Author name cluster

David Wilkie

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5 papers

2 author rows

TIST Journal 2015 Journal Article

Sensing the Pulse of Urban Refueling Behavior

Fuzheng Zhang
Nicholas Jing Yuan
David Wilkie
Yu Zheng
Xing Xie

Urban transportation is an important factor in energy consumption and pollution, and is of increasing concern due to its complexity and economic significance. Its importance will only increase as urbanization continues around the world. In this article, we explore drivers’ refueling behavior in urban areas. Compared to questionnaire-based methods of the past, we propose a complete data-driven system that pushes towards real-time sensing of individual refueling behavior and citywide petrol consumption. Our system provides the following: detection of individual refueling events (REs) from which refueling preference can be analyzed; estimates of gas station wait times from which recommendations can be made; an indication of overall fuel demand from which macroscale economic decisions can be made, and a spatial, temporal, and economic view of urban refueling characteristics. For individual behavior, we use reported trajectories from a fleet of GPS-equipped taxicabs to detect gas station visits. For time spent estimates, to solve the sparsity issue along time and stations, we propose context-aware tensor factorization (CATF), a factorization model that considers a variety of contextual factors (e.g., price, brand, and weather condition) that affect consumers’ refueling decision. For fuel demand estimates, we apply a queue model to calculate the overall visits based on the time spent inside the station. We evaluated our system on large-scale and real-world datasets, which contain 4-month trajectories of 32,476 taxicabs, 689 gas stations, and the self-reported refueling details of 8,326 online users. The results show that our system can determine REs with an accuracy of more than 90%, estimate time spent with less than 2 minutes of error, and measure overall visits in the same order of magnitude with the records in the field study.

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ICRA Conference 2012 Conference Paper

LQG-obstacles: Feedback control with collision avoidance for mobile robots with motion and sensing uncertainty

Jur van den Berg
David Wilkie
Stephen J. Guy
Marc Niethammer
Dinesh Manocha

This paper presents LQG-Obstacles, a new concept that combines linear-quadratic feedback control of mobile robots with guaranteed avoidance of collisions with obstacles. Our approach generalizes the concept of Velocity Obstacles [3] to any robotic system with a linear Gaussian dynamics model. We integrate a Kalman filter for state estimation and an LQR feedback controller into a closed-loop dynamics model of which a higher-level control objective is the “control input”. We then define the LQG-Obstacle as the set of control objectives that result in a collision with high probability. Selecting a control objective outside the LQG-Obstacle then produces collision-free motion. We demonstrate the potential of LQG-Obstacles by safely and smoothly navigating a simulated quadrotor helicopter with complex non-linear dynamics and motion and sensing uncertainty through three-dimensional environments with obstacles and narrow passages.

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AAAI Conference 2011 Conference Paper

Self-Aware Traffic Route Planning

David Wilkie
Jur van den Berg
Ming Lin
Dinesh Manocha

One of the most ubiquitous AI applications is vehicle route planning. While state-of-the-art systems take into account current trafﬁc conditions or historic trafﬁc data, current planning approaches ignore the impact of their own plans on the future trafﬁc conditions. We present a novel algorithm for self-aware route planning that uses the routes it plans for current vehicle trafﬁc to more accurately predict future trafﬁc conditions for subsequent cars. Our planner uses a roadmap with stochastic, timevarying trafﬁc densities that are deﬁned by a combination of historical data and the densities predicted by the planned routes for the cars ahead of the current traf- ﬁc. We have applied our algorithm to large-scale traf- ﬁc route planning, and demonstrated that our self-aware route planner can more accurately predict future traf- ﬁc conditions, which results in a reduction of the travel time for those vehicles that use our algorithm.

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IROS Conference 2009 Conference Paper

Generalized velocity obstacles

David Wilkie
Jur van den Berg
Dinesh Manocha

We address the problem of real-time navigation in dynamic environments for car-like robots. We present an approach to identify controls that will lead to a collision with a moving obstacle at some point in the future. Our approach generalizes the concept of velocity obstacles, which have been used for navigation among dynamic obstacles, and takes into account the constraints of a car-like robot. We use this formulation to find controls that will allow collision free navigation in dynamic environments. Finally, we demonstrate the performance of our algorithm on a simulated car-like robot among moving obstacles.

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ICRA Conference 2008 Conference Paper

Toward a multi-disciplinary model for bio-robotic systems

Richard Primerano
David Wilkie
William C. Regli

The design of robotic systems involves contributions from several areas of science and engineering. Electrical, mechanical and software components must be integrated to form the final system. Increasingly, simulation tools are being introduced into the design flow as a means to verify the performance of particular subsystems. In order to accurately simulate the complete robotic system we propose a framework that allows designers to describe the robotic system as an interconnection of mechanical, electrical, and software components, with well defined mechanisms for communicating with each other. Through this, we form a multi-disciplinary model that captures both the dynamics of the individual subsystems, and the dynamics resulting from the interconnection of the above subsystems. As a case-study, we will apply the framework to a biologically inspired robotic snake.

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