1. |
- Beal, Jacob, et al.
(author)
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Robust estimation of bacterial cell count from optical density
- 2020
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In: Communications Biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 3:1
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Journal article (peer-reviewed)abstract
- Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.
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2. |
- Cui, Shaohua, et al.
(author)
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Adaptive Collision-Free Trajectory Tracking Control for String Stable Bidirectional Platoons
- 2023
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In: IEEE Transactions on Intelligent Transportation Systems. - 1524-9050 .- 1558-0016. ; 24:11, s. 12141-12153
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Journal article (peer-reviewed)abstract
- Autonomous vehicle (AV) platoons, especially those with the bidirectional communication topology, have significant practical value, as they not only increase link capacity and reduce vehicle energy consumption, but also reduce the consumption of communication resources. Small gaps between AVs in a platoon easily lead to emergency braking or even collisions between consecutive AVs. This paper applies barrier Lyapunov functions to collision avoidance between AVs in a bidirectional platoon during trajectory tracking. Based on backstepping technique, an adaptive collision-free platoon trajectory tracking control algorithm is developed to distributedly design control laws for each AV in the platoon. The control algorithm does not need to introduce additional car-following models to simulate AV driving, and only needs to integrate the position trajectories of consecutive AVs to avoid inter-vehicle collisions. Two sign functions are introduced into the control laws of each AV to ensure strong string stability for bidirectional AV platoons. Moreover, uncertainties and external disturbances in vehicle motion are effectively compensated by introducing adaptation laws. Strong string stability is rigorously proved. CarSIM-based comparison simulations verify the effectiveness of the proposed control algorithm in avoiding inter-vehicle collisions, compensating for uncertainties in vehicle motion, and suppressing the amplification of spacing errors along the platoon.
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3. |
- Cui, Shaohua, 1995, et al.
(author)
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Delay-throughput tradeoffs for signalized networks with finite queue capacity
- 2024
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In: Transportation Research Part B: Methodological. - 0191-2615. ; 180
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Journal article (peer-reviewed)abstract
- Network-level adaptive signal control is an effective way to reduce delay and increase network throughput. However, in the face of asymmetric exogenous demand, the increase of network performance via adaptive signal control alone is at the expense of service fairness (i.e., phase actuation fairness and network resource utilization fairness). In addition, for oversaturated networks, arbitrary adaptive signal control seems to have little effect on improving network performance. Therefore, under the assumption that the mean routing proportions/turn ratios of vehicles at intersections are fixed, this study investigates the problem of optimally allocating input rates to entry links and simultaneously finding a stabilizing signal control policy with phase fairness. We model the stochastic optimization problem of maximizing network throughput subject to network stability (i.e., all queue lengths have finite means) and average phase actuation constraints to bridge the gap between stochastic network stability control and convex optimization. Moreover, we further propose a micro-level joint admission and bounded signal control algorithm to achieve network stability and throughput optimization simultaneously. Joint control is implemented in a fully decomposed and distributed manner. For any arrival rate, joint control provably achieves network throughput within O(1/V) of optimality while trading off average delay with O(V), where V is an adjusted control parameter. Through a comparative simulation of a real network with 256 O-D pairs, the proposed joint control keeps network throughput at maximum, guarantees service fairness, and fully utilizes network capacity (i.e., increases network throughput by 17.54%).
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4. |
- Cui, Shaohua, et al.
(author)
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Temporal Finite-Time Adaptation in Controlling Quantized Nonlinear Systems Amidst Time-Varying Output Constraints
- 2024
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In: IEEE Transactions on Automation Science and Engineering. - 1558-3783 .- 1545-5955. ; In Press
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Journal article (peer-reviewed)abstract
- Using the backstepping technique, this paper formulates innovative adaptive finite-time stabilizing controllers for uncertain nonlinear systems featuring nonuniform input quantization and asymmetric, time-varying output constraints. These novel controllers leverage the consistent characteristics of both hysteresis quantizers and logarithmic quantizers. Quantization errors, when consistent, become unbounded and contingent on control input, rendering them incompatible with the growth conditions of nonlinear systems. Consequently, the developed adaptive controllers eliminate the reliance on growth conditions, effectively addressing the impact of unbounded quantization errors on finite-time stability. This adaptability allows the controllers to function effectively with systems employing either hysteresis quantizers or logarithmic quantizers. The paper establishes the convergence of these controllers through the finite-time Lyapunov stability theorem. It also provides a comprehensive guideline for tuning settling time, enabling fine-grained control over finite-time convergence and adjustable tracking error performance. Additionally, the controllers rigorously maintain system output within predefined limits. Their effectiveness and low computational burden are demonstrated through three comparative numerical simulations and a practical simulation in collision-free trajectory tracking control of an autonomous vehicle platoon using the vehicle motion software CarSim. These simulations confirm the advanced performance of the adaptive controllers. Note to Practitioners—This paper introduces an innovative approach to control uncertain nonlinear systems encountering intricate input quantization and output constraints. Employing the sophisticated backstepping technique, the authors present adaptive finite-time-stabilizing controllers engineered to address nonuniform input quantization and asymmetric, time-varying output restrictions. What distinguishes these controllers is their reliance on the consistent behavior exhibited by hysteresis and logarithmic quantizers. This unique feature equips them to effectively counteract unbounded quantization errors influenced by control input. Most notably, these controllers eliminate the conventional growth conditions typically demanded by nonlinear systems. As a result, they extend their applicability to a broad spectrum of systems employing either hysteresis or logarithmic quantizers. The research also provides practitioners with a valuable guideline for precisely adjusting settling time. This enables the attainment of desired convergence rates while permitting adaptable tracking error performance. Additionally, these controllers guarantee that the system’s output adheres to predefined limits. The practical significance of this study is highlighted through three comparative numerical simulations and a real-world application simulation. This real-world simulation involves collision-free trajectory tracking control of an autonomous vehicle platoon, executed using the vehicle motion software CarSim. These simulations unequivocally demonstrate the effectiveness and low computational burden of the developed controllers, thereby establishing them as a valuable resource for practitioners facing complex control challenges in various domains.
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5. |
- Xue, Yongjie, et al.
(author)
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A platoon-based cooperative optimal control for connected autonomous vehicles at highway on-ramps under heavy traffic
- 2023
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In: Transportation Research, Part C: Emerging Technologies. - : Elsevier BV. - 0968-090X. ; 150
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Journal article (peer-reviewed)abstract
- To improve traffic efficiency at highway on-ramps under heavy traffic, this study proposes a platoon-based cooperative optimal control algorithm for connected autonomous vehicles (CAVs). The proposed algorithm classifies CAVs on both mainline and on-ramp into multiple local platoons (LPs) according to their initial conditions (i.e., spacing and speed), which enables the algorithm to adapt to time-varying traffic volume. A distributed cooperative control for multiple LPs is designed which projects on-ramp LPs onto mainline to transform the complex 2-D multi-platoon cooperation problem into a 1-D platoon following control problem. An optimal control is applied to further consider the strict nonlinear safety spacing constraint and state limitations (e.g., maximum speed and acceleration), and an analytical solution to the optimal control is derived based on Pontryagin's maximum principle. The consensus of intra-platoon and inter-platoon are analyzed, and sufficient conditions of the consensus are mathematically deducted based on Lyapunov stability theorem. Numerical simulations are conducted for different traffic demand levels and demand splits to verify the effectiveness of the proposed algorithm. The sensitivity analysis of maximum platoon sizes for mainline and on-ramp LPs is performed. A comparison with a baseline virtual platooning merging strategy is conducted, and results show that the proposed algorithm could significantly improve the average travel speed and traffic efficiency, and reduce total travel time.
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6. |
- Yang, Ying, et al.
(author)
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Data-driven rolling eco-speed optimization for autonomous vehicles
- 2024
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In: Frontiers of Engineering Management. - 2096-0255 .- 2095-7513. ; In Press
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Journal article (peer-reviewed)abstract
- In urban settings, fluctuating traffic conditions and closely spaced signalized intersections lead to frequent emergency acceleration, deceleration, and idling in vehicles. These maneuvers contribute to elevated energy use and emissions. Advances in vehicle-to-vehicle and vehicle-to-infrastructure communication technologies allow autonomous vehicles (AVs) to perceive signals over long distances and coordinate with other vehicles, thereby mitigating environmentally harmful maneuvers. This paper introduces a data-driven algorithm for rolling eco-speed optimization in AVs aimed at enhancing vehicle operation. The algorithm integrates a deep belief network with a back propagation neural network to formulate a traffic state perception mechanism for predicting feasible speed ranges. Fuel consumption data from the Argonne National Laboratory in the United States serves as the basis for establishing the quantitative correlation between the fuel consumption rate and speed. A spatiotemporal network is subsequently developed to achieve eco-speed optimization for AVs within the projected speed limits. The proposed algorithm results in a 12.2% reduction in energy consumption relative to standard driving practices, without a significant extension in travel time.
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7. |
- Yao, Baozhen, et al.
(author)
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Dynamic Pricing for Mobile Charging Service Considering Electric Vehicles Spatiotemporal Distribution
- 2023
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In: Smart Innovation, Systems and Technologies. - 2190-3026 .- 2190-3018. ; 356, s. 23-33
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Conference paper (peer-reviewed)abstract
- As mobile charging service has the advantages of flexible charging and simple operation, it is selected by more and more users of electric vehicles. However, due to the differences in road network density and traffic flow distribution, the uneven distribution of charging demand occurs in different regions. It reduces the service efficiency of mobile charging vehicles during the peak charging demand period, thus affecting the final revenue of operators. In order to solve this problem, this paper proposes a dynamic pricing strategy considering the spatiotemporal distribution of charging demand to induce users to transfer between different regions, which can alleviate the phenomenon that users wait too long during peak demand. In order to realize the city-level operation of mobile charging service, we divide the region into hexagons and make statistics on the charging demand in each region. The established demand updating model can reflect the impact of charging price on users’ charging behavior. Finally, we simulate the generation of charging demand in Haidian District, Beijing. According to the demand of each area, a thermodynamic diagram of charging demand is generated.
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