In this paper, we discuss the mechanisms for discretionary lane-changing behavior in traffic flow. NGSIM video data are used to check the validity of different lane-changing rules, and 373 lane changes at 4 locations in US-101 highway are analyzed. We find that the classical lane-changing rules of rule-based model cannot explain many cases in the empirical dataset. Therefore, we propose one new decision rule, comparing the position after a time horizon of several seconds without a lane-change. This rule can be described as “to have a further position within 9 seconds”. The tests on NGSIM data show that this rule can explain most (76%) of the lane-changing cases. Besides, some data when lane changes do not occur are also studied. We find that most (81%) of non-lane-changing vehicles do not fulfill the new rule. Thus, it can be considered as one sufficient and necessary condition for discretionary lane-changing.@en

The effect of shot peen forming on the mechanical behavior of fiber metal laminates (FMLs) based on aluminium-lithium alloy was investigated to reveal the strengthening mechanism and to dispel the suspicion that shot peen forming may result in the performance deterioration of FMLs. The interlaminar, static strength and fatigue properties of shot peened FMLs were investigated. The residual stress characteristics of the shot peened FMLs was also involved with finite element analysis to help understanding the unique mechanical behavior. The results indicated that shot peening caused non-negligible work hardening in external metal layers, which increased the tensile strength of the laminates. But the work hardening did not deteriorate the elongations of FMLs since the failure still dominated by the limitation of fiber failure strain. Moreover, two yield stages were observed in the tensile tests of shot peened FMLs owing to the great difference in stress states between external and internal metal layers. The compressive stress introduced by shot peening effectively improved the FCG properties of FMLs. All metal layers possessed similar crack propagation rates despite that the stress difference was up to 300 MPa, which indicated that the fiber bridging effect still dominated the FCG of FMLs.@en

Variable speed limits (VSLs) are a common traffic control measure to resolve freeway jam waves. State-of-the-art model predictive control (MPC) approaches of VSLs are developed based on Eulerian Lighthill-Whitham and Richards (LWR) models, where the decision variables are flows between road segments. It is difficult to implement constraints on speeds that are necessary in typical real-world speed limit systems, because converting flow to speed results in nonlinear and non-convex optimization formulations. In this paper, we develop a new MPC of VSLs based on a discrete Lagrangian LWR model, in which the decision variables are average speeds of vehicle groups. This allows formulating speed constraints as control constraints rather than state constraints in the MPC problem. The optimization of vehicle groups speeds is formulated as a linear programming problem which can be solved efficiently. We further integrate the presented MPC to a hierarchical VSL control framework leveraging connected vehicles. The presented MPC decides the optimal target speed of each vehicle group led by a connected automated vehicle (CAV) at the upper macroscopic level with a prediction horizon of 20 min. At the lower microscopic level, CAVs randomly distributed in mixed traffic are regarded as actuators of the upper layer. Microscopic CAV accelerations are optimized in a short horizon of the order 5–10 s so that the human-driven vehicles following them reach the target speed from the upper layer in an efficient and smooth manner. The presented MPC and the hierarchical control approach are tested in microscopic simulation environments. Simulation results show that (i) the presented MPC resolves freeway jam waves efficiently with reasonable safety constraints implemented, and (ii) the presented hierarchical control approach can effectively resolve jam waves in a single-lane freeway, even though the penetration rate of CAVs is as low as 5%.@en

Variable speed limits (VSLs) are a common traffic control measure to resolve freeway jam waves. State-of-the-art model predictive control (MPC) approaches of VSLs are developed based on Eulerian Lighthill-Whitham and Richards (LWR) models, where the decision variables are flows between road segments. It is difficult to implement constraints on speeds that are necessary in typical real-world speed limit systems, because converting flow to speed results in nonlinear and non-convex optimization formulations. In this paper, we develop a new MPC of VSLs based on a discrete Lagrangian LWR model, in which the decision variables are average speeds of vehicle groups. This allows formulating speed constraints as control constraints rather than state constraints in the MPC problem. The optimization of vehicle groups speeds is formulated as a linear programming problem which can be solved efficiently. We further integrate the presented MPC to a hierarchical VSL control framework leveraging connected vehicles. The presented MPC decides the optimal target speed of each vehicle group led by a connected automated vehicle (CAV) at the upper macroscopic level with a prediction horizon of 20 min. At the lower microscopic level, CAVs randomly distributed in mixed traffic are regarded as actuators of the upper layer. Microscopic CAV accelerations are optimized in a short horizon of the order 5–10 s so that the human-driven vehicles following them reach the target speed from the upper layer in an efficient and smooth manner. The presented MPC and the hierarchical control approach are tested in microscopic simulation environments. Simulation results show that (i) the presented MPC resolves freeway jam waves efficiently with reasonable safety constraints implemented, and (ii) the presented hierarchical control approach can effectively resolve jam waves in a single-lane freeway, even though the penetration rate of CAVs is as low as 5%.@en

Variable speed limits (VSLs) are a common traffic control measure to resolve freeway jam waves. State-of-the-art model predictive control (MPC) approaches of VSLs are developed based on Eulerian Lighthill-Whitham and Richards (LWR) models, where the decision variables are flows between road segments. It is difficult to implement constraints on speeds that are necessary in typical real-world speed limit systems, because converting flow to speed results in nonlinear and non-convex optimization formulations. In this paper, we develop a new MPC of VSLs based on a discrete Lagrangian LWR model, in which the decision variables are average speeds of vehicle groups. This allows formulating speed constraints as control constraints rather than state constraints in the MPC problem. The optimization of vehicle groups speeds is formulated as a linear programming problem which can be solved efficiently. We further integrate the presented MPC to a hierarchical VSL control framework leveraging connected vehicles. The presented MPC decides the optimal target speed of each vehicle group led by a connected automated vehicle (CAV) at the upper macroscopic level with a prediction horizon of 20 min. At the lower microscopic level, CAVs randomly distributed in mixed traffic are regarded as actuators of the upper layer. Microscopic CAV accelerations are optimized in a short horizon of the order 5–10 s so that the human-driven vehicles following them reach the target speed from the upper layer in an efficient and smooth manner. The presented MPC and the hierarchical control approach are tested in microscopic simulation environments. Simulation results show that (i) the presented MPC resolves freeway jam waves efficiently with reasonable safety constraints implemented, and (ii) the presented hierarchical control approach can effectively resolve jam waves in a single-lane freeway, even though the penetration rate of CAVs is as low as 5%.@en

Variable speed limits (VSLs) are a common traffic control measure to resolve freeway jam waves. State-of-the-art model predictive control (MPC) approaches of VSLs are developed based on Eulerian Lighthill-Whitham and Richards (LWR) models, where the decision variables are flows between road segments. It is difficult to implement constraints on speeds that are necessary in typical real-world speed limit systems, because converting flow to speed results in nonlinear and non-convex optimization formulations. In this paper, we develop a new MPC of VSLs based on a discrete Lagrangian LWR model, in which the decision variables are average speeds of vehicle groups. This allows formulating speed constraints as control constraints rather than state constraints in the MPC problem. The optimization of vehicle groups speeds is formulated as a linear programming problem which can be solved efficiently. We further integrate the presented MPC to a hierarchical VSL control framework leveraging connected vehicles. The presented MPC decides the optimal target speed of each vehicle group led by a connected automated vehicle (CAV) at the upper macroscopic level with a prediction horizon of 20 min. At the lower microscopic level, CAVs randomly distributed in mixed traffic are regarded as actuators of the upper layer. Microscopic CAV accelerations are optimized in a short horizon of the order 5–10 s so that the human-driven vehicles following them reach the target speed from the upper layer in an efficient and smooth manner. The presented MPC and the hierarchical control approach are tested in microscopic simulation environments. Simulation results show that (i) the presented MPC resolves freeway jam waves efficiently with reasonable safety constraints implemented, and (ii) the presented hierarchical control approach can effectively resolve jam waves in a single-lane freeway, even though the penetration rate of CAVs is as low as 5%.@en

Variable speed limits (VSLs) are a common traffic control measure to resolve freeway jam waves. State-of-the-art model predictive control (MPC) approaches of VSLs are developed based on Eulerian Lighthill-Whitham and Richards (LWR) models, where the decision variables are flows between road segments. It is difficult to implement constraints on speeds that are necessary in typical real-world speed limit systems, because converting flow to speed results in nonlinear and non-convex optimization formulations. In this paper, we develop a new MPC of VSLs based on a discrete Lagrangian LWR model, in which the decision variables are average speeds of vehicle groups. This allows formulating speed constraints as control constraints rather than state constraints in the MPC problem. The optimization of vehicle groups speeds is formulated as a linear programming problem which can be solved efficiently. We further integrate the presented MPC to a hierarchical VSL control framework leveraging connected vehicles. The presented MPC decides the optimal target speed of each vehicle group led by a connected automated vehicle (CAV) at the upper macroscopic level with a prediction horizon of 20 min. At the lower microscopic level, CAVs randomly distributed in mixed traffic are regarded as actuators of the upper layer. Microscopic CAV accelerations are optimized in a short horizon of the order 5–10 s so that the human-driven vehicles following them reach the target speed from the upper layer in an efficient and smooth manner. The presented MPC and the hierarchical control approach are tested in microscopic simulation environments. Simulation results show that (i) the presented MPC resolves freeway jam waves efficiently with reasonable safety constraints implemented, and (ii) the presented hierarchical control approach can effectively resolve jam waves in a single-lane freeway, even though the penetration rate of CAVs is as low as 5%.@en

Variable speed limits (VSLs) are a common traffic control measure to resolve freeway jam waves. State-of-the-art model predictive control (MPC) approaches of VSLs are developed based on Eulerian Lighthill-Whitham and Richards (LWR) models, where the decision variables are flows between road segments. It is difficult to implement constraints on speeds that are necessary in typical real-world speed limit systems, because converting flow to speed results in nonlinear and non-convex optimization formulations. In this paper, we develop a new MPC of VSLs based on a discrete Lagrangian LWR model, in which the decision variables are average speeds of vehicle groups. This allows formulating speed constraints as control constraints rather than state constraints in the MPC problem. The optimization of vehicle groups speeds is formulated as a linear programming problem which can be solved efficiently. We further integrate the presented MPC to a hierarchical VSL control framework leveraging connected vehicles. The presented MPC decides the optimal target speed of each vehicle group led by a connected automated vehicle (CAV) at the upper macroscopic level with a prediction horizon of 20 min. At the lower microscopic level, CAVs randomly distributed in mixed traffic are regarded as actuators of the upper layer. Microscopic CAV accelerations are optimized in a short horizon of the order 5–10 s so that the human-driven vehicles following them reach the target speed from the upper layer in an efficient and smooth manner. The presented MPC and the hierarchical control approach are tested in microscopic simulation environments. Simulation results show that (i) the presented MPC resolves freeway jam waves efficiently with reasonable safety constraints implemented, and (ii) the presented hierarchical control approach can effectively resolve jam waves in a single-lane freeway, even though the penetration rate of CAVs is as low as 5%.@en

Experiments and field observations have revealed that when silt and very fine sand are subject to oscillatory wave motion, a high shear flow layer and a high concentration layer (HCL) exist near the bottom. The behavior of the HCL is still under researched. Firstly, an intra-wave process based 1DV model was established for fine sediment transport under the combined action of waves and currents. Some key processes that were included in the model are represented through approaches for different bed forms (rippled bed and ‘flat bed’), hindered settling, stratification, reference concentration and critical shear stress. A number of experimental datasets were collected to verify the model, which shows that the model is able to properly simulate the flow and sediment dynamics. Secondly, sensitivity analyses were carried out on some factors which would impact the suspended sediment concentration (SSC) profile of the HCL by the 1DV model, such as bed forms, flow dynamics, stratification effects, mobile bed effects and hindered settling. Results show that bed forms play a significant role in the HCL and determination of the shape of the concentration profile. When a current is imposed, the SSC profiles become smoother; however, sediment concentration in the lower HCL is still dominated by the wave motions. For finer sediment, the stratification effects and the mobile bed effects strongly impact the HCL. In conclusion, this paper provides a tool for the study of the HCL and an evaluation of several impact factors on the HCL.@en

Halbach PM ironless linear motors mostly adopt film windings. In this paper, a novel Halbach PM ironless linear motor with trapezoid windings is proposed and analyzed. The trapezoid windings can achieve a primarily single-sided and well sinusoidal magnetic field. After current density formula is derived, the magnetic flux density equations of the trapezoid windings are formulated using the vector potential method. Based on analytical field, the force ripples of the Halbach PM ironless linear motor with trapezoid windings are analyzed using Maxwell stress tensor method. The simulations with FE method and numerical Lorentz force method are presented to show the validity of the analysis method.@en

Halbach PM ironless linear motors mostly adopt film windings. In this paper, a novel Halbach PM ironless linear motor with trapezoid windings is proposed and analyzed. The trapezoid windings can achieve a primarily single-sided and well sinusoidal magnetic field. After current density formula is derived, the magnetic flux density equations of the trapezoid windings are formulated using the vector potential method. Based on analytical field, the force ripples of the Halbach PM ironless linear motor with trapezoid windings are analyzed using Maxwell stress tensor method. The simulations with FE method and numerical Lorentz force method are presented to show the validity of the analysis method.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

Ecological function reflects the ability of the land to provide ecological goods to support high-quality human production and life. The evaluation of the county-level ecological function across the whole nation is crucial for sustainable land management, which has not been implemented effectively in China. In this study, we proposed a unified system for the assessment of ecological function that would be comparable at the county level, and we applied the system to evaluate the ecological function of 2850 counties across China based on multi-source data. We also examined the spatiotemporal changes in ecological function from 2009 to 2015 using standard deviational ellipses and coefficients of variation. The results showed that the number of counties with high levels of ecological function in China decreased by 8.13% from 2009 to 2012 and then increased by 0.6% from 2012 to 2015. The spatial pattern of the degradation of ecological function shifted from the east-west direction to the southwest-northeast direction and became centralized in the Central Plains area of China. The regional imbalance in ecological function followed the order from high to low of the central, western, northeastern, and eastern areas of China. Targeted policies were proposed to control the degradation of the ecological function in the four regions in China.@en

For traffic flow models, calibration and validation are essential. Cellular automaton (CA) models are a special class of models, describing the movement of vehicles in discretised space and time. However, the previous work on calibration and validation does not discuss CA models systematically. This study calibrates and validates a stochastic CA model. The authors use a simple CA model, which only has two important parameters to be calibrated. The methodology for optimisation is to minimise the relative root mean square error between two properties: The averaged velocity and the variation of velocities in a platoon at a given density. Three different sites are used as cases to show the methodology, for which different types of data (video trajectories or GPS data) are available. The authors find that the best model parameters vary for the different locations. This may result from various driving strategies and potential tendencies. Thus, it is concluded that for CA models, various traffic flow phenomena need to be simulated by various parameters.@en