Table of Contents
- Requirements
- The Environment
- Brief Run Level 3
- Brief Run Level 5
- Results
- Code Snippets
- Additional Info And Future Work
- To be able to display the behaviours of self driving cars through agent based modelling
- To be able to display the behaviours of none self driving cars through agent based modelling
- To be able to mimic the movements of pedestrians in a typical metropolitan setting
- To be able to allow the user to change the level of autonomy of the cars and analyse their changes
- To be able to record results based on the simulation
The simulation imitates a simple road with a small passage for the pedestrians to pass along, and a taffic light that changes in intervals, as the levels of autonomy change the way the cars behave when faced with a red light change, the model tries to imitate how the self driving cars would behave if they are in a compromised position through hacking, so while a low level autonomous car would drive uncontrollably if compromised a higher level car would still behave erratically but on a lesser scale, the level of autonomy currently ramges from 0 to 5, 5 being the highest.
These respective breed commands creates an set of all the breeds used in the simulation, an agentset can be seen as a collection of similar items and each item is known as the breed name.
;For example every item in the trees breed agentset is a tree.
breed [people person]
breed [cars car]
breed[houses house] ;
breed[trees tree]
breed[lights light]
breed[fires fire]
cars-own [
speed ; the current speed of the car
top-speed ; the maximum speed of the car
target-lane ; the desired lane of the car
patience ; the cars current level of patience
current-autonomy-level ; tracks the cars current level of autonomy
autonomous? ; Boolean variable to check if the car is autonomous or not
Law-Abiding? ; Checks if the car stops at a red light
max-patience ;The max patience for the cars, this is 100.
acceleration ;The rate at which cars accelerate
deceleration ;The rate at which cars decelerate
] ask n-of changed-number cars ;The use of n-of here was influence from this suggestion on stack overflow, linked here.
;https://stackoverflow.com/questions/60636497/how-to-change-the-colour-of-random-turtles-in-netlogo
[ if autonomy-level = 0 [set color blue set current-autonomy-level 0 set autonomous? true ]
if autonomy-level = 1 [set color blue + 1.0 set current-autonomy-level 1 set autonomous? true]
if autonomy-level = 2 [set color cyan set current-autonomy-level 2 set autonomous? true]
if autonomy-level = 3 [set color turquoise set current-autonomy-level 3 set autonomous? true]
if autonomy-level = 4 [set color green set current-autonomy-level 4 set autonomous? true]
if autonomy-level = 5 [set color lime set current-autonomy-level 5 set autonomous? true ]
]
end
to set-patience
;This procedure sets the patience of the autonomous cars.
ask cars with [autonomous? = true]
[
if autonomy-level = 0 [set current-autonomy-level 0 set patience (30 + random 15)]
if autonomy-level = 1 [set current-autonomy-level 1 set patience (40 + random 15)]
if autonomy-level = 2 [set current-autonomy-level 2 set patience (40 + random 15)]
if autonomy-level = 3 [set current-autonomy-level 3 set patience (45 + random 15)]
if autonomy-level = 4 [set current-autonomy-level 4 set patience (65 + random 15)]
if autonomy-level = 5 [set current-autonomy-level 5 set patience (85 + random 15)]
]
endThe PDF ReadMe file uploaded contains instructions on how to download NetLogo and run he program.
Future plans for the project
- Collect more precise information about self driivng cars
- Add more potential factors e.g Weather chages, Fire Hazards, Pollution etc
- Upscalling the GUI.