Institution
Ford Motor Company
Company•Dearborn, Michigan, United States•
About: Ford Motor Company is a company organization based out in Dearborn, Michigan, United States. It is known for research contribution in the topics: Internal combustion engine & Clutch. The organization has 36123 authors who have published 51450 publications receiving 855200 citations. The organization is also known as: Ford Motor & Ford Motor Corporation.
Topics: Internal combustion engine, Clutch, Control theory, Torque, Exhaust gas
Papers published on a yearly basis
Papers
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TL;DR: This initial experience with intravenous cangrelor during PCI suggests an acceptable risk of bleeding and adverse cardiac events while achieving rapid, reversible inhibition of platelet aggregation via competitive binding to the ADP P2Y12 platelet receptor with less prolongation of bleeding time then the glycoprotein IIb/IIIa receptor antagonist abciximab.
210 citations
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07 Nov 2002TL;DR: Extensive experimentation and comparisons using real data, different features, and different classifiers demonstrate the superiority of the proposed approach which has achieved an average accuracy of 94.81% on completely novel test images.
Abstract: On-road vehicle detection is an important problem with application to driver assistance systems and autonomous, self-guided vehicles. The focus of this paper is on the problem of feature extraction and classification for rear-view vehicle detection. Specifically, we propose using Gabor filters for vehicle feature extraction and support vector machines (SVM) for vehicle detection. Gabor filters provide a mechanism for obtaining some degree of invariance to intensity due to global illumination, selectivity in scale, and selectivity in orientation. Basically, they are orientation and scale tunable edge and line detectors. Vehicles do contain strong edges and lines at different orientation and scales, thus, the statistics of these features (e.g., mean, standard deviation, and skewness) could be very powerful for vehicle detection. To provide robustness, these statistics are not extracted from the whole image but rather are collected from several subimages obtained by subdividing the original image into subwindows. These features are then used to train a SVM classifier. Extensive experimentation and comparisons using real data, different features (e.g., based on principal components analysis (PCA)), and different classifiers (e.g., neural networks (NN)) demonstrate the superiority of the proposed approach which has achieved an average accuracy of 94.81% on completely novel test images.
210 citations
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01 Jan 2010TL;DR: In this paper, two different approaches based on Model Predictive Control (MPC) for obstacle avoidance with autonomous vehicles are presented, one solving a single nonlinear MPC problem and the second using a hierarchical scheme.
Abstract: Two frameworks based on Model Predictive Control (MPC) for obstacle avoidance with autonomous vehicles are presented. A given trajectory represents the driver intent. An MPC has to safely avoid obstacles on the road while trying to track the desired trajectory by controlling front steering angle and differential braking. We present two different approaches to this problem. The first approach solves a single nonlinear MPC problem. The second approach uses a hierarchical scheme. At the high-level, a trajectory is computed on-line, in a receding horizon fashion, based on a simplified point-mass vehicle model in order to avoid an obstacle. At the low-level an MPC controller computes the vehicle inputs in order to best follow the high level trajectory based on a nonlinear vehicle model. This article presents the design and comparison of both approaches, the method for implementing them, and successful experimental results on icy roads.Copyright © 2010 by ASME
210 citations
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05 May 1993TL;DR: In this paper, a space frame for an automotive vehicle included a plurality of hoop shaped structural member (12,14) and a structure (28,38,40) disposed on adjacent portions of the structural members for allowing nesting engagement therebetween to form a substantially flush outer surface.
Abstract: A space frame for an automotive vehicle included a plurality of hoop shaped structural member (12,14) and a structure (28,38,40) disposed on adjacent portions of the structural members for allowing nesting engagement therebetween to form a substantially flush outer surface (22,36) between the structural members.
209 citations
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TL;DR: In this article, a turbulent flame propagation model that is dependent on the structure of the turbulent flow field is formulated and applied to combustion in a spark-ignition engine, where combustion is assumed to proceed in a laminar fashion across the microscale.
209 citations
Authors
Showing all 36140 results
Name | H-index | Papers | Citations |
---|---|---|---|
Anil K. Jain | 183 | 1016 | 192151 |
Markus Antonietti | 176 | 1068 | 127235 |
Christopher M. Dobson | 150 | 1008 | 105475 |
Jack Hirsh | 146 | 734 | 86332 |
Galen D. Stucky | 144 | 958 | 101796 |
Federico Capasso | 134 | 1189 | 76957 |
Peter Stone | 130 | 1229 | 79713 |
Gerald R. Crabtree | 128 | 371 | 60973 |
Douglas A. Lauffenburger | 122 | 705 | 55326 |
Abass Alavi | 113 | 1298 | 56672 |
Mark E. Davis | 113 | 568 | 55334 |
Keith Beven | 110 | 514 | 61705 |
Naomi Breslau | 107 | 254 | 42029 |
Fei Wang | 107 | 1824 | 53587 |
Jun Yang | 107 | 2090 | 55257 |