Pub Date : 2021-01-01DOI: 10.1504/ijvics.2021.10043132
P. Nand, Shahjahan Ali, S. Tiwari
{"title":"Innovative approach to prevent wormhole attack on reactive routing of vehicular ad-hoc network by using clustering and digital signatures","authors":"P. Nand, Shahjahan Ali, S. Tiwari","doi":"10.1504/ijvics.2021.10043132","DOIUrl":"https://doi.org/10.1504/ijvics.2021.10043132","url":null,"abstract":"","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66683975","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030796
Hongying Mi, Ying Zheng
Because the existing early warning methods do not assign weights, it is easy to cause collisions in the vehicle driving process, and the prediction accuracy is low. Therefore, this paper proposes a binocular vision vehicle environment collision early warning method based on machine learning. The comparison of experiments on high-speed sections shows that the number of vehicle collisions decreases by about six times when using the proposed method in this paper is used, which is significantly less than that of the existing methods. Moreover, the distance error between the target vehicle and the running vehicle measured by the method in this paper is small, and the error rate is between 0.005 and 0.041. Therefore, it can accurately warn of the occurrence of vehicle collisions, and its application advantages are obvious.
{"title":"Binocular vision vehicle environment collision early warning method based on machine learning","authors":"Hongying Mi, Ying Zheng","doi":"10.1504/ijvics.2020.10030796","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030796","url":null,"abstract":"Because the existing early warning methods do not assign weights, it is easy to cause collisions in the vehicle driving process, and the prediction accuracy is low. Therefore, this paper proposes a binocular vision vehicle environment collision early warning method based on machine learning. The comparison of experiments on high-speed sections shows that the number of vehicle collisions decreases by about six times when using the proposed method in this paper is used, which is significantly less than that of the existing methods. Moreover, the distance error between the target vehicle and the running vehicle measured by the method in this paper is small, and the error rate is between 0.005 and 0.041. Therefore, it can accurately warn of the occurrence of vehicle collisions, and its application advantages are obvious.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43330464","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030792
Daqin Wu, Haiyan Hu
Aiming at the problems of low recognition accuracy and long time-consuming in current automobile recognition research, an automobile image recognition method based on monocular vision and environmental perception is proposed. A hybrid filter is composed of median filter and mean filter to suppress image noise and preserve the edge features of the signal. The non-target background is removed by environmental perception, and the target area is obtained with the geometric information in the vehicle shadow as the constraint condition. According to the result of image processing and the determination of target area, HAAR-like feature vectors of targets are extracted and dimensionality reduction is processed. The training classifier is constructed by using the obtained eigenvectors to recognise the current frame vehicles. The experimental results show that the method has the advantages of high recognition accuracy and short time-consuming.
{"title":"Automatic recognition of vehicle image based on monocular vision and environmental perception","authors":"Daqin Wu, Haiyan Hu","doi":"10.1504/ijvics.2020.10030792","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030792","url":null,"abstract":"Aiming at the problems of low recognition accuracy and long time-consuming in current automobile recognition research, an automobile image recognition method based on monocular vision and environmental perception is proposed. A hybrid filter is composed of median filter and mean filter to suppress image noise and preserve the edge features of the signal. The non-target background is removed by environmental perception, and the target area is obtained with the geometric information in the vehicle shadow as the constraint condition. According to the result of image processing and the determination of target area, HAAR-like feature vectors of targets are extracted and dimensionality reduction is processed. The training classifier is constructed by using the obtained eigenvectors to recognise the current frame vehicles. The experimental results show that the method has the advantages of high recognition accuracy and short time-consuming.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43974707","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030790
Minglei Song, Rongrong Li, Binghua Wu, MinWoo Lee
In order to solve the problems of pollution and traffic safety caused by vehicle traffic congestion, this paper establishes an analysis model of urban vehicle traffic congestion characteristics based on vehicle network theory. Through the application of vehicular network, the extended mobility model of vehicular network is established, and the extended motion model of vehicular network is simulated with simulation tools and middleware tools to obtain the trajectory data of urban traffic vehicles. Based on the trajectory data, the survival analysis of urban vehicle traffic congestion is carried out. Kaplan-Meyer non-parametric regression model was used to estimate the duration of urban vehicle traffic congestion, and its distribution characteristics were quantitatively analysed. The experimental results show that the traffic congestion characteristics of urban vehicles are significantly different under different influencing factors, and the error of the trajectory data of urban traffic vehicles obtained by the proposed model is less than 1%.
{"title":"Modelling and analysis of urban vehicle traffic congestion characteristics based on vehicle-borne network theory","authors":"Minglei Song, Rongrong Li, Binghua Wu, MinWoo Lee","doi":"10.1504/ijvics.2020.10030790","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030790","url":null,"abstract":"In order to solve the problems of pollution and traffic safety caused by vehicle traffic congestion, this paper establishes an analysis model of urban vehicle traffic congestion characteristics based on vehicle network theory. Through the application of vehicular network, the extended mobility model of vehicular network is established, and the extended motion model of vehicular network is simulated with simulation tools and middleware tools to obtain the trajectory data of urban traffic vehicles. Based on the trajectory data, the survival analysis of urban vehicle traffic congestion is carried out. Kaplan-Meyer non-parametric regression model was used to estimate the duration of urban vehicle traffic congestion, and its distribution characteristics were quantitatively analysed. The experimental results show that the traffic congestion characteristics of urban vehicles are significantly different under different influencing factors, and the error of the trajectory data of urban traffic vehicles obtained by the proposed model is less than 1%.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49195747","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030794
X. Tian
In order to solve the problems of poor signal anti-interference ability, high error rate and low network coverage in traditional vehicle communication network and improve the communication quality of vehicle communication network, an anti-interference method of vehicle communication network based on Internet of Vehicle (IoV) technology is proposed. The maximum cellular rate resource reuse algorithm (MCRRA) is used to optimise the link resources of vehicle communication network, so as to realise the optimal allocation of vehicle communication network resources. Then, the wavelet denoising method is used to filter the signal noise after resource allocation in vehicle communication network. Finally, the improved threshold function method of wavelet transform is used to compensate the pseudo-Gibbs phenomenon and signal loss in vehicle communication network. Experiments show that this method can effectively suppress the interference of vehicle communication network. The error rate of the vehicle communication network using this method is only 10%, and the coverage rate is as high as 98.7%.
{"title":"Anti-jamming method for vehicle communication network based on internet of vehicles technology","authors":"X. Tian","doi":"10.1504/ijvics.2020.10030794","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030794","url":null,"abstract":"In order to solve the problems of poor signal anti-interference ability, high error rate and low network coverage in traditional vehicle communication network and improve the communication quality of vehicle communication network, an anti-interference method of vehicle communication network based on Internet of Vehicle (IoV) technology is proposed. The maximum cellular rate resource reuse algorithm (MCRRA) is used to optimise the link resources of vehicle communication network, so as to realise the optimal allocation of vehicle communication network resources. Then, the wavelet denoising method is used to filter the signal noise after resource allocation in vehicle communication network. Finally, the improved threshold function method of wavelet transform is used to compensate the pseudo-Gibbs phenomenon and signal loss in vehicle communication network. Experiments show that this method can effectively suppress the interference of vehicle communication network. The error rate of the vehicle communication network using this method is only 10%, and the coverage rate is as high as 98.7%.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46842594","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030802
Dahui Li, Jianzhao Cui, Qi Fan
In order to solve the problems of low accuracy and long delay in traditional data monitoring methods of vehicle-mounted traffic network, an anomaly monitoring method based on Support Vector Machine (SVM) is proposed. The data of acceleration sensor, gyroscope and magnetic field sensor are collected and filtered. The online analysis method of driving behaviour based on support vector machine is introduced to identify various driving behaviours. By simulating the normal behaviour and abnormal behaviour based on HTTP protocol, the obtained data are analysed to construct the HTTP protocol behaviour. The neural network based on Radial Basis Function (RBF) was trained to monitor the abnormal data in driving behaviours by simulating the behaviour records generated by experiments for many times. The experimental results show that the proposed method can accurately monitor the abnormal data in driving behaviour, and the delay is short, which provides a favourable basis for relevant studies.
{"title":"Research on abnormal monitoring of vehicle traffic network data based on support vector machine","authors":"Dahui Li, Jianzhao Cui, Qi Fan","doi":"10.1504/ijvics.2020.10030802","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030802","url":null,"abstract":"In order to solve the problems of low accuracy and long delay in traditional data monitoring methods of vehicle-mounted traffic network, an anomaly monitoring method based on Support Vector Machine (SVM) is proposed. The data of acceleration sensor, gyroscope and magnetic field sensor are collected and filtered. The online analysis method of driving behaviour based on support vector machine is introduced to identify various driving behaviours. By simulating the normal behaviour and abnormal behaviour based on HTTP protocol, the obtained data are analysed to construct the HTTP protocol behaviour. The neural network based on Radial Basis Function (RBF) was trained to monitor the abnormal data in driving behaviours by simulating the behaviour records generated by experiments for many times. The experimental results show that the proposed method can accurately monitor the abnormal data in driving behaviour, and the delay is short, which provides a favourable basis for relevant studies.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49272594","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030791
Chunmei Wang
In order to overcome the problem of poor application of traditional urban intelligent traffic signal self-organisation control, a method of urban intelligent traffic signal self-organisation control based on vehicle network is proposed. A signal self-organising control system based on on-demand distribution is constructed, in which the fixed unit module RSU receives vehicle traffic data through sensors. RDU is used to monitor vehicle data and construct signal adaptive control strategy, which can reduce vehicle waiting time and realise urban intelligent traffic signal self-organising control. Simulation results show that the average number of stops at the intersection at the same time point is less than 0.3. The average stopping time is 8.728s, which is obviously lower than other methods. The average pass rate at the intersection is 98.65%, which is obviously higher than other methods and feasible.
{"title":"Research on self-organising control method of urban intelligent traffic signal based on vehicle networking","authors":"Chunmei Wang","doi":"10.1504/ijvics.2020.10030791","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030791","url":null,"abstract":"In order to overcome the problem of poor application of traditional urban intelligent traffic signal self-organisation control, a method of urban intelligent traffic signal self-organisation control based on vehicle network is proposed. A signal self-organising control system based on on-demand distribution is constructed, in which the fixed unit module RSU receives vehicle traffic data through sensors. RDU is used to monitor vehicle data and construct signal adaptive control strategy, which can reduce vehicle waiting time and realise urban intelligent traffic signal self-organising control. Simulation results show that the average number of stops at the intersection at the same time point is less than 0.3. The average stopping time is 8.728s, which is obviously lower than other methods. The average pass rate at the intersection is 98.65%, which is obviously higher than other methods and feasible.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44521096","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030797
C. Liu
In order to solve the problem of inaccurate detection of road space occupation, an intelligent traffic guidance and display system based on vehicle network is designed. Firstly, the real-time acquisition and prediction of vehicle and path environment data are realised by using navigation information data acquisition module. Secondly, the traffic guidance information is used to publish the model, edit the data, and send the traffic guidance information display module. Then, the set theory method is used to detect the traffic volume of RFID readers set up on the road. Finally, the average space speed, space occupation rate and road delay time are calculated to complete the traffic guidance. The experimental results show that the system can quickly balance the delay in road network and shows powerful guidance display performance with instantaneity larger than 95% and dynamics high 0.97 in ten kinds of traffic congestions in different roads.
{"title":"Design of intelligent traffic guidance display system based on internet of vehicles","authors":"C. Liu","doi":"10.1504/ijvics.2020.10030797","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030797","url":null,"abstract":"In order to solve the problem of inaccurate detection of road space occupation, an intelligent traffic guidance and display system based on vehicle network is designed. Firstly, the real-time acquisition and prediction of vehicle and path environment data are realised by using navigation information data acquisition module. Secondly, the traffic guidance information is used to publish the model, edit the data, and send the traffic guidance information display module. Then, the set theory method is used to detect the traffic volume of RFID readers set up on the road. Finally, the average space speed, space occupation rate and road delay time are calculated to complete the traffic guidance. The experimental results show that the system can quickly balance the delay in road network and shows powerful guidance display performance with instantaneity larger than 95% and dynamics high 0.97 in ten kinds of traffic congestions in different roads.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42484377","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 : 2020-07-27DOI: 10.1504/ijvics.2020.10030793
Min Yang
A vehicle communication signal recognition and compensation system based on vehicle network is proposed to overcome the problems of the traditional vehicle communication signal recognition system, such as poor anti-interference and signal recognition accuracy. The hardware part of the system consists of three modules. The software uses inverse operator and Wiener filter to compensate the vehicle communication signal and improves the precision of signal recognition. The MFCC parameters are extracted as the main parameters of signal recognition, and the distance measurement between the unknown communication signal and each template is obtained by using the non-linear registration mode DTW, so as to realise the optimal registration mode of signal pattern recognition. Experimental results show that the anti-interference performance of the system is about 110 dB, and the recognition rate of different types of signals is more than 85%, which proves that the system has high recognition accuracy and strong anti-interference ability.
{"title":"Design of recognition and compensation system for vehicle communication signal based on vehicle networking","authors":"Min Yang","doi":"10.1504/ijvics.2020.10030793","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10030793","url":null,"abstract":"A vehicle communication signal recognition and compensation system based on vehicle network is proposed to overcome the problems of the traditional vehicle communication signal recognition system, such as poor anti-interference and signal recognition accuracy. The hardware part of the system consists of three modules. The software uses inverse operator and Wiener filter to compensate the vehicle communication signal and improves the precision of signal recognition. The MFCC parameters are extracted as the main parameters of signal recognition, and the distance measurement between the unknown communication signal and each template is obtained by using the non-linear registration mode DTW, so as to realise the optimal registration mode of signal pattern recognition. Experimental results show that the anti-interference performance of the system is about 110 dB, and the recognition rate of different types of signals is more than 85%, which proves that the system has high recognition accuracy and strong anti-interference ability.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45214753","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 : 2020-05-04DOI: 10.1504/ijvics.2020.10029206
Shailendra Mishra, Mayank Singh
M-governance mainly facilitates government to public (G2P) and public to government (P2G) communication for better public service in terms of information transmission and dissemination. This research aims to develop a m-governance framework and architecture for mobile governance to enhance the communication services of the University in the domain of Admission, Affiliation, Curriculum, Examination, Result and General Inquiry. Proposed m-governance framework build-up on the basis of Technology Acceptance Model (TAM) and 15 enabler including perceived ease of use, perceived usefulness, perceived access, interpersonal influence, perceived trustworthiness, perceived mobility, transparency of governance, compatibility, flexibility, perceived security, perceived enjoyment, network provider service, completeness of service, location influence in the service and emergency management. Proposed application architecture for mobile governance is beneficial because it allows administrators of the affiliated colleges to use the mobile device of their choice but Android, and it offers a simple solution. The analysis of the data reveals that the administrators as well as academician are inclined to have mobile governance for enhancing the communication services of the higher educational system.
{"title":"A conceptual framework and architecture for m-governance","authors":"Shailendra Mishra, Mayank Singh","doi":"10.1504/ijvics.2020.10029206","DOIUrl":"https://doi.org/10.1504/ijvics.2020.10029206","url":null,"abstract":"M-governance mainly facilitates government to public (G2P) and public to government (P2G) communication for better public service in terms of information transmission and dissemination. This research aims to develop a m-governance framework and architecture for mobile governance to enhance the communication services of the University in the domain of Admission, Affiliation, Curriculum, Examination, Result and General Inquiry. Proposed m-governance framework build-up on the basis of Technology Acceptance Model (TAM) and 15 enabler including perceived ease of use, perceived usefulness, perceived access, interpersonal influence, perceived trustworthiness, perceived mobility, transparency of governance, compatibility, flexibility, perceived security, perceived enjoyment, network provider service, completeness of service, location influence in the service and emergency management. Proposed application architecture for mobile governance is beneficial because it allows administrators of the affiliated colleges to use the mobile device of their choice but Android, and it offers a simple solution. The analysis of the data reveals that the administrators as well as academician are inclined to have mobile governance for enhancing the communication services of the higher educational system.","PeriodicalId":39333,"journal":{"name":"International Journal of Vehicle Information and Communication Systems","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45104410","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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