issues
search
huawei-noah
/
SMARTS
Scalable Multi-Agent RL Training School for Autonomous Driving
MIT License
955
stars
190
forks
source link
Get actor of interest from scenario metadata and fix metrics
#1986
Closed
Adaickalavan
closed
1 year ago
Adaickalavan
commented
1 year ago
Added a specialised metric formula module for Driving SMARTS 2023.1 and 2023.2 benchmark.
Made all metrics as functions to be minimised, except the overall score which is to be maximised.
Driving SMARTS 2023.3 benchmark and the metrics module now uses
actor_of_interest_re_filter
from scenario metadata to identify the lead vehicle.
Minor fix in regular expression compilation of
actor_of_interest_re_filter
from scenario metadata.
Fixed acceleration and jerk computation in comfort metric, by ignoring vehicle position jitters smaller than a threshold.
actor_of_interest_re_filter
from scenario metadata to identify the lead vehicle.actor_of_interest_re_filter
from scenario metadata.