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doc/research/paf24/general/current_state.md

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+# Current state of the simulation
+
+**Summary:** The current state of the simulation is assessed by doing three runs of 20 mins (real world time), where all mistakes or anomalies are written down.
+
+- [Goal](#goal)
+- [Methodology](#methodology)
+- [Observed Errors Grouped by Domains](#observed-errors-grouped-by-domains)
+  - [Infrastructure](#infrastructure)
+  - [Testing and Validation](#testing-and-validation)
+  - [Perception](#perception)
+  - [Localization and Mapping](#localization-and-mapping)
+  - [Decision-Making](#decision-making)
+  - [Path Planning](#path-planning)
+  - [Control](#control)
+- [Raw notes](#raw-notes)
+  - [Run 1](#run-1)
+  - [Run 2](#run-2)
+  - [Run 3](#run-3)
+
+## Goal
+
+In order to understand the current state of the agent, it is crucial to assess the status quo and note the challenges it is faced with.
+
+## Methodology
+
+This assessment was done by three leaderboard runs in the CARLA simulator with the handover-state for PAF24. While doing so, all mistakes made by the agent have been noted, as well as possible anomalies occurring during the inspection.
+After the review, the mistakes have been grouped by the roles defined in the project in order to make it easier to address the challenges in the respective domains. **Note:** Some mistakes overlap and communication is key when tackling these issues.
+
+## Observed Errors Grouped by Domains
+
+### Infrastructure
+
+These issues relate to foundational aspects of the simulation environment and underlying software stability:
+
+- **Simulator Performance Degradation:**
+  - Simulation slows down over time (from .33 to .29 rate), potentially impacting reaction times and sensor data processing.
+- **Vehicle Despawning:**
+  - Random despawning of cars and potential timeout for stuck vehicles may interfere with the agent’s perception and response.
+
+---
+
+### Testing and Validation
+
+These errors highlight the gaps in the testing and validation process, particularly areas that may need further testing to ensure proper functioning in the real environment:
+
+- **Consistency in Object Detection:**
+  - Image segmentation flickering (e.g., police car with indicators), suggesting inadequate validation for dynamic objects with flashing lights.
+- **Vision Node Stability:**
+  - Vision node appears to freeze occasionally, indicating possible untested scenarios or bugs in the perception pipeline.
+- **Unrealistic Emergency Braking and Recovery Testing:**
+  - Unstable lane holding and recovery, resulting in inappropriate emergency braking maneuvers, suggests insufficient validation in complex recovery scenarios.
+- **Misclassification of Tree Trunks:**
+  - Trees being detected as cars, indicating the need for validation of object detection in diverse environmental conditions.
+
+---
+
+### Perception
+
+Errors within perception involve how the agent senses and understands its surroundings:
+
+- **Object Misclassification and Collision:**
+  - Tree trunks mistakenly detected as cars.
+  - Crashes into bikers and parked cars, suggesting perception failures in identifying and avoiding static and moving obstacles.
+- **Segmentation and Detection Instability:**
+  - Vision node freezing.
+  - Flickering segmentation for objects like police cars with indicators.
+- **Lane Detection and Holding Errors:**
+  - Difficulty in stable lane holding, leading to unexpected lane deviations and emergency braking.
+  - Misinterpretation of open car doors, causing lane intrusions without sufficient clearance.
+
+---
+
+### Localization and Mapping
+
+Issues with localization and mapping involve understanding and positioning within the environment:
+
+- **Positioning Errors in Turns:**
+  - Turns are too wide, leading the agent onto the walkway, indicating potential localization issues in tight maneuvers.
+- **Lane Holding and Position Drift:**
+  - Unstable lane holding with constant left and right drifting suggests potential mapping or localization inaccuracies.
+
+---
+
+### Decision-Making
+
+Errors in decision-making relate to the agent's ability to make appropriate choices in response to various scenarios:
+
+- **Right of Way Violations:**
+  - Fails to yield to oncoming traffic when turning left and when merging into traffic.
+  - Ignores open car doors when passing parked cars, causing dangerous close passes.
+- **Erroneous Stopping and Acceleration:**
+  - Stops unnecessarily at green lights and struggles to resume smoothly after stopping.
+  - Abrupt stopping and starting at green lights, potentially due to aggressive speed control.
+- **Repeated Mistakes in Overtaking and Lane Changes:**
+  - Treats temporary parked cars as regular vehicles to overtake without checking oncoming traffic, leading to unsafe lane changes.
+
+---
+
+### Path Planning
+
+Path planning issues include errors in determining the correct and safest path:
+
+- **Incorrect Overtaking Paths:**
+  - Attempts to overtake trees and temporary parked cars without considering oncoming traffic, showing flaws in path generation.
+- **Wide Turning Paths:**
+  - Takes overly wide turns that lead to walkway intrusions.
+- **Aggressive Lane Changes:**
+  - Lane change planning is overly aggressive, causing the vehicle to abruptly veer, triggering emergency stops to avoid collisions.
+
+---
+
+### Control
+
+Control-related issues concern the vehicle’s execution of planned actions, like maintaining speed and stability:
+
+- **Abrupt and Aggressive Speed Control:**
+  - Speed controller is too aggressive when accelerating from green lights, leading to abrupt stopping and starting.
+- **Instability in Lane Holding:**
+  - Inconsistent lane holding, particularly after getting unstuck, results in unexpected deviations onto walkways.
+- **Inconsistent Recovery Behavior:**
+  - Repeatedly gets stuck in various situations (e.g., speed limit signs or temporary parked cars) and fails to recover smoothly, indicating control issues in re-engaging the driving path.
+
+---
+
+## Raw notes
+
+Here are the raw notes in case misunderstandings have been made when grouping the mistakes
+
+### Run 1
+
+- Scared to get out of parking spot
+- lane not held causing problems when avoiding open car door
+- stopping for no apparent reason
+- does not keep lane (going left and right)
+- driving into still standing car at red light
+- impatient when waiting for light to turn green (after the crash, going back and forth)
+- abrupt stopping and going when light turns green without reason → speed controller too aggressive?
+- Problems to keep lane is causing emergency(?) brake maneuvers
+- vision node seems to be frozen ?
+- Detects bikers, crashes into them nonetheless
+- lane change very aggressive causing emergency stop in order to not go into oncoming traffic
+- gets stuck as a result
+- simulator despawns cars randomly
+- left turn does not give way to oncoming traffic when seeing them
+- does the turn too wide, gets onto walkway
+- simulation gets slower as time progresses, started at .33 rate, now at .29
+- gets stuck in front of speed limit sign after doing turn too wide
+- gets unstuck, lane holding too aggressive goes onto walkway again (integrator windup while being stuck?)
+- gets stuck again (→ unstuck behavior bad)
+- when getting unstuck, merges onto street without giving way to traffic on the road
+- drives into oncoming traffic, traffic on the same lane overtakes on the right side and does not stop
+- really stuck now
+
+### Run 2
+
+- merges without giving way to traffic
+- does not respect open car door
+- crashes into car in front when going after stop at red light
+- stops at green light
+- crashes into bikers
+- kid runs onto street, agent crashes into oncoming traffic, gets stuck
+- nudges away from the car it crashed into
+- is now free but does not move
+- crashes again
+- police car with indicators on standing on the side is crashed into
+- image segmentation for police car seems to be flickering
+- tree trunk has bounding box (are trees detected as cars?)
+
+### Run 3
+
+- does not give way when exiting a parking spot
+- LIDAR detects floor
+- trajectory for overtaking is wrong / no overtake needed
+- stops without reason
+- tries to "overtake" tree (detects tree as car)
+- playback ration temperature dependent likely
+- after emergency brake stops too long
+- left turn doesn't give way to oncoming traffic
+- recovery leads to oncoming traffic (left turn situation maybe doesn't recognize street?) 9 min
+- temporary parked car with indicators on counts as normal overtake (does not check oncoming traffic)
+- temporary parked car with indicators is the crux
+- Despawn time of cars ? Cars despawn when stuck → over time limit ?
+- Trajectory correctly generated, just too deep in the mistakes