ITS Berkeley

Viability-based computation of spatially constrained minimum time trajectories for an autonomous underwater vehicle: implementation and experiments

Tinka, Andrew
Diemer, S.
2009

A viability algorithm is developed to compute the constrained minimum time function for general dynamical systems. The algorithm is instantiated for a specific dynamics (Dubin's vehicle forced by a flow field) in order to numerically solve the minimum time problem. With the specific dynamics considered, the framework of hybrid systems enables us to solve the problem efficiently. The algorithm is implemented in C using epigraphical techniques to reduce the dimension of the problem. The feasibility of this optimal trajectory algorithm is tested in an experiment with a light autonomous...

Path and travel time inference from GPS probe vehicle data

Hunter, Timothy
Herring, Ryan
Bayen, Alexandre M.
2009

We consider the problem of estimating real-time traffic conditions from sparse, noisy GPS probe vehicle data. We specifically address arterial roads, which are also known as the secondary road network (highways are considered the primary road network). We consider several estimation problems: historical traffic patterns, real-time traffic conditions, and forecasting future traffic conditions. We assume that the data available for these estimation problems is a small set of sparsely traced vehicle trajectories, which represents a small fraction of the total vehicle flow through the network. We...

Viability-based computation of spatially constrained minimum time trajectories for an autonomous underwater vehicle: implementation and experiments

Tinka, Andrew
Diemer, S.
Bayen, Alexandre M.
2009

A viability algorithm is developed to compute the constrained minimum time function for general dynamical systems. The algorithm is instantiated for a specific dynamics (Dubin's vehicle forced by a flow field) in order to numerically solve the minimum time problem. With the specific dynamics considered, the framework of hybrid systems enables us to solve the problem efficiently. The algorithm is implemented in C using epigraphical techniques to reduce the dimension of the problem. The feasibility of this optimal trajectory algorithm is tested in an experiment with a light autonomous...

Lagrangian sensing: traffic estimation with mobile devices

Work, Daniel B.
Tossavainen, Olli‐Pekka
Bayen, Alexandre M.
2009

An inverse modeling algorithm is developed to reconstruct the state of traffic (velocity field) on highways from GPS measurements gathered from mobile phones traveling on-board vehicles. The algorithm is based on ensemble Kalman filtering (EnKF), to overcome the nonlinearity and non-differentiability of a distributed highway traffic model for velocity. The algorithm is implemented in an architecture which includes GPS enabled phones and a privacy aware data collection infrastructure based on the novel concept of virtual trip lines (a technology developed by Nokia). The data...

Optimal Sensor Placement for Freeway Travel Time Estimation

Ban, Xuegang (Jeff)
Bayen, Alexandre M.
Herring, Ryan
2009

This article presents a modeling framework and a polynomial solution algorithm for determining optimal locations of point detectors used to compute freeway travel times. First, an objective function is introduced to minimize the deviation of estimated and actual travel times of all individual sub-segments of a freeway route. By discretizing the problem in both time and space, we formulate it as a dynamic programming model, which can be solved via a shortest path search in an acyclic graph. Numerical examples are provided to illustrate the model and algorithm using microscopic traffic...

Improved Power Grid Stability and Efficiency with a Building-Energy Cyber-Physical System

Piette, Mary Ann
Sohn, Michael
Bayen, Alexandre M.
2009

This position article outlines some challenges of demand response in the context of the power grid and its interaction with buildings. We describe significant issues in energy-efficient operation of buildings, in particular questions such as system reliability, risk management and environmental impact. We also outline a strategy for the development of new technologies for a cyber-physical infrastructure system that integrates management of smart buildings with management of the power grid. Specific emphasis is given to the interaction of physical and computational processes through sensing,...

Minimal Error Certificates for Detection of Faulty Sensors Using Convex Optimization

Claudel, Christian G.
Nahoum, Matthieu
Bayen, Alexandre M.
2009

This article proposes a new method for sensor fault detection, applicable to systems modeled by conservation laws. The state of the system is modeled by a Hamilton-Jacobi equation, in which the Hamiltonian is uncertain. Using a LaxHopf formula, we show that any local measurement of the state of the system restricts the allowed set of possible values of other local measurements. We derive these constraints explicitly for arbitrary Hamilton-Jacobi equations. We apply this framework to sensor fault detection, and pose the problem finding the minimal possible sensor error (minimal error...

Flatness-Based Control of Open-Channel Flow in an Irrigation Canal Using SCADA [Applications of Control]

Rabbani, Tarek
Munier, Simon
Dorchies, David
Malaterre, Pierre-olivier
Bayen, Alexandre
Litrico, Xavier
2009

This article applied a flatness-based controller to an open channel hydraulic canal. The controller was tested by computer simulation using Saint-Venant equations as well as by real experimentation on the Gignac canal in southern France. The initial model that assumes constant lateral withdrawals is improved to take into account gravitational lateral withdrawals, which vary with the water level. Accounting for gravitational lateral withdrawals decreased the steady-state error from 6.2% (constant lateral withdrawals assumption) to 1% (gravitational lateral withdrawals assumption). The...

Kernel Regression for Travel Time Estimation via Convex Optimization

Blandin, Sébastien
El Ghaoui, Laurent
Bayen, Alexandre
2009

We develop an algorithm aimed at estimating travel time on segments of a road network using a convex optimization framework. Sampled travel time from probe vehicles are assumed to be known and serve as a training set for a machine learning algorithm to provide an optimal estimate of the travel time for all vehicles. A kernel method is introduced to allow for a non-linear relation between the known entry times and the travel times that we want to estimate. To improve the quality of the estimate we minimize the estimation error over a convex combination of known kernels. This problem is...

Kalman Filter Based Estimation of Flow States in Open Channels Using Lagrangian Sensing

Rafiee, Mohammad
Wu, Qingfang
Bayen, Alexandre M.
2009

In this article, we investigate real-time estimation of flow state in open channels using the measurements obtained from Lagrangian sensors (drifters). One-dimensional Shallow Water Equations (SWE), also known as Saint-Venant equations, are used as the mathematical model for the flow. After linearizing and discretizing the PDEs using an explicit linear scheme, we construct a linear state-space model of the flow. The Kalman filter is then used to estimate the states by incorporating the measurements obtained from passive drifters. Drifters which are equipped with GPS receivers move with the...