Highway Env Versions Save

• Fix collision reward in parking env
• Minor update of documentation and workflows
• Minor update of example notebooks
• Update rendering logic

• fix vehicle order in occupancy grid obs
• fix broken seeding implementation
• support numpy types for discrete actions
• use Runge-Kutta 4 integration for dynamical continuous actions, making the dynamics make more stable
• use gymnasium rather than gym

Fixes https://github.com/eleurent/highway-env/issues/400

• Change the step / reset / render interfaces to match the new API of gym 0.26
• Drop support for gym <0.26

• fix a bug in generating discrete actions from continuous actions
• fix more bugs related to changes in gym's latest versions
• new intersection-env variant with continuous actions
• add longitudinal/lateral/angular offsets to the lane as part of the kinematics observation's features
• add more configurable options for reward function and termination conditions
• add configurable min/max speed for continuous actions
• bug fix for reward computation in the multi-agent setting
• add get_available_actions for MultiAgentAction
• fix various deprecation warnings
• add a multi-objective version of HighwayEnv

Huge thanks to contributors @zerongxi, @TibiGG, @KexianShen, @lorandcheng

• Add documentation on continuous actions
• Fix various bugs or imprecision in collision checks and obstacles rendering
• Image observations are now centered on the observer vehicle
• Fix the lane change behaviour in some situations
• Add TupleObservation, which is a union of several observation types
• Improve the accuracy of the LidarObservation
• Add support for PolyLane, and methods to save/load road networks from a config
• Fix steering wheel / angle conversion
• Change of the velocity term projection in the reward function
• Add support for latest gym versions (>=0.22) which dropped the Monitor wrapper
• Add a copy of the GoalEnv interface which was removed from gym

This release introduces additional content:

• a new continuous control environment, racetrack-v0, where the agent must learn to steer and follow the tracks, while avoiding other vehicles
• a new "on_road" layer in the OccupancyGrid observation type, which enables the observer to see the drivable space
• a new "align_to_vehicle_axes" option in the OccupancyGrid observation type, which renders the observation in the local vehicle frame
• a new DiscreteAction action type, which discretizes the original ContinuousAction type. This allows to do low-level control, but with a small discrete action space (e.g. for DQN). Note that this is different from the DiscreteMetaAction type, which implements its own low-level sub-policies.
• new example scripts and notebooks for training agents, such as a PPO continuous control policy for racetrack-v0.
• updated documentation

This release contains

• A few fixes for compatibility with SB3
• Some changes for video rendering and framerate
• highway-fast-v0: a faster variant of highway-v0 to train/debug models more quickly

Minor update with

• different handling of image observations + example script with stable baselines
• small changes in the dynamical model