Privately Owned Vehicle Work Group Kick-Off Meeting - 2024/11/11 - Slot 1

[m-zain-khawaja]

Agenda

Provide a summary of the key developments which have already occurred in the PoV work group prior to its formation, including:

• SceneSeg Neural Network
• SceneSeg dataset
• Codebase summary
• Overall development goals and product plan

Attendees

• @m-zain-khawaja (Senior Tech Lead at AWF and Privately Owned Vehicle Work Group Chair)
• @mitsudome-r (AWF Technical Steering Committee Chair)
• @idorobotics (Project Manager at AWF)
• Narendar Selvaraj (Senior Member of Technical Staff at AMD)
• Jim Lee (Independent Researcher)

Discussion

• Introductions by attendees
• Run through of agenda items by @m-zain-khawaja
• A presentation was shared by @m-zain-khawaja on the SceneSeg Neural Network, describing the key network features and role of SceneSeg as forming a Safety Shield for autonomous vehicles by detecting all important foreground objects, irrespective of what that object is.
• A detailed run-through was presented of the codebase for the SceneSeg Neural Network and its inner workings by @m-zain-khawaja
• An overview was presented by @m-zain-khawaja of the overall neural network vision pipeline and high-level ensemble network, called AutoSeg
• Jim enquired whether static objects could also be detected by SceneSeg, and @m-zain-khawaja explained that given the training of the network on movable foreground objects, the main detection relates to all movable object categories, and that a separate neural network would be required to complete the vision-pipeline Safety Shield. This second neural network would calculate the true depth of pixels in the scene and use geometric 3D processing to detect the object-ness of every 3D point in the scene.
• @mitsudome-r enquired about publicising the AutoSeg repo (which contains the code for SceneSeg) and transferring ownership to Autoware, an action item was taken that @m-zain-khawaja would have a meeting with @mitsudome-r to transfer ownership of the AutoSeg repo to Autoware Foundation and make the repo public.
• @idorobotics requested a 15 minute slot in the next meeting to cover best practice guidelines for work-group meetings
• Jim also enquired about areas where he could help contribute to the code-base, to which @m-zain-khawaja replied that it would be very helpful if a literature review could be conducted on state-of-the-art approaches related to lane detection, path prediction and diversion-path prediction (drivable paths in road work scenarios), including what state-of-the art methods exist, what approaches they follow, performance metrics, and open-source datasets which can be used for network training.
• @m-zain-khawaja then shared a presentation covering the overall development goals and product strategy related to the privately owned vehicle development, alongside the development roadmap.
• Narendar shared that AMD has planes to develop an autonomous driving solution tailored for a highway lane-driving scenario, and that the Privately Owned Vehicle development seemed highly relevant to AMD's work, and followed a development strategy that closely aligned with that of AMD.
• Narendar also said that he would request some of his other colleagues in the machine learning team at AMD to join Slot 2 of this work-group meeting scheduled for later today.
• Jim also mentioned that he would be interested in continuing the discussion offline and asked how best he could get in touch with @m-zain-khawaja, to which @m-zain-khawaja replied that the Privately Owned Vehicle Work Group Channel in the Autoware Foundation Discord server was a good place for such discussions.

Zoom Meeting Video Recording

Video Meeting Link

Passcode to Access Recording: 5W2W4A^m

[idorobotics]

@m-zain-khawaja WG Best Practices training usually takes around 40-50 min

[m-zain-khawaja]

@idorobotics - thank you for your message, I can follow up on email to schedule a time for us to discuss 1-on-1 and go through work-group best practices so that the Slot 2 participants are able to get the main WG updates - is that okay?

[idorobotics]

The best practices training is for the benefit of all WG members. I can run the session during the slot 1 WG meeting, next Monday (18 Nov).

[m-zain-khawaja]

Sure - I will schedule it accordingly for Slot 1 next week