Randomation-Vehicle-Physics VS ecs

I've seen AI cars with physics in this project https://github.com/JustInvoke/Randomation-Vehicle-Physics Maybe you can take a look at the code and see how they implement it. Also there is an assest called Universal Vehicle Controller which has AI with physics, and a link to a demo if you want to try it before.

Randomation vehicle physics at: https://github.com/JustInvoke/Randomation-Vehicle-Physics

Elastic Common Data Model (ECS) sample data: Although intended for the Elastic Stack, you can adapt these sample logs for use in Splunk. The repository contains logs from various sources, such as network traffic, security events, and web server logs: https://github.com/elastic/ecs/tree/master/generated/samples

// Base represents the base schema type defined by the Elastic Common Schema (ECS). // // See https://github.com/elastic/ecs/blob/main/schemas/base.yml type Base struct { Timestamp *time.Time json:"@timestamp" Tags string json:"tags,omitempty" Labels map[string]any json:"labels,omitempty" Message string json:"message,omitempty" }

To move ECS ahead, we're adding the latest data types from current Elasticsearch like wildcard (https://github.com/elastic/ecs/blob/master/experimental/generated/elasticsearch/7/template.json#L30) or histogram. It won't be successful if we are only tied to the common denominator of data types in terms of space efficiency, performance, features,...