I am trying to control the car intelligently by setting it waypoints in the code. The problem is that the car still needs user input to go from point A to Point B. Code: bng.load_scenario(scenario) bng.start_scenario() # Make the vehicle's AI span the map vehicle.ai_set_mode('span') vehicle.ai_set_target(pos=(-713, 70, 118)) How to make car AI control using python. Secondly, how to set user input to false. The options are Code: * ``disabled``: Turn the AI off (default state) * ``random``: Drive from random points to random points on the map * ``span``: Drive along the entire road network of the map * ``manual``: Drive to a specific waypoint, target set separately * ``chase``: Chase a target vehicle, target set separately * ``flee``: Flee from a vehicle, target set separately * ``stopping``: Make the vehicle come to a halt (AI disables itself once the vehicle stopped.)
Can you provide me the directions that how I will use the lua for AI control of cars. I know how to declare waypoints and car in the game. What I have to do next.
No, it’s because it’s a complex question so he would need to ask people like estama or other programmers for info. Although the update is near, it’s been speculated for the 21st of December with pretty good evidence backing it up.
tdev said it will be released a couple days before Christmas and someone mentioned large updates are almost always on Fridays so therefore the only date that fits is the 21st. Although there is no way to say for sure, this is the best guess. Also this is incredibly off topic so let’s not discuss this any further. (I can’t be bothered to find the links because I’m on mobile but it’s either in update speculation thread or the ‘where are we going?’ Thread)
Guys. I add the 5 pathway points and 3 cars to prefab file. Now i want the cars to follow the waypoint (AI control) in the scenario. How will i do that with the lua code.
I recommend you to download this scenario and examine how it is made: https://www.beamng.com/resources/running-late-gull.6139/
It's been in development for a few months, mainly exposing BeamNG functionality in a research-oriented way. One of the more fun uses will be developing OpenAI Gym environments for deep learning experiments, though we just now started that with a simple race around the WC USA track. More to come.