Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow char- acteristics including safety condition on two-lane freeway is of great significance in planning, design, and manage...Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow char- acteristics including safety condition on two-lane freeway is of great significance in planning, design, and manage- ment of a freeway. Many previous traffic flow models are able to figure out flow characteristics such as speed, den- sity, delay, and so forth. These models, however, have great difficulty in reflecting safety condition of vehicles. Besides, for the cellular automation, one of the most widely used microscopic traffic simulation models, its discreteness in both time and space can possibly cause inaccuracy or big errors in simulation results. In this paper, a micro-simula- tion model of two-lane freeway vehicles is proposed to evaluate characteristics of traffic flow, including safety condition. The model is also discrete in time but continu- ous in space, and it divides drivers into several groups on the basis of their preferences for overtaking, which makes the simulation more aligned with real situations. Partial test is conducted in this study and results of delay, speed, volume, and density indicate the preliminary validity of our model, based on which the proposed safety coefficient evaluates safety condition under different flow levels. It is found that the results of this evaluation coincide with daily experience of drivers, providing ground for effectiveness of the safety coefficient.展开更多
The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,t...The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,two network structure indicators are proposed.Firstly,according to the obvious defects lying in the traditional no-linear coefficient,the realistic no-linear coefficient γRNL,a modified no-linear coefficient indicator,is put forward,which takes into account the effects of barriers in a city.Secondly,to cover the gap of an indicator which can reflect the coverage homogeneity of a transit network,the length dimension LDis proposed on the basis of Fractal Theory.Finally,a case study is applied to verify the validity and practicability of the two indicators in problem diagnosis using regression analysis.The results validate that γRNLcan evaluate the detour of bus lines more reasonably than the previous no-linear coefficient because it reflects the layout of bus lines,and LDcan represent the rate of change of the network density,adding a new member to the scheme of network structure indicators for public transit.展开更多
Accurate traffic state estimations(TSEs)within road networks are crucial for enhancing intelligent transportation systems and developing effective traffic management strategies.Traditional TSE methods often assume hom...Accurate traffic state estimations(TSEs)within road networks are crucial for enhancing intelligent transportation systems and developing effective traffic management strategies.Traditional TSE methods often assume homogeneous traffic,where all vehicles are considered identical,which does not accurately reflect the complexities of real traffic conditions that often exhibit heterogeneous characteristics.In this study,we address the limitations of conventional models by introducing a novel TSE model designed for precise estimations of heterogeneous traffic flows.We develop a comprehensive traffic feature index system tailored for heterogeneous traffic that includes four elements:basic traffic parameters,heterogeneous vehicle speeds,heterogeneous vehicle flows,and mixed flow rates.This system aids in capturing the unique traffic characteristics of different vehicle types.Our proposed high-dimensional fuzzy TSE model,termed HiF-TSE,integrates three main processes:feature selection,which eliminates redundant traffic features using Spearman correlation coefficients;dimension reduction,which utilizes the T-distributed stochastic neighbor embedding machine learning algorithm to reduce high-dimensional traffic feature data;and FCM clustering,which applies the fuzzy C-means algorithm to classify the simplified data into distinct clusters.The HiF-TSE model significantly reduces computational demands and enhances efficiency in TSE processing.We validate our model through a real-world case study,demonstrating its ability to adapt to variations in vehicle type compositions within heterogeneous traffic and accurately represent the actual traffic state.展开更多
We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy fli...We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy flight based pigeon inspired optimization(LFPIO).First,we propose a non-singular fast terminal sliding mode observer(NFTSMO)to estimate the influence of a disturbance,and prove that the observer converges in fixed time using a Lyapunov function.Second,we design an obstacle avoidance strategy based on topology reconstruction,by which the UAV can save energy and safely pass obstacles.Third,we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors.Further,the cost function of each UAV is designed,by which the UAV formation problem is transformed into a game problem.Finally,we develop LFPIO and use it to solve the Nash equilibrium.Numerical simulations are conducted,and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.展开更多
文摘Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow char- acteristics including safety condition on two-lane freeway is of great significance in planning, design, and manage- ment of a freeway. Many previous traffic flow models are able to figure out flow characteristics such as speed, den- sity, delay, and so forth. These models, however, have great difficulty in reflecting safety condition of vehicles. Besides, for the cellular automation, one of the most widely used microscopic traffic simulation models, its discreteness in both time and space can possibly cause inaccuracy or big errors in simulation results. In this paper, a micro-simula- tion model of two-lane freeway vehicles is proposed to evaluate characteristics of traffic flow, including safety condition. The model is also discrete in time but continu- ous in space, and it divides drivers into several groups on the basis of their preferences for overtaking, which makes the simulation more aligned with real situations. Partial test is conducted in this study and results of delay, speed, volume, and density indicate the preliminary validity of our model, based on which the proposed safety coefficient evaluates safety condition under different flow levels. It is found that the results of this evaluation coincide with daily experience of drivers, providing ground for effectiveness of the safety coefficient.
基金Sponsored by the National High Technology Research and Development Program of China(Grant No.214AA110303)
文摘The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,two network structure indicators are proposed.Firstly,according to the obvious defects lying in the traditional no-linear coefficient,the realistic no-linear coefficient γRNL,a modified no-linear coefficient indicator,is put forward,which takes into account the effects of barriers in a city.Secondly,to cover the gap of an indicator which can reflect the coverage homogeneity of a transit network,the length dimension LDis proposed on the basis of Fractal Theory.Finally,a case study is applied to verify the validity and practicability of the two indicators in problem diagnosis using regression analysis.The results validate that γRNLcan evaluate the detour of bus lines more reasonably than the previous no-linear coefficient because it reflects the layout of bus lines,and LDcan represent the rate of change of the network density,adding a new member to the scheme of network structure indicators for public transit.
基金supported by the National Key R&D Program of China(Grant No.2023YFB4302702)the Fundamental Research Funds for the Central Universities(Grant No.2023JKF02ZK08).
文摘Accurate traffic state estimations(TSEs)within road networks are crucial for enhancing intelligent transportation systems and developing effective traffic management strategies.Traditional TSE methods often assume homogeneous traffic,where all vehicles are considered identical,which does not accurately reflect the complexities of real traffic conditions that often exhibit heterogeneous characteristics.In this study,we address the limitations of conventional models by introducing a novel TSE model designed for precise estimations of heterogeneous traffic flows.We develop a comprehensive traffic feature index system tailored for heterogeneous traffic that includes four elements:basic traffic parameters,heterogeneous vehicle speeds,heterogeneous vehicle flows,and mixed flow rates.This system aids in capturing the unique traffic characteristics of different vehicle types.Our proposed high-dimensional fuzzy TSE model,termed HiF-TSE,integrates three main processes:feature selection,which eliminates redundant traffic features using Spearman correlation coefficients;dimension reduction,which utilizes the T-distributed stochastic neighbor embedding machine learning algorithm to reduce high-dimensional traffic feature data;and FCM clustering,which applies the fuzzy C-means algorithm to classify the simplified data into distinct clusters.The HiF-TSE model significantly reduces computational demands and enhances efficiency in TSE processing.We validate our model through a real-world case study,demonstrating its ability to adapt to variations in vehicle type compositions within heterogeneous traffic and accurately represent the actual traffic state.
基金Project supported by the Science and Technology Innovation 2030 Key Project of“New Generation Artificial Intelligence,”China(No.2018AAA0100803)the National Natural Science Foundation of China(Nos.T2121003,U1913602,U20B2071,91948204,and U19B2033)。
文摘We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy flight based pigeon inspired optimization(LFPIO).First,we propose a non-singular fast terminal sliding mode observer(NFTSMO)to estimate the influence of a disturbance,and prove that the observer converges in fixed time using a Lyapunov function.Second,we design an obstacle avoidance strategy based on topology reconstruction,by which the UAV can save energy and safely pass obstacles.Third,we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors.Further,the cost function of each UAV is designed,by which the UAV formation problem is transformed into a game problem.Finally,we develop LFPIO and use it to solve the Nash equilibrium.Numerical simulations are conducted,and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.
