To incorporate appropriate technology throughout the town that would support their autonomous vehicles project. by Ted Murphy https://padlet.com/tedandbern/towntech Tae Su en-us 2018-01-19 02:35:31 UTC 2023-03-29 04:51:05 UTC hello@padlet.com List of main concepts tkim9 https://padlet.com/tedandbern/towntech/wish/222671741 -  Bounding boxes
- Feature Maps
- Filters (Kernels) 
 - Over-fitting
- Point Clouds
 - Receptive Field
- Sensor Fusion
- Lidar Augmentation]]> 2018-01-19 02:56:03 UTC https://padlet.com/tedandbern/towntech/wish/222671741 Bounding boxes tkim9 https://padlet.com/tedandbern/towntech/wish/222673558 A rectangular area to efficiently cover all the affected area of some random shape. In the context of autonomous vehicles, the term is short for axis-aligned bounding box. It can be used to efficiently and effectively represent the area of collision to be avoided from two or more autonomous vehicles. ]]> 2018-01-19 03:12:11 UTC https://padlet.com/tedandbern/towntech/wish/222673558 Feature Maps (Self-organizing map) tkim9 https://padlet.com/tedandbern/towntech/wish/222673825 2018-01-19 03:14:36 UTC https://padlet.com/tedandbern/towntech/wish/222673825 Filters (kernels) tkim9 https://padlet.com/tedandbern/towntech/wish/222673869 A small matrix used to apply effects like the ones you might find in Photoshop or Gimp, such as blurring, sharpening, outlining or embossing. ]]> 2018-01-19 03:15:03 UTC https://padlet.com/tedandbern/towntech/wish/222673869 Over-fitting tkim9 https://padlet.com/tedandbern/towntech/wish/222674210 A modeling error which occurs when a function is too closely fit to a limited set of data points. Over-fitting the model generally takes the form of making an overly complex model. In reality, the data being studied often has some degree of error or random noise within it.]]> 2018-01-19 03:18:19 UTC https://padlet.com/tedandbern/towntech/wish/222674210 Point Clouds tkim9 https://padlet.com/tedandbern/towntech/wish/222674237 A collection of data points defined by a given coordinates system. In a 3D coordinates system, for example, a point cloud may define the shape of some real or created physical system.


]]> 2018-01-19 03:18:33 UTC https://padlet.com/tedandbern/towntech/wish/222674237 Receptive Field tkim9 https://padlet.com/tedandbern/towntech/wish/222674253 An area of the body surface over which a single sensory receptor, or its afferent nerve fiber, is capable of sensing stimuli. In some body area, e.g. face, ears, front paws, the sensitive areas are small; over the back they are larger.

]]> 2018-01-19 03:18:41 UTC https://padlet.com/tedandbern/towntech/wish/222674253 Sensor Fusion tkim9 https://padlet.com/tedandbern/towntech/wish/222674267 Sensor fusion is the aggregation of data from multiple sensors to gain a more accurate picture of the sensors' subject or environment than can be determined by any one sensor alone]]> 2018-01-19 03:18:48 UTC https://padlet.com/tedandbern/towntech/wish/222674267 tkim9 https://padlet.com/tedandbern/towntech/wish/224932541 2018-01-26 04:25:03 UTC https://padlet.com/tedandbern/towntech/wish/224932541 tkim9 https://padlet.com/tedandbern/towntech/wish/224932942 2018-01-26 04:29:08 UTC https://padlet.com/tedandbern/towntech/wish/224932942 tkim9 https://padlet.com/tedandbern/towntech/wish/224933261 2018-01-26 04:32:07 UTC https://padlet.com/tedandbern/towntech/wish/224933261 tkim9 https://padlet.com/tedandbern/towntech/wish/224933410 2018-01-26 04:33:39 UTC https://padlet.com/tedandbern/towntech/wish/224933410 tkim9 https://padlet.com/tedandbern/towntech/wish/224933545 2018-01-26 04:35:09 UTC https://padlet.com/tedandbern/towntech/wish/224933545 tkim9 https://padlet.com/tedandbern/towntech/wish/224933611 2018-01-26 04:35:47 UTC https://padlet.com/tedandbern/towntech/wish/224933611 tkim9 https://padlet.com/tedandbern/towntech/wish/224934012 2018-01-26 04:41:58 UTC https://padlet.com/tedandbern/towntech/wish/224934012 tkim9 https://padlet.com/tedandbern/towntech/wish/224934208 2018-01-26 04:44:58 UTC https://padlet.com/tedandbern/towntech/wish/224934208 Main features incorporated into the car tkim9 https://padlet.com/tedandbern/towntech/wish/227351825
]]> 2018-02-02 03:04:25 UTC https://padlet.com/tedandbern/towntech/wish/227351825 Lidar Augmentation tkim9 https://padlet.com/tedandbern/towntech/wish/227353474 Time-of-flight sensor where a laser-pulse is fired and the reflected pulse is recorded by a diode, the distance is then estimated as the velocity of light divided by times the time it takes for the laser pulse to return.
Prone to errors. One example is a situation where, on a road, there are autonomous vehicles which all use the lidar augmentation. This would result in vehicles processing incorrect 3D models of the surrounding environment. 
Encrypting the laser-pulse so that it is unique to a single vehicle


]]> 2018-02-02 03:18:38 UTC https://padlet.com/tedandbern/towntech/wish/227353474 tkim9 https://padlet.com/tedandbern/towntech/wish/227354274 2018-02-02 03:25:39 UTC https://padlet.com/tedandbern/towntech/wish/227354274 tkim9 https://padlet.com/tedandbern/towntech/wish/227354306 2018-02-02 03:25:49 UTC https://padlet.com/tedandbern/towntech/wish/227354306 tedandbern https://padlet.com/tedandbern/towntech/wish/241202659 Potential V2I Safety Applications crash scenario mitigation opportunities include:
  • Intersection safety
  • Roadway departure prevention
  • Speed management
  • Transit safety and operations
  • Commercial vehicle enforcement and operations
  • At-grade rail crossing operations
  • Priority assignment for emergency vehicles
]]> 2018-03-13 04:36:56 UTC https://padlet.com/tedandbern/towntech/wish/241202659 Intelligent Transport Systems tedandbern https://padlet.com/tedandbern/towntech/wish/241202933 https://www.its.dot.gov/research_archives/safety/v2i_comm_plan.htm]]> 2018-03-13 04:40:16 UTC https://padlet.com/tedandbern/towntech/wish/241202933 A vehicle-to-infrastructure communication basedalgorithm for urban traffic control tedandbern https://padlet.com/tedandbern/towntech/wish/241203113  We present in this paper a new algorithm for urban traffic light control with mixed traffic (communicating and non communicating vehicles) and mixed infrastructure (equipped and unequipped junctions). We call equipped junction here a junction with a traffic light signal (TLS) controlled by a road side unit (RSU). On such a junction, the RSU manifests its connectedness to equipped vehicles by broadcasting its communication address and geographical coordinates. The RSU builds a map of connected vehicles approaching and leaving the junction. The algorithm allows the RSU to select a traffic phase, based on the built map. The selected traffic phase is applied by the TLS; and both equipped and unequipped vehicles must respect it. The traffic management is in feedback on the traffic demand of communicating vehicles. We simulated the vehicular traffic as well as the communications. The two simulations are combined in a closed loop with visualization and monitoring interfaces. Several indicators on vehicular traffic (mean travel time, ended vehicles) and IEEE 802.11p communication performances (endto-end delay, throughput) are derived and illustrated in three dimension maps. We then extended the traffic control to a urban road network where we also varied the number of equipped junctions. Other indicators are shown for road traffic performances in the road network case, where high gains are experienced in the simulation results ]]> 2018-03-13 04:41:58 UTC https://padlet.com/tedandbern/towntech/wish/241203113 Research on road works and improving traffic flow using V2I and V2V with RSU able to signal over 2kms tedandbern https://padlet.com/tedandbern/towntech/wish/241237388 https://pdfs.semanticscholar.org/b58b/72b4111aebc02cc71886f50736b1e67339b9.pdf]]> 2018-03-13 08:19:55 UTC https://padlet.com/tedandbern/towntech/wish/241237388