation are promising and demonstrate the effectiveness of the proposed method in varying traffic densities.","PeriodicalId":283766,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123056233","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

Genetic adaptive A-Star approach for ttrain trip profile optimization problems 列车行程曲线优化问题的遗传自适应A-Star方法

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009488

Jin Huang, Lei Sun, F. Du, Hai Wan, Xibin Zhao

引用次数: 5

Cloud aided semi-active suspension control 云辅助半主动悬架控制

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009481

Zhaojian Li, I. Kolmanovsky, E. Atkins, Jianbo Lu, Dimitar Filev, J. Michelini

引用次数: 42

Exploring the Mahalanobis-Taguchi approach to extract vehicle prognostics and diagnostics 探索Mahalanobis-Taguchi方法提取车辆预测和诊断

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009482

M. Gosnell, R. Woodley

{"title":"Exploring the Mahalanobis-Taguchi approach to extract vehicle prognostics and diagnostics","authors":"M. Gosnell, R. Woodley","doi":"10.1109/CIVTS.2014.7009482","DOIUrl":"https://doi.org/10.1109/CIVTS.2014.7009482","url":null,"abstract":"Army logistical systems and databases contain massive amounts of data that require effective methods of extracting actionable information and generating knowledge. Vehicle diagnostics and prognostics can be challenging to analyze from the Command and Control (C2) perspective, making management of the fleet difficult within existing systems. Databases do not contain root causes or the case-based analyses needed to diagnose or predict breakdowns. 21st Century Systems, Inc. previously introduced the Agent-Enabled Logistics Enterprise Intelligence System (AELEIS) to assist logistics analysts with assessing the availability and prognostics of assets in the logistics pipeline. One component being developed within AELEIS is incorporation of the Mahalanobis-Taguchi System (MTS) to assist with identification of impending fault conditions along with fault identification. This paper presents an analysis into the application of MTS within data representing a known vehicular fault, showing how construction of the Mahalanobis Space using competing methodologies can lead to reduced false positives while still capturing true positive fault conditions. These results are then discussed within the larger scope of AELEIS and the resulting C2 benefits.","PeriodicalId":283766,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130752437","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

Evolving the topology of subway networks using genetic algorithms 基于遗传算法的地铁网络拓扑演化

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009478

A. Bazzan, S. Dahmen

引用次数: 0

An evolutionary approach to traffic assignment 交通分配的进化方法

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009476

A. Bazzan, Daniel Cagara, B. Scheuermann

引用次数: 17

Behavior characteristics of mixed traffic flow on campus 校园混合交通流行为特征研究

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009490

Mianfang Liu, Shengwu Xiong, Xiaohan Yu, Pengfeng Duan, Jun Wang

{"title":"Behavior characteristics of mixed traffic flow on campus","authors":"Mianfang Liu, Shengwu Xiong, Xiaohan Yu, Pengfeng Duan, Jun Wang","doi":"10.1109/CIVTS.2014.7009490","DOIUrl":"https://doi.org/10.1109/CIVTS.2014.7009490","url":null,"abstract":"Campus security is an important part of social security in China. As reported in exist literature, very limited efforts are made to study mixed traffic flow behavior on campus. Present study attempts to highlight studies of single traffic flow or pedestrian-vehicle traffic flow. This paper deals with the research into the analysis of the characteristics of mixed traffic flow on campus, including cars, motorbikes, bicycles, and pedestrians. Total 440 minutes video data on two different locations on campus are extracted by employing videographic technique. The research is designed determine factors for traffic flow variety. Fluctuations in traffic flow depends on the student schedules, particularly during the peak time as there are large pedestrian flow and bicycle flow in short interval time. At the same time, a spatial-temporal analysis for establishing the relationship about mixed traffic flows is discussed. Flow models of speed-flow, speed-occupancy, flow-occupancy about mixed traffic are developed to illustrate behavior characteristics of mixed traffic stream on campus of different dimensions. The results obtained are significant for evacuation simulation and planning under various conditions on campus.","PeriodicalId":283766,"journal":{"name":"2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123623846","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

Robust obstacle segmentation based on topological persistence in outdoor traffic scenes 基于拓扑持久性的室外交通场景鲁棒障碍物分割

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009483

Chunpeng Wei, Qian Ge, Somrita Chattopadhyay, E. Lobaton

引用次数: 10

Driver distraction detection by in-vehicle signal processing 基于车载信号处理的驾驶员分心检测

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009479

Seon-Ho Im, Cheolha Lee, Seok-Joo Yang, Jinhak Kim, B. You

引用次数: 9

A GPU-based real-time traffic sign detection and recognition system 基于gpu的实时交通标志检测与识别系统

2014 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems (CIVTS) Pub Date : 2014-12-01 DOI: 10.1109/CIVTS.2014.7009470

Zhilu Chen, Xinming Huang, Zhen Ni, Haibo He

引用次数: 20