Efficient Perception, Planning, and Control Algorithms for Vision-Based Automated Vehicles

Autonomous vehicles have limited computational resources; hence, their control systems must be efficient. The cost and size of sensors have limited the development of self-driving cars. To overcome these restrictions, this study proposes an efficient framework for the operation of vision-based automatic vehicles; the framework requires only a monocular camera and a few inexpensive radars. The proposed algorithm comprises a multi-task UNet (MTUNet) network for extracting image features and constrained iterative linear quadratic regulator (CILQR) and vision predictive control (VPC) modules for rapid motion planning and control. MTUNet is designed to simultaneously solve lane line segmentation, the ego vehicle's heading angle regression, road type classification, and traffic object detection tasks at approximately 40 FPS (frames per second) for 228 x 228 pixel RGB input images. The CILQR controllers then use the MTUNet outputs and radar data as inputs to produce driving commands for lateral and longitudinal vehicle guidance within only 1 ms. In particular, the VPC algorithm is included to reduce steering command latency to below actuator latency to prevent self-driving vehicle performance degradation during tight turns. The VPC algorithm uses road curvature data from MTUNet to estimate the correction of the current steering angle at a look-ahead point to adjust the turning amount. Including the VPC algorithm in a VPC-CILQR controller on curvy roads leads to higher performance than CILQR alone. Our experiments demonstrate that the proposed autonomous driving system, which does not require high-definition maps, could be applied in current autonomous vehicles.Comment: 10 figures, 13 page

The Outer Halo Globular Clusters of M31

We present Keck/HIRES spectra of 3 globular clusters in the outer halo of M31, at projected distances beyond ~80 kpc from M31. The measured recession velocities for all 3 globular clusters confirm their association with the globular cluster system of M31. We find evidence for a declining velocity dispersion with radius for the globular cluster system. Their measured internal velocity dispersions, derived virial masses and mass-to-light ratios are consistent with those for the bulk of the M31 globular cluster system. We derive old ages and metallicities which indicate that all 3 belong to the metal-poor halo globular cluster subpopulation. We find indications that the radial gradient of the mean metallicity of the globular cluster system interior to 50 kpc flattens in the outer regions, however it is still more metal-poor than the corresponding field stars at the same (projected) radius.Comment: 6 pages, 4 figures, 3 tables. Accepted for publication in MNRAS Letter

Electromagnetic Wave Theory and Applications

Contains table of contents for Section 3 and reports on four research projects.California Institute of Technology/Jet Propulsion Laboratory Agreement 959548National Aeronautics and Space Administration Grant NAGW-1617National Aeronautics and Space Administration Agreement 958461U.S. Navy - Office of Naval Research Grant N00014-89-J-1107U.S. Navy - Office of Naval Research Grant N00014-92-J-1616U.S. Navy - Office of Naval Research Grant N00014-92-J-4098Digital Equipment CorporationJoint Services Electronics Program Contract DAAL03-92-C-0001U.S. Navy - Office of Naval Research Agreement N00014-90-J-1002U.S. Navy - Office of Naval Research Agreement N00014-89-J-1019DEMACOU.S. Army Cold Regions Research and Engineering Laboratory Contract DACA89-93-K-0009U.S. Department of Transportation Agreement DTRS-57-92-C-00054TTD1Advanced Research Projects Agency/Consortium for Superconducting Electronics Contract MDA972-90-C-0021National Science Foundation Fellowship MIP 88-58764National Science Foundatio