Roberto Horowitz

University of California, Berkeley | UCB · Department of Mechanical Engineering

Highway on-ramps are regarded as typical bottlenecks in transportation networks. In previous work, mainline vehicles' selfish lane choice behavior at on-ramps is studied and regarded as one cause leading to on-ramp inefficiency. When on-ramp vehicles plan to merge into the mainline of the highway, mainline vehicles choose to either stay steadfast o...

We consider the scenario where human-driven/autonomous vehicles with low/high occupancy are sharing a segment of highway and autonomous vehicles are capable of increasing the traffic throughput by preserving a shorter headway than human-driven vehicles. We propose a toll lane framework where a lane on the highway is reserved freely for autonomous v...

The recent rapid growth in the cloud storage industry has strongly increased the demand for high-capacity hard disk drives (HDDs). Increasing the areal density brings new challenges to the high-accuracy head-positioning control in the next generation HDD development. Triple-stage-actuator (TSA) system is one of the emerging technologies that can ac...

Vehicle bypassing is known to increase delays at traffic diverges. However, due to the complexities of this phenomenon, accurate and yet simple models of such lane change maneuvers are hard to develop. In this work, we present a macroscopic model for predicting the number of vehicles that perform a bypass at a traffic diverge when taking an exit li...

The multi actuator drive technology was unveiled by Seagate in December 2017, a breakthrough that can almost double the data performance of the future generation hard disk drives. This technology will equip drives with dual actuators operating on the same pivot point. Each actuator will control half of the drive's arms. Since two actuators operate...

In this paper, a frequency separation based adaptive feedforward control algorithm is developed with the ability to identify the plant and do compensation region by region. In this algorithm, the accelerometer signal is filtered by a series of uniformly distributed bandpass filters to generate a bunch of subband signals which are mutually exclusive...

With increasing data density on hard disk drives, there is need to develop more robust and better performing track following control systems. We present a multi-input multi-output (MIMO) data driven feedback control design methodology. The design considers multiple frequency response measurements of all actuators, simultaneously, ensuring robustnes...

In this paper we present a model-predictive control (MPC) based approach for vehicle platooning in an urban traffic setting. Our primary goal is to demonstrate that vehicle platooning has the potential to significantly increase throughput at intersections, which can create bottlenecks in the traffic flow. To do so, our approach relies on vehicle co...

This article presents a model-based method for fusing data from multiple sensors with a hypothesis-test-based component for rejecting potentially faulty or otherwise malign data. Our framework is based on an extension of the classic particle filter algorithm for real-time state estimation of uncertain systems with nonlinear dynamics with partial an...

In this paper we present a model-predictive control (MPC) based approach for vehicle platooning in an urban traffic setting. Our primary goal is to demonstrate that vehicle platooning has the potential to significantly increase throughput at intersections, which can create bottlenecks in the traffic flow. To do so, our approach relies on vehicle co...

Multi Actuator Technology was unveiled in December 2017 by Seagate, a breakthrough that can double the data performance of the future generation hard disk drives. This technology will equip drives with dual actuators operating on the same pivot point. Each actuator will control half of the drives arms. This new technology brings new control challen...

In Part I of this paper series, several macroscopic traffic model elements for mathematically describing freeway networks equipped with managed lane facilities were proposed. These modeling techniques seek to capture at the macroscopic the complex phenomena that occur on managed lane-freeway networks, where two parallel traffic flows interact with...

Many potential applications of reinforcement learning in the real world involve interacting with other agents whose numbers vary over time. We propose new neural policy architectures for these multi-agent problems. In contrast to other methods of training an individual, discrete policy for each agent and then enforcing cooperation through some addi...

It is known that connected and autonomous vehicles are capable of maintaining shorter headway and distances when they form platoons of vehicles. Thus, such technologies can potentially increase the road capacities of traffic networks. Consequently, it is envisioned that their deployment will also increase the overall network mobility. In this paper...

Deep neural networks can be powerful tools, but require careful application-specific design to ensure that the most informative relationships in the data are learnable. In this paper, we apply deep neural networks to the nonlinear spatiotemporal physics problem of vehicle traffic dynamics. We consider problems of estimating macroscopic quantities (...

Road network junctions, such as merges and diverges, often act as bottlenecks that initiate and exacerbate congestion. More complex junction configurations lead to more complex driver behaviors, resulting in aggregate congestion patterns that are more difficult to predict and mitigate. In this paper, we discuss diverge configurations where vehicles...

In a traffic network, vehicles normally select their routes selfishly. Consequently, traffic networks normally operate at an equilibrium characterized by Wardrop conditions. However, it is well known that equilibria are inefficient in general. In addition to the intrinsic inefficiency of equilibria, the authors recently showed that, in mixed-autono...

It is known that connected and autonomous vehicles are capable of maintaining shorter headways and distances when they form platoons of vehicles. Thus, such technologies can result in increases in the capacities of traffic networks. Consequently, it is envisioned that their deployment will boost the network mobility. In this paper, we verify the va...

A data driven control design approach in the frequency domain is used to design track following feedback controllers for dual-stage hard disk drives using multiple data measurements. The advantage of the data driven approach over model based approach is that, in the former approach the controllers are directly designed from frequency responses of t...

To help mitigate road congestion caused by the unrelenting growth of traffic demand, many transportation authorities have implemented managed lane policies, which restrict certain freeway lanes to certain types of vehicles. It was originally thought that managed lanes would improve the use of existing infrastructure through demand-management behavi...

Vehicle bypassing is known to negatively affect delays at traffic diverges. However, due to the complexities of this phenomenon, accurate and yet simple models of such lane change maneuvers are hard to develop. In this work, we present a macroscopic model for predicting the number of vehicles that bypass at a traffic diverge. We take into account t...

This paper presents a model-based method for fusing data from multiple sensors with a hypothesis-test-based component for rejecting potentially faulty or otherwise malign data. Our framework is based on an extension of the classic particle filter algorithm for real-time state estimation of uncertain systems with nonlinear dynamics with partial and...

To help mitigate road congestion caused by the unrelenting growth of traffic demand, many transportation authorities have implemented managed lane policies, which restrict certain freeway lanes to certain types of vehicles. It was originally thought that managed lanes would improve the use of existing infrastructure through demand-management behavi...

A frequency based data-driven control design considering mixed H2/H-infinity control objectives is developed for multiple input-single output systems. The main advantage of the data-driven control over the model-based control is its ability to use the frequency response measurements of the controlled plant directly without the need to identify a mo...

This paper addresses an open problem in traffic modeling: the second-order macroscopic node problem. A second-order macroscopic traffic model, in contrast to a first-order model, allows for variation of driving behavior across subpopulations of vehicles in the flow. The second-order models are thus more descriptive (e.g., they have been used to mod...

The propagation of traffic congestion along roads is a commonplace nonlinear phenomenon. When many roads are connected in a network, congestion can spill from one road to others as drivers queue to enter a congested road. This paper considers the node model problem, which refers to methods for solving for cross-flows when roads meet at a junction....

This paper proposes a novel direct adaptive control method for rejecting unknown deterministic disturbances and tracking unknown trajectories in systems with uncertain dynamics when the disturbances or trajectories are the summation of multiple sinusoids with known frequencies, such as periodic profiles or disturbances. The proposed algorithm does...

We formulate the Asymmetric Cell Transmission Model (ACTM) as a piecewise affine system defined over regions of the state and input space. We synthesize a hybrid Model Predictive Controller (MPC) for the piecewise affine model such that persistent feasibility and stability are guaranteed. We do so by designing a terminal constraint and terminal cos...

This paper proposes a novel adaptive feedforward control method for rejecting unknown disturbances acting on linear systems with uncertain dynamics. The proposed algorithm does not require a model of the plant dynamics and does not use batches of measurements in the adaptation process. Moreover, it is applicable to both minimum and non-minimum phas...

Loop detectors are installed along many of the freeways across the state of California to provide real-time and historical traffic data. These data are used by Caltrans for traffic management operations, such as freeway ramp metering, and to evaluate the performance of freeway corridor traffic management systems. These data are also being used to c...

Ramp metering is proved to be an effective strategy for reducing or avoiding freeway traffic congestion. As a result, huge amount of research has been conducted on synthesizing effective ramp metering controls. In the previous works, freeway is assumed to be a deterministic system which is in contrast with the intrinsic stochastic nature and behavi...

This paper studies possible robust control design methods in triple-stage actuation settings for achieving minimum position error signal (PES) while maintaining enough stability margins. Firstly, the sensitivity-decoupling design technique, is utilized to estimate the resulting increase in low frequency disturbance attenuation and servo bandwidth....

Track settling control for a hard disk drive with three actuators has been considered. The objective is to settle the read/write head on a specific track by following the minimum jerk trajectory. Robust output feedback model predictive control methodology has been utilized for the control design which can satisfy actuator constraints in the presenc...

We propose a macroscopic modeling framework for networks of freeways equipped with managed lanes. Two types of managed lane configuration are considered: full-access, where vehicles can switch between the general purpose (GP) and the managed lanes anywhere; and separated, where such switching is allowed only at certain locations called gates. The p...

We are experiencing an explosion in the amount of sensors measuring our activities and the world around us. These sensors are spread throughout the built environment and can help us perform state estimation and control of related systems, but they are often built and/or maintained by third parties or system users. As a result, by outsourcing system...

The propagation of traffic congestion along roads is a commonplace nonlinear phenomenon. When many roads are connected in a network, congestion can spill from one road to others as drivers queue to enter a congested road, creating further nonlinearities in the network dynamics. This paper considers the node model problem, which refers to methods fo...

The problem of maximizing bandwidth along anarterial is addressed here by use of two combined control actions:traffic light offsets and recommended speeds. The optimizationproblem has been enriched in order to account for traffic energyconsumption and network travel time, thus avoiding impracticalor undesirable solutions. A traffic microscopic simu...

A specific class of track seeking problem has been considered in this paper, where the HDD head should follow a simple predetermined trajectory. This process is considered to be relatively slow, therefore, only VCM is used as an actuator. The accuracy of this trajectory following problem can be improved using iterative learning control, ILC. Two di...

A direct adaptive feedforward control method for tracking repeatable runout (RRO) in bit patterned media recording (BPMR) hard disk drives (HDD) is proposed. The technique estimates the system parameters and the residual RRO simultaneously and constructs a feedforward signal based on a known regressor. An improved version of the proposed algorithm...

This paper discusses first order node models for macroscopic multi-commodity traffic simulation. There are two parts: (1) input-output flow computation based on input demand, input link priorities, split ratios that define how incoming flow is distributed between output links, and output supply; and (2) a traffic assignment algorithm for the case w...

In an age of ever-increasing penetration of GPS-enabled mobile devices, the potential of real-time "probe" location information for estimating the state of transportation networks is receiving increasing attention. Much work has been done on using probe data to estimate the current speed of vehicle traffic (or equivalently, trip travel time). While...

In hard disk drive (HDD) magnetic recording bit patterned media (BPM), data are written in predetermined paths. The deviation of these paths from the perfect circle is categorized as repeatable run-out (RRO) which needs to be tracked. An adaptive RRO following algorithm was developed in [1,2] in order to track the RRO. This algorithm uses models of...

We propose a macroscopic modeling framework for a network of roads and multi-commodity traffic. The proposed framework is based on the Lighthill-Whitham-Richards kinematic wave theory; more precisely, on its discretization, the Cell Transmission Model (CTM), adapted for networks and multi-commodity traffic. The resulting model is called the Link-No...

Aircraft Electric Power Systems (EPS) route power from generators to vital avionics loads by configuring a set of electronic control switches denoted as contactors. The external loads applied to an EPS, power requirement of the system, electrical component failure events, and the dynamics of the system are inherently uncertain. In this paper, we ad...

A computationally efficient model predictive controller for congestion control in freeway networks is presented in this paper. The controller utilizes a modified Link-Node Cell Transmission Model (LN-CTM) to simulate traffic state trajectories under the effect of ramp metering, variable speed limit control and compute performance objectives. The mo...

This paper presents an adaptive repetitive controller for active tracking (rejecting) of unknown periodic trajectories (disturbances). The proposed control law is based on a modified filtered- ${x}$ least mean squares (MFX-LMS) algorithm with a novel variable step size that improves the convergence rate and fades the steady state excess error in a...

The equilibria of a simplified Asymmetric Cell Transmission Model (ACTM model) and their stability properties are investigated to reveal some patterns of congestion.

Traffic management centers want to improve the performance of road networks and reduce congestion by actively managing the infrastructure of a freeway corridor. A promising avenue for proactive traffic management is the prediction of near-future traffic conditions in real time by using a traffic flow model. Important calibration parameters of such...

Input/ output feedback linearization and smoothed sliding control methods are used to control a floating offshore wind tur-bine on a barge platform in high wind speed in order to regu-late the power capture. The model of the turbine has the blade pitch angle as the input, generator speed, platform pitch angle and its derivative as the measurements,...

This paper presents an online adaptive algorithm to compensate damping and stiffness frequency mismatches in rate integrating Coriolis Vibratory Gyroscopes (CVGs). The proposed adaptive compensator consists of a least square estimator that estimates the damping and frequency mismatches, and an online compensator that corrects the mismatches. In ord...

In this paper we employ a modified filtered-x least mean squares (MFX-LMS) method to synthesis an adaptive repetitive controller for rejecting periodic disturbances at selective frequencies. We show how a MFX-LMS algorithm can be utilized when the reference signal is deterministic and periodic. A new adaptive step size is proposed with the motivati...

In non-uniform sampled systems, the measurements are arriving at irregular time intervals. However, the control is updated at regular time intervals. An observer is required to obtain the estimate of the states during the control update times. We evaluate two observer designs: A Kalman filter and a gain-scheduling observer. The Kalman filter has th...

An adaptive feedforward controller design for tracking repeatable runout (RRO) in bit patterned media recording (BMPR) is proposed for single stage hard disk drives (HDD). The technique is based on a modified filtered-x least mean squares (MFX-LMS) algorithm with deterministic periodic input, and a novel variable step size that boosts both the conv...

An adaptive predictor for a linear discrete time-varying stochastic system is proposed in this paper in order to forecast freeway traffic flow at a specific location over a one-hour horizon. Historical sensor data is first clustered by the K-means method to obtain the representative data pattern of the sensor. For each K-means cluster and using the...

In this paper, we present a case study on the macroscopic model calibration of the I-680 freeway in Northern California. This calibration effort posed two major challenges: 1) Only about half of the detectors on the mainline were functioning, and 2) no detection was available on the ramps. The only available ramp flow information were the Census co...

This paper presents an online adaptive controller to compensate damping and stiffness frequency mismatches in vibratory gyroscopes. This adaptive controller is running together with the method of averaging. The adaptive controller first estimates the effective damping and stiffness frequency mismatches using least square method and then compensates...

This paper presents an adaptive notch filter to achieve more accurate demodulation variables in the method of averaging. The main advantage of this notch filter is a very sharp attenuation gain at twice of the estimated resonance frequency, which is the main frequency component of the oscillatory noise in the demodulated variables. The position of...

Estimation of intersection origin-destination (OD) matrices is a frequently-encountered problem in transportation management operations. In particular, advanced traffic responsive arterial signalization management schemes rely on the accurate real-time estimation of vehicle queue lengths and turning ratios. This paper proposes a new method for esti...

This paper presents a novel robust H∞ control design for linear systems with periodic irregular sampling and regular actuation rates. A three-step design algorithm is developed to design a controller that achieves high robustness in terms of disk margin, and high performance in terms of root mean square (RMS) of 3σ-value of performance signal. The...

This paper considers robust controller design for track-following in hard disk drives (HDD) with irregular sampling of the position error signal (PES) but regular (clock-driven) control updates. This sampling and actuation behavior is modeled by applying a novel discretization method to a continuous-time model of an HDD, resulting in a discrete-tim...

This paper deals with the problem of irregular sampling rate in the discrete time track following control of read/write head in hard disk drives (HDD). Irregular sampling is gradually becoming an issue not to be ignored in modern HDDs. Current technological trend in the industry suggests an increasing need for assembling disks prewritten with servo...

The work described in this paper demonstrates a novel application of piezoelectric thin-film sensing technology by incorporating ZnO strain sensors into a hard disk drive (HDD) and deploying the sensors in a high-sample-rate feedback controller to suppress vibrations. First, thin-film ZnO sensors are fabricated directly onto a HDD suspension compon...

This paper analyzes the parameter identification of the macroscopic traffic flow model METANET. In previous papers, this calibration has been done by minimizing numerically the difference between the data and the prediction of the model. Results indicate that this optimization usually falls in quite suboptimal local minima, especially when there ar...

The estimation of traffic speed based on loop detector occupancy is a long-standing problem that is critical to traffic management and control. Single-loop detector stations are still popular in highway traffic systems in practice. Although dual loop stations could generate more accurate speed estimation with event data, updating single loops to du...

Vibratory micro rate integrating gyroscopes (MRIG) are conventionally modeled using the position and velocity of the gyroscope, as the state space variables. This work describes the dynamic analysis of a z-axis MRIG using an alternate set of dynamic variables, which are the angular momentum, the inner product between position and linear momentum ve...

This paper considers the output feedback H2 guaranteed cost control problem. In [1], it was observed that exploiting the solution of a discrete algebraic Riccati equation corresponding to an optimal full information control design allowed the output feedback control problem, for a fixed value of a design parameter, to be reduced to a so-called full...

In this paper, we present a model predictive controller to reduce road traffic congestion in freeway networks. The model predictive controller regulates traffic in the freeway through the use of ramp metering and variable speed limits. The controller uses a Link-Node Cell transmission model (LN-CTM) to represent freeway dynamics. We modify the stan...

This paper presents two methodologies for analyzing the H2 guaranteed cost performance of a discrete-time LTI system with norm-bounded structured uncertainty. The first methodology is based on semi-definite programming and the second methodology is based on smooth nonlinear convex optimization in which each function evaluation requires the solution...

We present an optimal control approach to freeway traffic congestion control. A Link-Node Cell transmission model (LN-CTM) is used to represent the freeway traffic dynamics. The approach searches for solutions represented by a combination of ramp metering and variable speed control. The optimization problem corresponding to the optimal control prob...