State-Constrained Optimal Solutions for Safe Eco-Approach and Departure at Signalized Intersections

2020 ◽  
Author(s):  
Jihun Han ◽  
Dominik Karbowski ◽  
Aymeric Rousseau
Keyword(s):  
Analytical Solutions ◽  
Pure State ◽  
Energy Savings ◽  
Minimum Principle ◽  
Optimization Methods ◽  
Signalized Intersections ◽  
Constant Acceleration ◽  
Preceding Vehicle ◽  
Speed Change ◽  
Pass Through

Abstract This paper provides fundamentals of how to energy-efficiently pass through signalized intersections while avoiding any rear-end collisions with leading vehicles. In our previous works [1, 2], analytical solutions with and without second-order pure state constraints imposed by the preceding vehicle were presented; these showed significant energy saving potential for connected and automated vehicles (CAVs) compared to human-driven vehicles. However, these solutions were derived assuming that the desired distance headway policy does not include a speed change over a predictive horizon, and that the preceding vehicle has constant acceleration. We use the desired time headway policy that includes the speed change to define the first-order pure state constraint. We then derive analytical solutions using the direct adjoining method based on Pontryagin’s minimum principle. We also present a novel solver to compute energy-optimal and collision-free state trajectories by accounting for a piecewise constant acceleration of the preceding vehicle without using any numerical optimization methods that require initial guesses. For simple scenarios with one intersection, we analyze how the novel solver allows CAVs to smoothly pass through the signalized intersection and then reach a desired cruising speed. We also use a simulation framework based on high-fidelity powertrain models to validate its effectiveness based on energy savings when driving on real-world urban routes.

String Instabilities in Formation Flight: Limitations Due to Integral Constraints

2004 ◽  
Vol 126 (4) ◽  
pp. 873-879 ◽  
Author(s):  
P. Seiler ◽  
A. Pant ◽  
J. K. Hedrick
Keyword(s):  
Flight Control ◽  
Formation Control ◽  
Energy Savings ◽  
Feedback Loops ◽  
Formation Flight ◽  
Control Laws ◽  
Aerodynamic Efficiency ◽  
Preceding Vehicle ◽  
Specific Control ◽  
Theoretical Results

Flying in formation improves aerodynamic efficiency and, consequently, leads to an energy savings. One strategy for formation control is to follow the preceding vehicle. Many researchers have shown through simulation results and analysis of specific control laws that this strategy leads to amplification of disturbances as they propagate through the formation. This effect is known as string instability. In this paper, we show that string instability is due to a fundamental constraint on coupled feedback loops. The tradeoffs imposed by this constraint imply that predecessor following is an inherently poor strategy for formation flight control. Finally, we present two examples that demonstrate the theoretical results.

scholarly journals Application and benchmarking of a direct method to optimize the fuel consumption of a diesel electric locomotive

2018 ◽  
Vol 232 (9) ◽  
pp. 2272-2289 ◽  
Author(s):  
V Macian ◽  
C Guardiola ◽  
B Pla ◽  
A Reig
Keyword(s):  
Optimal Control ◽  
Direct Method ◽  
Minimum Principle ◽  
Optimization Technique ◽  
Direct Methods ◽  
Optimization Methods ◽  
Computational Time ◽  
Electric Locomotive ◽  
Pontryagin Minimum Principle ◽  
A Direct Method

This paper addresses the optimal control of a long-haul passenger train to deliver minimum-fuel operations. Contrary to the common Pontryagin minimum principle approach in railroad-related literature, this work addresses this optimal control problem with a direct method of optimization, the use of which is still marginal in this field. The implementation of a particular direct method based on the Euler collocation scheme and its transcription into a nonlinear problem are described in detail. In this paper, this optimization technique is benchmarked with well-known optimization methods in the literature, namely dynamic programming and the Pontryagin minimum principle, by simulating a real route. The results showed that the direct methods are on the same level of optimality compared with other algorithms while requiring reduced computational time and memory and being able to handle very complex dynamic systems. The performance of the direct method is also compared to the real trajectory followed by the train operator and exhibits up to 20% of fuel saving in the example route.

Operational Energy Optimization for Pure Electric Ground Vehicles Based on Terrain Profile Preview

2011 ◽  
Author(s):  
Yan Chen ◽  
Zili Chen ◽  
Junmin Wang
Keyword(s):  
Energy Savings ◽  
Hybrid Electric Vehicles ◽  
Energy Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Ground Vehicles ◽  
Battery Power ◽  
Operational Energy ◽  
Global Optimal ◽  
Fuel Optimization

This paper presents an operational energy optimization method for pure electric ground vehicles (EGVs) based on terrain profile preview. Dynamic programming is applied to obtain the global optimal energy point for torque distributions. The vehicles considered in this paper are powered by batteries and in-wheel motors. Different from the fuel optimization methods of conventional hybrid electric vehicles which adjust battery power supplies, a pure EGV actuated by in-wheel motors has only one energy source, whose power consumption is mainly determined by the torque distributions among in-wheel motors in terms of their operating efficiencies. Moreover, the optimization results show that different terrains will influence the optimal torque distributions and energy savings.

scholarly journals Biomimetic molecular design tools that learn, evolve, and adapt

2017 ◽  
Vol 13 ◽  
pp. 1288-1302 ◽  
Author(s):  
David A Winkler
Keyword(s):  
Molecular Design ◽  
Optimization Methods ◽  
Synthetic Methods ◽  
Biological Processes ◽  
New Developments ◽  
Design And Optimization ◽  
Bioactive Natural Products ◽  
Unit Operations ◽  
S Curve ◽  
Pass Through

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

Combined Plant and Controller Design Using Decomposition-Based Design Optimization and the Minimum Principle

2010 ◽  
Author(s):  
James T. Allison ◽  
Sam Nazari
Keyword(s):  
Optimal Control ◽  
Design Optimization ◽  
System Design ◽  
Physical System ◽  
Design Problem ◽  
Controller Design ◽  
Minimum Principle ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Augmented Lagrangian Coordination

An often cited motivation for using decomposition-based optimization methods to solve engineering system design problems is the ability to apply discipline-specific optimization techniques. For example, structural optimization methods have been employed within a more general system design optimization framework. We propose an extension of this principle to a new domain: control design. The simultaneous design of a physical system and its controller is addressed here using a decomposition-based approach. An optimization subproblem is defined for both the physical system (i.e., plant) design and the control system design. The plant subproblem is solved using a general optimization algorithm, while the controls subproblem is solved using a new approach based on optimal control theory. The optimal control solution, which is derived using the the Minimum Principle of Pontryagin (PMP), accounts for coupling between plant and controller design by managing additional variables and penalty terms required for system coordination. Augmented Lagrangian Coordination is used to solve the system design problem, and is demonstrated using a circuit design problem.

Speeds of Right-Turning Vehicles at Signalized Intersections during Green or Yellow Phase

2021 ◽  
pp. 036119812110116
Author(s):  
Kay Fitzpatrick ◽  
Michael P. Pratt ◽  
Raul Avelar
Keyword(s):  
Pedestrian Safety ◽  
Operational Efficiency ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Radius Of Curvature ◽  
Vehicle Type ◽  
Curvature Equation ◽  
Site Characteristics ◽  
Preceding Vehicle ◽  
Selection Of

The operation and design of signalized intersections involves tradeoffs between operational efficiency and safety for a variety of users, including motorists, pedestrians, and bicyclists. Additionally, the mix of vehicle types in the fleet sometimes requires special considerations. These concerns especially apply to the selection of curb radius at the corners, where right-turning vehicles operate close to pedestrians. Larger curb radii accommodate the swept paths of trucks and allow right turns to occur at higher speeds but may compromise safety and security for pedestrians by increasing the crossing distance and increasing the frequency of higher-speed turns. The authors collected right-turn vehicle speeds at 31 urban signalized intersection approaches in Texas with radii ranging from 15 to 70 ft. The authors calibrated a model to predict right-turn speeds as a function of site characteristics including curb radius, leading headway, vehicle type (car versus truck), maneuver of the preceding vehicle (through versus right turn), and signal indication (yellow or green). The analysis results indicate that right-turn speeds increase slightly with increasing radius, if the preceding vehicle proceeds through (rather than turning right) at the intersection, or if the signal indication is yellow rather than green. The calculated 85th percentile turning speed is generally higher than the assumed speed calculated using the radius of curvature equation. These trends should be considered if the intersection is expected to have notable volumes of pedestrians or trucks, as lower speeds are desirable for pedestrian safety, but larger radii may be necessary to accommodate turning trucks.

scholarly journals THE CONTROL OF FLEXIBLE AUTOMATED PRODUCTION OF THE SCRAPER CONVEYERS

2021 ◽  
Vol 2 (446) ◽  
pp. 189-197
Author(s):  
L. G. Shpakova ◽  
E. Moraru ◽  
B. N. Feshin ◽  
K. M. Tokhmetova ◽  
Ye. V. Kalashnikova
Keyword(s):  
Energy Consumption ◽  
Control Systems ◽  
Production Line ◽  
Energy Savings ◽  
Optimization Methods ◽  
Automated Production ◽  
Technological Processes ◽  
Industrial Complexes ◽  
Virtual Modeling ◽  
Electromechanical Equipment

The analysis of possible energy saving in in the technological process of production of elements of scraper conveyors containing flexible automated production is given. It consists of complex subordinate aggregate installations consisting of conveyor lines, robot manipulators and tripods. The studied technological processes and control systems for electric drives of actuators are multi-connected, distributed in space, stochastic and multidimensional in the number of control and monitoring coordinates. It is proposed a methodology of reducing energy consumption of actuators by means of physical-virtual modeling and parameterization based on estimates of energy costs, by means of planning factor experiments, steep ascending in the anti-gradient direction of integral quadratic estimates of the control system, which are proportional to the costs of electricity in transient modes of actuators. The methodology, in comparison with the well-known optimization methods, is invariant to the type of products developed in flexible automated production, to the laws of distribution of the semi-finished products flows entering the production line, and is focused on predicting the boundaries of the saved energy and the life of the electromechanical equipment and improving reliability of electric drive control systems operation as a part of industrial complexes. The uniqueness of the method consists in applicability of the developed algorithm of evaluating energy savings and optimizing technological processes according to the criterion of energy consumption in real time in the condi- tions of the probabilistic situation of input parameters, regardless of the selected method of setting the optimal parameters of production line facilities.

scholarly journals Optimal Energy Consumption Analysis of Natural Gas Pipeline

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Enbin Liu ◽  
Changjun Li ◽  
Yi Yang
Keyword(s):  
Energy Consumption ◽  
Natural Gas ◽  
Energy Savings ◽  
Solution Process ◽  
Optimization Methods ◽  
High Energy ◽  
Gas Pipeline ◽  
Dynamic Programming Method ◽  
Long Distance ◽  
Optimal Energy

There are many compressor stations along long-distance natural gas pipelines. Natural gas can be transported using different boot programs and import pressures, combined with temperature control parameters. Moreover, different transport methods have correspondingly different energy consumptions. At present, the operating parameters of many pipelines are determined empirically by dispatchers, resulting in high energy consumption. This practice does not abide by energy reduction policies. Therefore, based on a full understanding of the actual needs of pipeline companies, we introduce production unit consumption indicators to establish an objective function for achieving the goal of lowering energy consumption. By using a dynamic programming method for solving the model and preparing calculation software, we can ensure that the solution process is quick and efficient. Using established optimization methods, we analyzed the energy savings for the XQ gas pipeline. By optimizing the boot program, the import station pressure, and the temperature parameters, we achieved the optimal energy consumption. By comparison with the measured energy consumption, the pipeline now has the potential to reduce energy consumption by 11 to 16 percent.

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