Travel time and delay are among the most important measures for gauging a transportation system’s performance. To address the growing problem of congestion in the US, transportation planning legislation mandated the ...Travel time and delay are among the most important measures for gauging a transportation system’s performance. To address the growing problem of congestion in the US, transportation planning legislation mandated the monitoring and analysis of system performance and produced a renewed interest in travel time and delay studies. The use of traditional sensors installed on major roads (e.g. inductive loops) for collecting data is necessary but not sufficient because of their limited coverage and expensive costs for setting up and maintaining the required infrastructure. The GPS-based techniques employed by the University of Delaware have evolved into an automated system, which provides more realistic experience of a traffic flow throughout the road links. However, human error and the weaknesses of using GPS devices in urban settings still have the potential to create inaccuracies. By simultaneously collecting data using three different techniques, the accuracy of the GPS positioning data and the resulting travel time and delay values could be objectively compared for automation and statistically compared for accuracy. It was found that the new technique provided the greatest automation requiring minimal attention of the data collectors and automatically processing the data sets. The data samples were statistically analyzed by using a combination of parametric and nonparametric statistical tests. This analysis greatly favored the GeoStats GPS method over the rest methods.展开更多
The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance,so as to predict the travel time of the road sections.However,in the case of traffic congestion,t...The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance,so as to predict the travel time of the road sections.However,in the case of traffic congestion,the accuracy of its prediction time is low.After empirical analysis,this paper establishes a multi-factor synthesis by studying 7 factors:traffic flow,number of stops,traffic light duration,road network density,average speed,road area,and number of intersections the prediction function achieves the purpose of accurately predicting the transit time of congested road sections.The gray correlation coefficients of the seven factors obtained from the gray correlation analysis are:0.9827,0.9679,0.6747,0.8030,0.9445,0.8759,0.4328.The correlation coefficients of traffic volume,number of stops,average speed,and road congestion delay time were all about 95%,which were the main influencing factors of the study.The prediction needs to be based on functions.This paper fits the main influencing factors to the delay time of congested roads.It is found that the delay time varies parabolically with the traffic flow and the number of stops,and linearly with the average speed.Because the three impact factors have different weights on the delay time of congested roads,demand takes the weight of each factor.Therefore,the gray correlation coefficients occupied by the main influencing factors are normalized to obtain the weights of three of 0.340,0.334,and 0.326.The weighted fitting function is subjected to nonlinear summation processing to obtain a multi-factor comprehensive prediction function.By comparing the original data with the fitting data and calculating the accuracy of the fitting function,it is found that the accuracy of each fitting function is close to 0,the residual error,the relative error is small,and the accuracy is high.展开更多
In this paper, the stabilization problem for a class of networked control systems （NCSs） with data packet dropouts and transmission time delays is considered, where the delays are time-varying and uncertain, the dat...In this paper, the stabilization problem for a class of networked control systems （NCSs） with data packet dropouts and transmission time delays is considered, where the delays are time-varying and uncertain, the data packet dropout is modeled as a two-state Markov chain. To compensate the lost packet, a data packet dropout compensator is established. Thus a more realistic model for such NCSs is presented. Sufficient conditions for the stabilization of the new resulting system are derived in the form of linear matrix inequalities （LMIs）. Numerical example illustrates the solvability and effectiveness of the results.展开更多
The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks （WSNs）. Therefore, introducing mobile collectors to collect data instead of nmlti-hop...The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks （WSNs）. Therefore, introducing mobile collectors to collect data instead of nmlti-hop data relay is essential. However, for rmny proposed data gathering ap-proaches, long data deNNy is the train problenm. Hence, the problem of how to decrease the energy consumption and the data deNNy needs to be solved. In this paper, a low deNNy data collection mechanism using multiple mobile collectors is pro- posed. First, a self-organization clustering algorithm is designed. Second, sensor nodes are organized into three-level clusters. Then a collection strategy based on the hierarchical structure is proposed, which includes two rules to dispatch mobile collec- tors rationally. Simulation results show that the proposed mechanism is superior to other existing approaches in terms of the reduction in energy ex-penditure and the decrease in data deNNy.展开更多
This paper presents an expression of the semantic proximity. Based on the temporal data model, a method of the temporal approximation is given. Using these concepts, this paper provides an evaluated method of fuzzy an...This paper presents an expression of the semantic proximity. Based on the temporal data model, a method of the temporal approximation is given. Using these concepts, this paper provides an evaluated method of fuzzy and dynamic association degree with delayed time and a superposition method of association degrees. Particularly, by means of the fuzzy and dynamic association degree, the connection between the weather data of two regions can be discovered.展开更多
The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g.,time delays and data loss)in this paper.Firstly...The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g.,time delays and data loss)in this paper.Firstly,the couple-group consensus tracking control is analyzed theoretically,the communication constraints are compensated by the prediction method,and the factor of leaders is introduced to make the system not lose generality.Secondly,the necessary and sufficient condition is given to ensure the stability of the system and achieve the couple-group consensus tracking control,and relax the topology constraint of in-degrees balance by cooperative-competitive interactions.In addition,the result of couple groups is extended to multiple groups based on the predictive control protocol.Numerical simulations with Matlab show that the proposed networked predictive control can effectively overcome the network constraints,the dynamic performance and control effect are better than the general control without the prediction.展开更多
文摘Travel time and delay are among the most important measures for gauging a transportation system’s performance. To address the growing problem of congestion in the US, transportation planning legislation mandated the monitoring and analysis of system performance and produced a renewed interest in travel time and delay studies. The use of traditional sensors installed on major roads (e.g. inductive loops) for collecting data is necessary but not sufficient because of their limited coverage and expensive costs for setting up and maintaining the required infrastructure. The GPS-based techniques employed by the University of Delaware have evolved into an automated system, which provides more realistic experience of a traffic flow throughout the road links. However, human error and the weaknesses of using GPS devices in urban settings still have the potential to create inaccuracies. By simultaneously collecting data using three different techniques, the accuracy of the GPS positioning data and the resulting travel time and delay values could be objectively compared for automation and statistically compared for accuracy. It was found that the new technique provided the greatest automation requiring minimal attention of the data collectors and automatically processing the data sets. The data samples were statistically analyzed by using a combination of parametric and nonparametric statistical tests. This analysis greatly favored the GeoStats GPS method over the rest methods.
文摘The navigation software uses the positioning system to determine the traffic conditions of the road sections in advance,so as to predict the travel time of the road sections.However,in the case of traffic congestion,the accuracy of its prediction time is low.After empirical analysis,this paper establishes a multi-factor synthesis by studying 7 factors:traffic flow,number of stops,traffic light duration,road network density,average speed,road area,and number of intersections the prediction function achieves the purpose of accurately predicting the transit time of congested road sections.The gray correlation coefficients of the seven factors obtained from the gray correlation analysis are:0.9827,0.9679,0.6747,0.8030,0.9445,0.8759,0.4328.The correlation coefficients of traffic volume,number of stops,average speed,and road congestion delay time were all about 95%,which were the main influencing factors of the study.The prediction needs to be based on functions.This paper fits the main influencing factors to the delay time of congested roads.It is found that the delay time varies parabolically with the traffic flow and the number of stops,and linearly with the average speed.Because the three impact factors have different weights on the delay time of congested roads,demand takes the weight of each factor.Therefore,the gray correlation coefficients occupied by the main influencing factors are normalized to obtain the weights of three of 0.340,0.334,and 0.326.The weighted fitting function is subjected to nonlinear summation processing to obtain a multi-factor comprehensive prediction function.By comparing the original data with the fitting data and calculating the accuracy of the fitting function,it is found that the accuracy of each fitting function is close to 0,the residual error,the relative error is small,and the accuracy is high.
基金The work was supported in part by the National Natural Science Foundation of China (No. 60174010, 60404022)the Key Scientific ResearchProject of the Education Ministry (No. 204014)
文摘In this paper, the stabilization problem for a class of networked control systems （NCSs） with data packet dropouts and transmission time delays is considered, where the delays are time-varying and uncertain, the data packet dropout is modeled as a two-state Markov chain. To compensate the lost packet, a data packet dropout compensator is established. Thus a more realistic model for such NCSs is presented. Sufficient conditions for the stabilization of the new resulting system are derived in the form of linear matrix inequalities （LMIs）. Numerical example illustrates the solvability and effectiveness of the results.
基金This paper was supported by the National Natural Science Foundation of China under Ca-ants No.60835001, No. 61104068 the Natural Science Foundation of Jiangsu Province, China un- der Crant No.BK2010200.
文摘The majority of the energy consumption by the sensors is the energy requirement for data transmission in Wireless Sensor Networks （WSNs）. Therefore, introducing mobile collectors to collect data instead of nmlti-hop data relay is essential. However, for rmny proposed data gathering ap-proaches, long data deNNy is the train problenm. Hence, the problem of how to decrease the energy consumption and the data deNNy needs to be solved. In this paper, a low deNNy data collection mechanism using multiple mobile collectors is pro- posed. First, a self-organization clustering algorithm is designed. Second, sensor nodes are organized into three-level clusters. Then a collection strategy based on the hierarchical structure is proposed, which includes two rules to dispatch mobile collec- tors rationally. Simulation results show that the proposed mechanism is superior to other existing approaches in terms of the reduction in energy ex-penditure and the decrease in data deNNy.
基金Project supported by the National Natural Science Foundation of China (No.69763003).
文摘This paper presents an expression of the semantic proximity. Based on the temporal data model, a method of the temporal approximation is given. Using these concepts, this paper provides an evaluated method of fuzzy and dynamic association degree with delayed time and a superposition method of association degrees. Particularly, by means of the fuzzy and dynamic association degree, the connection between the weather data of two regions can be discovered.
基金supported by Natural Science Foundation of Heilongjiang Province of China under Grant No.LH2022F033the National Natural Science Foundation of China under Grant Nos.61903104,61773144 and 12071102Heilongjiang Postdoctoral Scientific Research Developmental Fund under Grant Nos.LBHQ20099 and LBH-Q20168。
文摘The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g.,time delays and data loss)in this paper.Firstly,the couple-group consensus tracking control is analyzed theoretically,the communication constraints are compensated by the prediction method,and the factor of leaders is introduced to make the system not lose generality.Secondly,the necessary and sufficient condition is given to ensure the stability of the system and achieve the couple-group consensus tracking control,and relax the topology constraint of in-degrees balance by cooperative-competitive interactions.In addition,the result of couple groups is extended to multiple groups based on the predictive control protocol.Numerical simulations with Matlab show that the proposed networked predictive control can effectively overcome the network constraints,the dynamic performance and control effect are better than the general control without the prediction.
