Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456406
Wu Meng, S. Fengchun, N. Jinrui, Wang Dafang
This paper researches how physical layer influences the signal reflection of the CAN bus is carried on in both theory and experimental ways. In order to analyze the problems in engineering applies of CAN network, and to bring forward the methods to solve them. In this way, reference can be provided for the design of the communication based on CAN bus in the future.
{"title":"Research on reflection of CAN signal in transmission line","authors":"Wu Meng, S. Fengchun, N. Jinrui, Wang Dafang","doi":"10.1109/ICVES.2007.4456406","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456406","url":null,"abstract":"This paper researches how physical layer influences the signal reflection of the CAN bus is carried on in both theory and experimental ways. In order to analyze the problems in engineering applies of CAN network, and to bring forward the methods to solve them. In this way, reference can be provided for the design of the communication based on CAN bus in the future.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131174678","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456402
Zhang Tao, Yang Diange, Li Ting, Lian Xiaomin
Model of intersection, as a part of road network model, which is the basis of In-Vehicle Navigation System, provides an abstract description of urban traffic intersection. This paper proposes a Multi-branch model, which abstracts branch based on physical structure of intersection for describing structural features of different types of intersections. And on this basis it describes accurate navigation attributes for vehicle navigation. Experiment shows that the model can be conveniently applied to ln-Vehicle Navigation System, with accurate and abundant driving information. The model is proved practical for In-Vehicle Navigation System.
{"title":"Multi-branch model of intersection for vehicle navigation","authors":"Zhang Tao, Yang Diange, Li Ting, Lian Xiaomin","doi":"10.1109/ICVES.2007.4456402","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456402","url":null,"abstract":"Model of intersection, as a part of road network model, which is the basis of In-Vehicle Navigation System, provides an abstract description of urban traffic intersection. This paper proposes a Multi-branch model, which abstracts branch based on physical structure of intersection for describing structural features of different types of intersections. And on this basis it describes accurate navigation attributes for vehicle navigation. Experiment shows that the model can be conveniently applied to ln-Vehicle Navigation System, with accurate and abundant driving information. The model is proved practical for In-Vehicle Navigation System.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127006097","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456396
Li Da-xue, Wu Tao, Dai Bin
It is necessary to extend the intelligent vehicle to navigate from structured environment to rough terrain, which is a great challenge for environment modeling. Ladar and camera are the most widely used sensors, but each of them has shortcoming. In this paper, SVM method is used to fuse the information from ladar and color camera. After registration, ladar point is represented by its position and neighbored pixels in the image. The height of the object as well as the H and S components of the color of the pixels are selected to represent the terrain. Grass and non-grass terrain are recognized based on the features. Experiment shows this method is simple and efficiency.
{"title":"Fusing ladar and color image for detection grass off-road scenario","authors":"Li Da-xue, Wu Tao, Dai Bin","doi":"10.1109/ICVES.2007.4456396","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456396","url":null,"abstract":"It is necessary to extend the intelligent vehicle to navigate from structured environment to rough terrain, which is a great challenge for environment modeling. Ladar and camera are the most widely used sensors, but each of them has shortcoming. In this paper, SVM method is used to fuse the information from ladar and color camera. After registration, ladar point is represented by its position and neighbored pixels in the image. The height of the object as well as the H and S components of the color of the pixels are selected to represent the terrain. Grass and non-grass terrain are recognized based on the features. Experiment shows this method is simple and efficiency.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124360264","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456360
Kunfeng Wang, Zhenjiang Li, Qingming Yao, Wuling Huang, Fei-Yue Wang
The objective of this paper is to present a detailed description of using DSP board and image processing techniques to construct an automated vehicle counting system. Such a system has many potential applications, such as traffic signal control and district traffic abduction. We use TITMS320DM642 DSP as the computational unit to avoid heavy investment in industrial control computer while obtaining improved computational power and optimized system structure. The overall software is comprised of two parts: embedded DSP software and host PC software. The embedded DSP software acquires the video image from stationary cameras, detects and counts moving vehicles, and transmits the processing results and realtime images after compression to PC software through network. The host PC software works as a graphic user interface through which the end user can configure the DSP board parameters and access the video processing results. The vehicle detection and counting algorithm is carefully devised to keep robust and efficient in traffic scenes for longtime span and with changeful illumination. Experimental results show that the proposed system performs well in actual traffic scenes, and the processing speed and accuracy of the system can meet the requirement of practical applications.
{"title":"An automated vehicle counting system for traffic surveillance","authors":"Kunfeng Wang, Zhenjiang Li, Qingming Yao, Wuling Huang, Fei-Yue Wang","doi":"10.1109/ICVES.2007.4456360","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456360","url":null,"abstract":"The objective of this paper is to present a detailed description of using DSP board and image processing techniques to construct an automated vehicle counting system. Such a system has many potential applications, such as traffic signal control and district traffic abduction. We use TITMS320DM642 DSP as the computational unit to avoid heavy investment in industrial control computer while obtaining improved computational power and optimized system structure. The overall software is comprised of two parts: embedded DSP software and host PC software. The embedded DSP software acquires the video image from stationary cameras, detects and counts moving vehicles, and transmits the processing results and realtime images after compression to PC software through network. The host PC software works as a graphic user interface through which the end user can configure the DSP board parameters and access the video processing results. The vehicle detection and counting algorithm is carefully devised to keep robust and efficient in traffic scenes for longtime span and with changeful illumination. Experimental results show that the proposed system performs well in actual traffic scenes, and the processing speed and accuracy of the system can meet the requirement of practical applications.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128555838","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456355
Jungsook Kim, Jaehan Lim, B. Jang
The demand for the safety is increased in the telematics area. The main reason for the car accident is driver's delay in recognition and error in operation and judgment about danger. About 45 % car crash comes from delayed recognition and 28 % comes from error in operation and judgment. In order to solve the safety problem, we propose the wireless sensor system which can reduce the danger by warning invisible and unexpected risk in advance. In the consideration of environment which our system is deployed, our wireless sensor system for safety is composed of wireless sensor node sensing car existence with magnetic sensors, wireless relay node relaying the sensed data to the main server, and base station which is main server gathering all sensed data from sensor node and generating alarm messages. It is expected that our system successfully reduce car accident with wireless sensor network technology.
{"title":"Algorithm and system for traffic safety on the intersection","authors":"Jungsook Kim, Jaehan Lim, B. Jang","doi":"10.1109/ICVES.2007.4456355","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456355","url":null,"abstract":"The demand for the safety is increased in the telematics area. The main reason for the car accident is driver's delay in recognition and error in operation and judgment about danger. About 45 % car crash comes from delayed recognition and 28 % comes from error in operation and judgment. In order to solve the safety problem, we propose the wireless sensor system which can reduce the danger by warning invisible and unexpected risk in advance. In the consideration of environment which our system is deployed, our wireless sensor system for safety is composed of wireless sensor node sensing car existence with magnetic sensors, wireless relay node relaying the sensed data to the main server, and base station which is main server gathering all sensed data from sensor node and generating alarm messages. It is expected that our system successfully reduce car accident with wireless sensor network technology.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124558056","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456368
Shengmin Cui, Dafang Wang, Jianfeng Wang, Wu Meng
In order to analyze the schedulability of realtime transmission of multi-messages on controller area network (CAN), an amended scheduling algorithm is put forward. This algorithm is based on rate-monotonic (RM) scheduling algorithm, which is widely used on scheduling realtime multitasks on uniprocessor. CAN is treated as exclusive critical sections. The utilization of CAN is defined as a key factor of schedulability. A realistic workload of CAN in pure electric vehicle is present, and the schedulability of this system is calculated. The result is coincident to the actual work. The RM-scheduling upper limits of variant velocity messages are counted, which can be used as the guideline to evaluate the communication ability of CAN.
{"title":"Analysis of schedulability of CAN based on RM algorithm","authors":"Shengmin Cui, Dafang Wang, Jianfeng Wang, Wu Meng","doi":"10.1109/ICVES.2007.4456368","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456368","url":null,"abstract":"In order to analyze the schedulability of realtime transmission of multi-messages on controller area network (CAN), an amended scheduling algorithm is put forward. This algorithm is based on rate-monotonic (RM) scheduling algorithm, which is widely used on scheduling realtime multitasks on uniprocessor. CAN is treated as exclusive critical sections. The utilization of CAN is defined as a key factor of schedulability. A realistic workload of CAN in pure electric vehicle is present, and the schedulability of this system is calculated. The result is coincident to the actual work. The RM-scheduling upper limits of variant velocity messages are counted, which can be used as the guideline to evaluate the communication ability of CAN.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"148 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116580554","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456385
L. Zhifeng, Wang Jianqiang, L. Keqiang
In order to solve the problem of the instability in the selection of relevant target, caused by the complexity of the measurement environment of vehicular radar, a robust method to determine the relevant target using vehicular radar is proposed. Based on analyzing the measurement environment, the method uses the principle of the nearest object in the same lane for target pre-selection. The Kalman filter is applied to predict the target information and the relevance verification of the pre-selected target is done by the consistence checking. The target decisions are made through a "relevant target life cycle" method. The verification tests show that by efficiently eliminating the effects of ghost objects, other disturbances and the bumping and swinging of vehicle, the proposed method can accomplish the determination of relevant target under different conditions.
{"title":"A robust method to determine relevant target vehicle using vehicular radar","authors":"L. Zhifeng, Wang Jianqiang, L. Keqiang","doi":"10.1109/ICVES.2007.4456385","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456385","url":null,"abstract":"In order to solve the problem of the instability in the selection of relevant target, caused by the complexity of the measurement environment of vehicular radar, a robust method to determine the relevant target using vehicular radar is proposed. Based on analyzing the measurement environment, the method uses the principle of the nearest object in the same lane for target pre-selection. The Kalman filter is applied to predict the target information and the relevance verification of the pre-selected target is done by the consistence checking. The target decisions are made through a \"relevant target life cycle\" method. The verification tests show that by efficiently eliminating the effects of ghost objects, other disturbances and the bumping and swinging of vehicle, the proposed method can accomplish the determination of relevant target under different conditions.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127104619","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456388
Liang Zhao, Fei-Yue Wang
In this paper, an self-organizing TSK-type fuzzy neural network is proposed for predicting the short-term traffic flow. The proposed fuzzy neural network is adaptively organized from the collected short-term traffic flow data. The whole process is divided into two stage, i.e., structure identification and parameter learning. In structure identification, the mean shift clustering algorithm performs the whole traffic flow data set in order to generate the initial structure and mean firing strength method is used to prune the redundant fuzzy neurons. After the structure identification is finished, the chaotic parameter PSO is adopted to perform the parameter learning. Then the trained fuzzy neural network is employed the collected short- term traffic flow test set and the prediction result verifies that the self-organizing TSK-type fuzzy neural network has higher prediction accuracy than some traditional methods.
{"title":"Short-term fuzzy traffic flow prediction using self-organizing TSK-type fuzzy neural network","authors":"Liang Zhao, Fei-Yue Wang","doi":"10.1109/ICVES.2007.4456388","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456388","url":null,"abstract":"In this paper, an self-organizing TSK-type fuzzy neural network is proposed for predicting the short-term traffic flow. The proposed fuzzy neural network is adaptively organized from the collected short-term traffic flow data. The whole process is divided into two stage, i.e., structure identification and parameter learning. In structure identification, the mean shift clustering algorithm performs the whole traffic flow data set in order to generate the initial structure and mean firing strength method is used to prune the redundant fuzzy neurons. After the structure identification is finished, the chaotic parameter PSO is adopted to perform the parameter learning. Then the trained fuzzy neural network is employed the collected short- term traffic flow test set and the prediction result verifies that the self-organizing TSK-type fuzzy neural network has higher prediction accuracy than some traditional methods.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127160145","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456377
C. Blanc, P. Checchin, S. Gidel, L. Trassoudaine
This paper deals with the assessment of centralized fusion for two dissimilar sensors for the purpose of tracking road obstacles. The aim of sensor fusion is to produce an improved estimated state of a system from a set of independent data sources. Indeed, for a robust perception of the environment, seen here as obstacles, several sensors should be installed in the equipped vehicle: camera, lidar, radar, etc. In our case, the motivation for this work comes from the need to track road targets with lidar measurements combined with radar ones. Thus, the aim is to combine effectively radar range measurements (i.e. range and range rate) with lidar Cartesian measurements for a "turn" scenario. Centralized fusion, i.e. measurement fusion, for two dissimilar sensors is considered here for assessment which is based on Cramer- Rao Lower Bound (CRLB), the basic tool for investigating estimation performance as it represents a limit of cognizability of the state. In the target tracking area, a recursive formulation of the Posterior Cramer-Rao Lower Bound (PCRLB) is used to analyze performance. Many bound comparisons are made according to the scenarios used and various sensor configurations. Moreover, two algorithms for target motion analysis are developed and compared to the theoretical bounds of performance: the extended Kalman filter and the particle filter.
{"title":"Data fusion performance evaluation for range measurements combined with cartesian ones for road obstacle tracking","authors":"C. Blanc, P. Checchin, S. Gidel, L. Trassoudaine","doi":"10.1109/ICVES.2007.4456377","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456377","url":null,"abstract":"This paper deals with the assessment of centralized fusion for two dissimilar sensors for the purpose of tracking road obstacles. The aim of sensor fusion is to produce an improved estimated state of a system from a set of independent data sources. Indeed, for a robust perception of the environment, seen here as obstacles, several sensors should be installed in the equipped vehicle: camera, lidar, radar, etc. In our case, the motivation for this work comes from the need to track road targets with lidar measurements combined with radar ones. Thus, the aim is to combine effectively radar range measurements (i.e. range and range rate) with lidar Cartesian measurements for a \"turn\" scenario. Centralized fusion, i.e. measurement fusion, for two dissimilar sensors is considered here for assessment which is based on Cramer- Rao Lower Bound (CRLB), the basic tool for investigating estimation performance as it represents a limit of cognizability of the state. In the target tracking area, a recursive formulation of the Posterior Cramer-Rao Lower Bound (PCRLB) is used to analyze performance. Many bound comparisons are made according to the scenarios used and various sensor configurations. Moreover, two algorithms for target motion analysis are developed and compared to the theoretical bounds of performance: the extended Kalman filter and the particle filter.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130729912","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}
Pub Date : 2007-12-01DOI: 10.1109/ICVES.2007.4456373
B. Liu, Fei-Yue Wang, J. Geng, Qingming Yao, Hui Gao, Buqing Zhang
This paper presents a brief review of state-of-the- art research in the field of intelligent spaces. With the increased availability of smart sensors and context-aware appliances that are equipped with embedded computing and communication capability, the intelligent space concept have found widespread applications. First, we introduce the concept, and applications of intelligent spaces. Then we explore research issues on the implementation and design of intelligent spaces, including hardware, networking, system architecture, information understanding and inference, decision making and acting from a system-level perspective. Finally, we present a case study on the intelligent transportation spaces in details.
{"title":"Intelligent spaces: An overview","authors":"B. Liu, Fei-Yue Wang, J. Geng, Qingming Yao, Hui Gao, Buqing Zhang","doi":"10.1109/ICVES.2007.4456373","DOIUrl":"https://doi.org/10.1109/ICVES.2007.4456373","url":null,"abstract":"This paper presents a brief review of state-of-the- art research in the field of intelligent spaces. With the increased availability of smart sensors and context-aware appliances that are equipped with embedded computing and communication capability, the intelligent space concept have found widespread applications. First, we introduce the concept, and applications of intelligent spaces. Then we explore research issues on the implementation and design of intelligent spaces, including hardware, networking, system architecture, information understanding and inference, decision making and acting from a system-level perspective. Finally, we present a case study on the intelligent transportation spaces in details.","PeriodicalId":202772,"journal":{"name":"2007 IEEE International Conference on Vehicular Electronics and Safety","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122092504","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}
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