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2007 IEEE Intelligent Transportation Systems Conference最新文献

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An Algorithm to Compensate for Road Illumination Changes for AID Systems 辅助系统道路光照变化补偿算法研究
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357652
Jun Cai, M. Shehata, Wael Badawy, Muzamil S. Pervez
{"title":"An Algorithm to Compensate for Road Illumination Changes for AID Systems","authors":"Jun Cai, M. Shehata, Wael Badawy, Muzamil S. Pervez","doi":"10.1109/ITSC.2007.4357652","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357652","url":null,"abstract":"Many ITS systems suffer from high false alarm rates due to static glare. Static glare appears in video scenes when the road is wet and light originating from static light source, such as road lamp, is reflected on the road. Often an Automatic Incidents Detection (AID) system will detect occurrences of static glare as incidents, causing the generation of false alarms. In this paper, an effective real-time algorithm is proposed to detect static glare. This algorithm generates a static glare map that can be used by an AID system to avoid static glare false alarms.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129527492","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: 10
A Dynamic Traffic Forecast Using Hybrid Wavelet Network with an Adaptive Genetic Local Search 基于自适应遗传局部搜索的混合小波网络动态交通预测
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357671
Kai Cao, Mo Zhao
{"title":"A Dynamic Traffic Forecast Using Hybrid Wavelet Network with an Adaptive Genetic Local Search","authors":"Kai Cao, Mo Zhao","doi":"10.1109/ITSC.2007.4357671","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357671","url":null,"abstract":"The paper proposes a dynamic predictor using hybrid wavelet neural network, which use multiple types of mother wavelet in the network according to the feature of pattern change of predicted information instead of a single type. The predictor has function of parallel prediction. In addition, an adaptive genetic local search algorithm is employed to train effectively the network. A case study of traffic information forecasting using proposed wavelet neural network is demonstrated.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128419407","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
Multi-Classifier Based LIDAR and Camera Fusion 基于多分类器的激光雷达与相机融合
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357683
J. Hwang, Seungdeuk Cho, Kyung-Jin Ryu, Seungkeun Park, Euntai Kim
{"title":"Multi-Classifier Based LIDAR and Camera Fusion","authors":"J. Hwang, Seungdeuk Cho, Kyung-Jin Ryu, Seungkeun Park, Euntai Kim","doi":"10.1109/ITSC.2007.4357683","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357683","url":null,"abstract":"We present a sensor fusion system using lidar and camera. We separate the system into two part which is hypothesis generation part and hypothesis verification part. These parts use different single sensors. Hypothesis generation is done using the lidar and hypothesis verification is done using the camera image. In hypothesis generation, we cluster the lidar data and do a perspective mapping to generate the candidate. In hypothesis verification, we used 5-SVMs classifier. Based on the candidate position, the candidate is putted in different SVM. In the result, we compared the result between 5-SVM hypothesis verification and single SVM hypothesis verification. The result showed 2.2% improvement.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128526418","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
A Transportation Facilities Management Tree Model Based on IPv6 基于IPv6的交通设施管理树模型
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357749
Zhiheng Li, Zuo Zhang, Qiang Chen, Yudong Chen
{"title":"A Transportation Facilities Management Tree Model Based on IPv6","authors":"Zhiheng Li, Zuo Zhang, Qiang Chen, Yudong Chen","doi":"10.1109/ITSC.2007.4357749","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357749","url":null,"abstract":"Transportation facilities management faces the challenge of huge amount of geographically dispersed facilities. Communication between them is one of the critical issues. Recent studies show that IT technology is one of efficient solutions. The development of IPv6 enables the possibility of connecting all the facilities to Internet with its large address space and improved performance in routing, mobility and safety. This paper presents a layered tree model of managing transportation facilities based on IPv6. According to the proposed model, different transportation facilities can be managed uniformly over the widely spread road network. And the paper discusses how the model structure is built, the management functions and the communication features based on the model. Then, a demo application is introduced to show that the tree structure is in accordance with next generation Internet thus could support for future ITS.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128266243","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 study on incident detection model applying APID model, fuzzy logic and traffic pattern 应用APID模型、模糊逻辑和流量模式的事件检测模型研究
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357788
Nam-Kwan Hong, Jin-Woo Choi, Young-Kyu Yang
{"title":"A study on incident detection model applying APID model, fuzzy logic and traffic pattern","authors":"Nam-Kwan Hong, Jin-Woo Choi, Young-Kyu Yang","doi":"10.1109/ITSC.2007.4357788","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357788","url":null,"abstract":"The study has designed an incident detection model by utilizing fuzzified APID Model along with traffic pattern, for realizing incident detection that is more efficient and suitable for road environment with lamps. Traffic data used by the model are traffic volume, occupancy and speed collected for 3 months in 5 minute interval by the loop detector installed at the Seoul Ring Road. The APID Model uses upper and lower threshold data detected by the loop detector. However, these data do not reflect road environment selected by the study. Therefore, the study has fuzzified variables to suit single site loop detector configuration, adopted MIN-MAX centroid method for inference method and adopted center of gravity method for defuzzification method. Also, the study has designed an incident pattern by considering compressional wave test, confirmation of road incident dissolution, day of the week and varying traffic occupancy shown by different links. In addition, incident rate and differences in incident pattern values of finally modified APID Model had been used to derive the incident rate threshold value for judging occurrence of an incident. The result of detection rate and false alarm rate test, conducted to comparatively analyze conventional APID Model, fuzzified APID Model and proposed integration model, has shown improved performance by the model suggested by the study.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"33 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128732872","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
Multiple Vehicles Detection and Tracking based on Scale-Invariant Feature Transform 基于尺度不变特征变换的多车检测与跟踪
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357684
Jae-Young Choi, Kyung-Sang Sung, Young-Kyu Yang
{"title":"Multiple Vehicles Detection and Tracking based on Scale-Invariant Feature Transform","authors":"Jae-Young Choi, Kyung-Sang Sung, Young-Kyu Yang","doi":"10.1109/ITSC.2007.4357684","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357684","url":null,"abstract":"To monitor road situation, the source from CCTV is more useful than any other data from GPS or loop detector because it can give the whole picture of the two-dimensional traffic situation. This paper suggests multiple vehicles detection by quad-tree segmentation and tracking method using scale invariant feature transform to improve the performance of tracking for extracting traffic parameter such as vehicle count, speed, class, and so on. The experimental result presents the proposed method is effective and robust on detection and tracking vehicle, especially in cases that a vehicle changes a lane, occlusion of vehicles is occurred, and an affine shape of vehicle is changed due to car movement.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128960342","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: 53
Pattern Analysis of Mobile Traffic Information User Service 移动交通信息用户服务模式分析
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357626
Hojin Shin, D. Noyce, X. Qin
{"title":"Pattern Analysis of Mobile Traffic Information User Service","authors":"Hojin Shin, D. Noyce, X. Qin","doi":"10.1109/ITSC.2007.4357626","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357626","url":null,"abstract":"This paper presents research on a wireless Internet portal in South Korea serviced by SK Telecom. Data utilized for this research included a service log for the entire year of 2004. Frequency analysis of requested information showed that 'Section Speed' was the most requested data by drivers, followed by 'Traffic Status'. Monthly analysis showed that people most often requested information in January, August, and September. This result was likely due to increased traffic volume and corresponding congestion while people make more trips for holidays in those months. More information requests occurred on weekends versus weekdays, and during evening hours rather than other times of the day. In comparison with Automatic Response Service, a similar pattern was observed for the monthly and daily service request rate, though NATE had more service requests than ARS. Analysis of section speed request showed that people used the service more as traffic congestion increased.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125690884","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 Hierarchy Control Algorithm and its application in Urban Arterial Control Problem 一种层次控制算法及其在城市干线控制问题中的应用
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357673
Juan Chen, Lihong Xu, Xiaoguang Yang, Changliang Yuan
{"title":"A Hierarchy Control Algorithm and its application in Urban Arterial Control Problem","authors":"Juan Chen, Lihong Xu, Xiaoguang Yang, Changliang Yuan","doi":"10.1109/ITSC.2007.4357673","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357673","url":null,"abstract":"The purpose of this paper is to investigate the application of a hierarchy control algorithm in solving the traffic signal timing control problem for an oversaturated traffic arterial. In the local control layer, the concept of feeding delay and non-feeding delay is introduced , and the cell transmission model is used to calculate the feeding delay and the non-feeding delay, then the control problem is formulated as an conflicted multi-objective control problem, and an IPNSGA-II based compatible controller installed at adjacent junctions is used to design signal timing plan for each junctions. Then in the coordination layer, based on the state of density on each link, three rules are proposed to define the range of the junctions required to be coordinated. Finally, the IPNSGA-II is used to design the traffic signal timing plan for the junction group. Simulation results show that the proposed algorithm is capable of dealing with real-time oversaturated traffic arterial control problem. The algorithm is tested in a simulation environment consisting of a core area of 7 junctions. It can be concluded that the proposed method is much more effective in relieving oversaturation in a network than the isolated intersection control strategy.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130754867","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: 7
Vehicle Detection under Various Lighting Conditions by Incorporating Particle Filter 基于粒子滤波的不同光照条件下车辆检测
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357745
Yi-Ming Chan, Shih-Shinh Huang, L. Fu, P. Hsiao
{"title":"Vehicle Detection under Various Lighting Conditions by Incorporating Particle Filter","authors":"Yi-Ming Chan, Shih-Shinh Huang, L. Fu, P. Hsiao","doi":"10.1109/ITSC.2007.4357745","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357745","url":null,"abstract":"We propose an automatic system to detect preceding vehicles on the highway under various lighting and different weather conditions based on the computer vision technologies. To adapt to different characteristics of vehicle appearance at daytime and nighttime, four cues including underneath, vertical edge, symmetry and taillight are fused for the preceding vehicle detection. By using particle filter with four cues through the processes including initial sampling, propagation, observation and cue fusion and evaluation, particle filter accurately generates the vehicle distribution. Thus, the proposed system can successfully detect and track preceding vehicles and be robust to different lighting conditions. Unlike normal particle filter focuses on a single target distribution in a discrete state space, we detect multiple vehicles with particle filter through a high-level tracking strategy using clustering technique called basic sequential algorithmic scheme (BSAS). Finally, experimental results for several videos from different scenes are provided to demonstrate the effectiveness of our proposed system.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130892651","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: 77
Residual Salinity Detection on Road Surface Using Neural Network 基于神经网络的路面残余盐分检测
2007 IEEE Intelligent Transportation Systems Conference Pub Date : 2007-10-22 DOI: 10.1109/ITSC.2007.4357800
M. Yamada, H. Yasukawa, T. Tanizaki, K. Ueda
{"title":"Residual Salinity Detection on Road Surface Using Neural Network","authors":"M. Yamada, H. Yasukawa, T. Tanizaki, K. Ueda","doi":"10.1109/ITSC.2007.4357800","DOIUrl":"https://doi.org/10.1109/ITSC.2007.4357800","url":null,"abstract":"This article discusses the use of microwaves to detect saline solutions on road surfaces in winter. The reflection characteristics of water and saline solutions at microwave frequencies depend on the respective dielectric constants. Therefore, the salinity and thickness of films seem to be detectable based on reflection characteristics. We confirm this ability through theoretical calculations and verification experiments. Field tests verify the practicality of this approach. Furthermore, we propose a new estimation method for the relationships salinity level and reflection characteristics using neural networks. It is shown that the proposed method has a good performance.","PeriodicalId":211095,"journal":{"name":"2007 IEEE Intelligent Transportation Systems Conference","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127903675","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
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