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At least 91 records · Page 5

System and method for investigating sub-surface features and 3D imaging of non-linear property, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation

A system and a method for generating a three-dimensional image of a rock formation, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation are provided. A first acoustic signal includes a first plurality of pulses. A second acoustic signal from a second source includes a second plurality of pulses. A detected signal returning to the borehole includes a signal generated by a non-linear mixing process from the first and second acoustic signals in a non-linear mixing zone within an intersection volume. The received signal is processed to extract the signal over noise and/or signals resulting from linear interaction and the three dimensional image of is generated.

58 GEOSCIENCES↗

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plans in terms of average delay, number of stops, and vehicular emissions at the network level.

97 MATHEMATICS AND COMPUTING↗

Deep Multi-Agent Reinforcement Learning for Real-World Signalized Traffic Corridor Control

Signalized traffic control problem has been addressed recently with deep Reinforcement Learning (RL) approaches involving diverse state, action, and reward structures. While significant progress has been noted in the literature, open challenges still remain in the areas of adaptive signal phase timing, coordination in a multi-intersection corridor setting, and consideration of real-world traffic conditions. In the context of deep RL-based problem framing, extensions are needed that enable adaptive signal phase timings in an intersection agent's action space, computationally efficient information sharing among neighboring signalized intersection agents along a corridor, and experimentation in realistic simulation environments. In this paper, we develop a deep Advantage Actor Critic (A2C) multi-agent RL (MARL) approach capturing the research extensions above and apply it within a real-world calibrated Aimsun Next traffic corridor simulation model based on traffic data from the City of Coral Gables, Florida. For a multi-intersection corridor control setting, our numerical simulation experiments with a decentralized A2C MARL algorithm applied at different time periods led to a total average corridor travel delay reduction (expressed in seconds/mile averaged over vehicles) from 4.9% to 19.9% compared to state-of-the-art actuated control.

Shuvo, Salman S. [BATTELLE (PACIFIC NW LAB)]↗

Distributed optimization for multi-commodity urban traffic control

A distributed method for concurrent traffic signal and routing control of traffic networks is proposed. The method is based on the multi-commodity store-and-forward model, in which the destinations are the commodities. The system benefits from the communication between vehicles and infrastructure, providing optimal signal timings to intersections and routes to vehicles on a link-by-link basis. Using the augmented Lagrangian to model the constraints into the objective, the baseline centralized problem is decomposed into a set of objective-coupled subproblems, one for each intersection, enabling the solution to be computed by a distributed- gradient projection algorithm. Further, the intersection agents only need to communicate and coordinate with neighboring intersections to ensure convergence to the optimal solution while tolerating suboptimal iterations that offer more flexibility, unlike other distributed approaches. Through microsimulation, we demonstrate the effectiveness of the proposed algorithm in traffic networks with time-varying demand. Computational analysis shows that the distributed problem is suitable for real-time applications. A robustness analysis show that the distributed formulation enables a graceful degradation of the system in case of failure.

Augmented Lagrangian↗

Conical-Domain Model for Estimating GPS Ionospheric Delays

The conical-domain model is a computational model, now undergoing development, for estimating ionospheric delays of Global Positioning System (GPS) signals. Relative to the standard ionospheric delay model described below, the conical-domain model offers improved accuracy. In the absence of selective availability, the ionosphere is the largest source of error for single-frequency users of GPS. Because ionospheric signal delays contribute to errors in GPS position and time measurements, satellite-based augmentation systems (SBASs) have been designed to estimate these delays and broadcast corrections. Several national and international SBASs are currently in various stages of development to enhance the integrity and accuracy of GPS measurements for airline navigation. In the Wide Area Augmentation System (WAAS) of the United States, slant ionospheric delay errors and confidence bounds are derived from estimates of vertical ionospheric delay modeled on a grid at regularly spaced intervals of latitude and longitude. The estimate of vertical delay at each ionospheric grid point (IGP) is calculated from a planar fit of neighboring slant delay measurements, projected to vertical using a standard, thin-shell model of the ionosphere. Interpolation on the WAAS grid enables estimation of the vertical delay at the ionospheric pierce point (IPP) corresponding to any arbitrary measurement of a user. (The IPP of a given user s measurement is the point where the GPS signal ray path intersects a reference ionospheric height.) The product of the interpolated value and the user s thin-shell obliquity factor provides an estimate of the user s ionospheric slant delay. Two types of error that restrict the accuracy of the thin-shell model are absent in the conical domain model: (1) error due to the implicit assumption that the electron density is independent of the azimuthal angle at the IPP and (2) error arising from the slant-to-vertical conversion. At low latitudes or at mid-latitudes under disturbed conditions, the accuracy of SBAS systems based upon the thin-shell model suffers due to the presence of complex ionospheric structure, high delay values, and large electron density gradients. Interpolation on the vertical delay grid serves as an additional source of delay error. The conical-domain model permits direct computation of the user s slant delay estimate without the intervening use of a vertical delay grid. The key is to restrict each fit of GPS measurements to a spatial domain encompassing signals from only one satellite. The conical domain model is so named because each fit involves a group of GPS receivers that all receive signals from the same GPS satellite (see figure); the receiver and satellite positions define a cone, the satellite position being the vertex. A user within a given cone evaluates the delay to the satellite directly, using (1) the IPP coordinates of the line of sight to the satellite and (2) broadcast fit parameters associated with the cone. The conical-domain model partly resembles the thin-shell model in that both models reduce an inherently four-dimensional problem to two dimensions. However, unlike the thin-shell model, the conical domain model does not involve any potentially erroneous simplifying assumptions about the structure of the ionosphere. In the conical domain model, the initially four-dimensional problem becomes truly two-dimensional in the sense that once a satellite location has been specified, any signal path emanating from a satellite can be identified by only two coordinates; for example, the IPP coordinates. As a consequence, a user s slant-delay estimate converges to the correct value in the limit that the receivers converge to the user s location (or, equivalently, in the limit that the measurement IPPs converge to the user s IPP).

Sparks, Lawrence↗

A computerized traffic control algorithm to determine optimal traffic signal settings

An algorithm was developed to optimally control the traffic signals at each intersection using a discrete time traffic model applicable to heavy or peak traffic. Off line optimization procedures were applied to compute the cycle splits required to minimize the lengths of the vehicle queues and delay at each intersection. The method was applied to an extensive traffic network in Toledo, Ohio. Results obtained with the derived optimal settings are compared with the control settings presently in use.

Seldner, K.↗

Multi-Commodity Traffic Signal Control and Routing With Connected Vehicles

We report a real-time traffic management policy that integrates traffic signal control and multi-commodity routing of connected vehicles in networks with multiple destinations is developed. The proposed policy is based on a multi-commodity formulation of the store-and-forward model and assumes all vehicles are able to exchange information with the infrastructure. Vehicles share information about their current location and final destination. Based on this information, the strategy determines both optimized signal timings at every intersection and vehicle-specific routing information at every link of the network. The control actions, i.e., signal times and routing information, are updated at every cycle and delivered by a finite horizon optimal control problem cast into a rolling horizon framework. The underlying optimization problem is convex, and thus the method is suitable for real-time operation in large networks. The method is validated via a micro-simulation study in networks with up to twenty intersections and, in all simulations, outperforms a real-time traffic-responsive signal control strategy that is based on a single-commodity store-and-forward model. The scalable computation effort for increasing network sizes and prediction horizon confirms the computational efficiency of the method.

42 ENGINEERING↗

Extracting Vehicle Trajectories from Partially Overlapping Roadside Radar

This work presents a methodology for extracting vehicle trajectories from six partially-overlapping roadside radars through a signalized corridor. The methodology incorporates radar calibration, transformation to the Frenet space, Kalman filtering, short-term prediction, lane-classification, trajectory association, and a covariance intersection-based approach to track fusion. The resulting dataset contains 79,000 fused radar trajectories over a 26-h period, capturing diverse driving scenarios including signalized intersections, merging behavior, and a wide range of speeds. Compared to popular trajectory datasets such as NGSIM and highD, this dataset offers extended temporal coverage, a large number of vehicles, and varied driving conditions. The filtered leader–follower pairs from the dataset provide a substantial number of trajectories suitable for car-following model calibration. The framework and dataset presented in this work has the potential to be leveraged broadly in the study of advanced traffic management systems, autonomous vehicle decision-making, and traffic research.

33 ADVANCED PROPULSION SYSTEMS↗

Safe Operations at Roadway Junctions - Design Principles from Automated Guideway Transit

Herein this paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone "interlocking" at each junction location deconflicts railway traffic, affirming safe passage. The analogous AV protection safety subsystem is defined as fail-safe equipment that monitors roadway intersections and junctions, communicates traffic signal status, perceives and communicates alerts and signals to AV connected vehicles concerning potential unsafe conditions, and performs related primary safety functions. Conclusions are drawn that the AV protection roadway intersection functions must be performed by local roadside equipment dedicated to protecting each roadway intersection and junction. Further, it is concluded that the communications technology connecting the infrastructure with the vehicle to perform this vital, fail-safe protection should meet specific functional and performance criteria.

33 ADVANCED PROPULSION SYSTEMS↗

Digital signal processing and control and estimation theory -- Points of tangency, area of intersection, and parallel directions

A number of current research directions in the fields of digital signal processing and modern control and estimation theory were studied. Topics such as stability theory, linear prediction and parameter identification, system analysis and implementation, two-dimensional filtering, decentralized control and estimation, image processing, and nonlinear system theory were examined in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the two disciplines. An extensive bibliography is included.

Willsky, A. S.↗

Vehicle Transponder for Preemption of Traffic Lights

The purpose of this article is to describe, in more detail, the transponder installed in each vehicle that participates in the emergency traffic-light-preemption system described in the immediately preceding article. The transponder (see figure) is a fully autonomous data--collection, data-processing, information-display, and communication subsystem that performs robustly in preemption of traffic lights and monitoring of the statuses of street intersections. This transponder monitors the condition of the emergency vehicle in which it is installed and determines when the vehicle has been placed in an emergency-response condition with its siren and/or warning lights activated. Upon detection of such a condition, the transponder collects real-time velocity and acceleration data from the onboard diagnostic (OBD) computer of the vehicle. For this purpose, the transponder contains an OBD interface circuit, including a microprocessor that determines the manufacturer and model of the vehicle and then sends the appropriate commands to the OBD computer requesting the speed and acceleration data. At the same time, data from an onboard navigation system are collected to determine the location and the heading of the vehicle. Then acceleration, speed, position, and heading data are processed and combined with a vehicle-identification number and the resulting set of data is transmitted to monitoring and control units located at all intersections within communication range. When the unit at an intersection determines that this vehicle is approaching and has priority to preempt the intersection, it transmits a signal declaring the priority and the preemption to all participating vehicles (including this one) in the vicinity. If the unit at the intersection has determined that other participating vehicles are also approaching the intersection, then this unit also transmits, to the vehicle that has priority, a message that the other vehicles are approaching the same intersection. The texts of these messages, plus graphical symbols that show the directions and numbers of the approaching vehicles, are presented on the display panel of a computer that is part of the transponder.

Foster, Conrad↗

Delay-Based Traffic Signal Control for Throughput Optimality and Fairness at an Isolated Intersection

With the attractive feature of guaranteeing maximum network throughput, backpressure routing has been widely used in wireless communication networks. Motivated by the backpressure routing, in this paper, we propose a delay-based traffic signal control algorithm in transportation networks. We prove that this delay-based control achieves optimal throughput performance, same as the queue-based traffic signal control in the literature. However, a vehicle at a lane whose queue length remains very small may be excessively delayed under the queue-based signal control. Our delay-based backpressure control can deal with the excessive delays and achieve better fairness with respect to delay while still guaranteeing throughput optimality. Moreover, a general weighted control scheme combining the queue-based and delay-based schemes is also investigated, to provide a more flexible control according to the quality of service requirements. Numerical results explore their performance under both homogeneous and heterogeneous traffic scenarios.

33 ADVANCED PROPULSION SYSTEMS↗

Advances in S. cerevisiae Engineering for Xylose Fermentation and Biofuel Production: Balancing Growth, Metabolism, and Defense

Genetically engineering microorganisms to produce chemicals has changed the industrialized world. The budding yeast Saccharomyces cerevisiae is frequently used in industry due to its genetic tractability and unique metabolic capabilities. S. cerevisiae has been engineered to produce novel compounds from diverse sugars found in lignocellulosic biomass, including pentose sugars, like xylose, not recognized by the organism. Engineering high flux toward novel compounds has proved to be more challenging than anticipated since simply introducing pathway components is often not enough. Several studies show that the rewiring of upstream signaling is required to direct products toward pathways of interest, but doing so can diminish stress tolerance, which is important in industrial conditions. As an example of these challenges, we reviewed S. cerevisiae engineering efforts, enabling anaerobic xylose fermentation as a model system and showcasing the regulatory interplay’s controlling growth, metabolism, and stress defense. Enabling xylose fermentation in S. cerevisiae requires the introduction of several key metabolic enzymes but also regulatory rewiring of three signaling pathways at the intersection of the growth and stress defense responses: the RAS/PKA, Snf1, and high osmolarity glycerol (HOG) pathways. The current studies reviewed here suggest the modulation of global signaling pathways should be adopted into biorefinery microbial engineering pipelines to increase efficient product yields.

59 BASIC BIOLOGICAL SCIENCES↗

Fuel-Based Nash Bargaining Approach for Adaptive Signal Control in an N -Player Cooperative Game

This paper presents a fuel-based game-theoretic approach for adaptive signal control. Our controller applies Nash bargaining (NB) in an n-player cooperative game to identify optimal phasing splits considering future traffic demands. The fuel-based NB controller utilizes an objective function that combines operational measures (delays and stops) with fuel consumption measures at intersections. The proposed controller was encoded in Python and then implemented and evaluated in a VISSIM microscopic traffic simulation model in an intersection with increasing volumes. The performance of the NB controller was compared to a traditional actuated control as the baseline. The results show that the NB controller was able to achieve superior environmental gains with a 17% saving in fuel consumption and a 17% reduction in CO emissions. In addition, the proposed controller was capable of maintaining acceptable operational conditions as it achieved a 20% reduction in delay, 8% reduction in the number of stops, and 8% reduction in queue lengths compared to the actuated controller. Compared to similar studies that applied NB for adaptive signal control, our fuel-based NB controller stands out as a promising approach to significantly improve fuel consumption at signalized intersections.

Engineering↗

Infrastructure Spatial Sensing at Intersections

This presentation was presented at the VTO AMR in 2018 covering the Infrastructure Spatial Sensing at Intersection project, which investigates the benefits and state of industry for utilizing LiDAR and advanced video signal processing to track all objects in the field of view at intersections to enhance safety and optimize traffic flow. Whereas the safety, mobility, and energy benefits of automated and connected vehicles (CAVs) will only be realized at intersections, once a significant portion of the vehicle fleet is converted to CAV technology, advanced spatial sensors deployed at intersections provide the observability to optimize traffic flow in the near term, hastening its benefits.

25 ENERGY STORAGE↗

Traffic signal design and simulation for vulnerable road users safety and bus preemption

Mostly, pedestrian car accidents occurred at a signalized interaction is because pedestrians cannot across the intersection safely within the green light. From the viewpoint of pedestrian, there might have two reasons. The first one is pedestrians cannot speed up to across the intersection, such as the elders. The other reason is pedestrians do not sense that the signal phase is going to change and their right-of-way is going to be lost. Developing signal logic to protect pedestrian, who is crossing an intersection is the first purpose of this study. In addition, to improve the reliability and reduce delay of public transportation service is the second purpose. Therefore, bus preemption is also considered in the designed signal logic. In this study, the traffic data of the intersection of Chong-Qing North Road and Min-Zu West Road, Taipei, Taiwan, is employed to calibrate and validate the signal logic by simulation. VISSIM 5.20, which is a microscopic traffic simulation software, is employed to simulate the signal logic. From the simulated results, the signal logic presented in this study can protect pedestrians crossing the intersection successfully. The design of bus preemption can reduce the average delay. However, the pedestrian safety and bus preemption signal will influence the average delay of cars largely. Thus, whether applying the pedestrian safety and bus preemption signal logic to an intersection or not should be evaluated carefully.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ultrafast x-ray scattering and electronic coherence at avoided crossings: complete isotropic signals

Abstract Nonadiabatic transitions at conical intersections and avoided crossings play a pivotal role in shaping the outcomes of photochemical reactions. Using the photodissociation of LiF as a model, this theoretical study explores the application of gas phase nonresonant ultrafast x-ray scattering to map nonadiabatic transitions at an avoided crossing, utilizing the part of the scattering signal that probes electronic coherence directly. The presented scattering signals are rotationally averaged and calculated from two- rather than one-electron (transition) densities, which inherently accounts for all possible electronic transitions driven by the x-ray photon. This approach provides quantitative predictions of the experimental signals, thereby facilitating future experimental endeavors to observe nonadiabatic effects and coherent electron dynamics with ultrafast x-ray scattering.

Optics↗