NetLogo Models Library:
IABM Textbook/chapter 5

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Traffic Grid Goal

If you download the NetLogo application, this model is included. You can also Try running it in NetLogo Web

ACKNOWLEDGMENT

This model is from Chapter Five of the book "Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo", by Uri Wilensky & William Rand.

• Wilensky, U. & Rand, W. (2015). Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo. Cambridge, MA. MIT Press.

This model is in the IABM Textbook folder of the NetLogo Models Library. The model, as well as any updates to the model, can also be found on the textbook website: http://www.intro-to-abm.com/.

ERRATA

The code for this model differs somewhat from the code in the textbook. The textbook code calls the STAY procedure, which is not defined here. One of our suggestions in the "Extending the model" section below does, however, invite you to write a STAY procedure.

WHAT IS IT?

The Traffic Grid Goal model simulates traffic moving in a city grid. It allows you to control traffic lights and global variables, such as the speed limit and the number of cars, and explore traffic dynamics.

This model extends the Traffic Grid model by giving the cars goals, namely to drive to and from work. It is the third in a series of traffic models that use different kinds of agent cognition. The agents in this model use goal-based cognition.

HOW IT WORKS

Each time step, the cars face the next destination they are trying to get to (either work or home) and attempt to move forward at their current speed. If their current speed is less than the speed limit and there is no car directly in front of them, they accelerate. If there is a slower car in front of them, they match the speed of the slower car and decelerate. If there is a red light or a stopped car in front of them, they stop.

Each car has a house patch and a work patch. (The house patch turns yellow and the work patch turns orange for a car that you are watching.) The cars will alternately drive from their home to work and then from their work to home.

There are two different ways the lights can change. First, the user can change any light at any time by making the light current, and then clicking CHANGE LIGHT. Second, lights can change automatically, once per cycle. Initially, all lights will automatically change at the beginning of each cycle.

HOW TO USE IT

Change the traffic grid (using the sliders GRID-SIZE-X and GRID-SIZE-Y) to make the desired number of lights. Change any other setting that you would like to change. Press the SETUP button.

At this time, you may configure the lights however you like, with any combination of auto/manual and any phase. Changes to the state of the current light are made using the CURRENT-AUTO?, CURRENT-PHASE and CHANGE LIGHT controls. You may select the current intersection using the SELECT INTERSECTION control. See below for details.

Start the simulation by pressing the GO button. You may continue to make changes to the lights while the simulation is running.

Buttons

SETUP -- generates a new traffic grid based on the current GRID-SIZE-X and GRID-SIZE-Y and NUM-CARS number of cars. Each car chooses a home and work location. All lights are set to auto, and all phases are set to 0%.

GO -- runs the simulation indefinitely. Cars travel from their homes to their work and back.

CHANGE LIGHT -- changes the direction traffic may flow through the current light. A light can be changed manually even if it is operating in auto mode.

SELECT INTERSECTION -- allows you to select a new "current" intersection. When this button is depressed, click in the intersection which you would like to make current. When you've selected an intersection, the "current" label will move to the new intersection and this button will automatically pop up.

WATCH A CAR -- selects a car to watch. Sets the car's label to its goal. Displays the car's house in yellow and the car's work in orange. Opens inspectors for the watched car and its house and work.

STOP WATCHING -- stops watching the watched car and resets its labels and house and work colors.

Sliders

SPEED-LIMIT -- sets the maximum speed for the cars.

NUM-CARS -- sets the number of cars in the simulation (you must press the SETUP button to see the change).

TICKS-PER-CYCLE -- sets the number of ticks that will elapse for each cycle. This has no effect on manual lights. This allows you to increase or decrease the granularity with which lights can automatically change.

GRID-SIZE-X -- sets the number of vertical roads there are (you must press the SETUP button to see the change).

GRID-SIZE-Y -- sets the number of horizontal roads there are (you must press the SETUP button to see the change).

CURRENT-PHASE -- controls when the current light changes, if it is in auto mode. The slider value represents the percentage of the way through each cycle at which the light should change. So, if the TICKS-PER-CYCLE is 20 and CURRENT-PHASE is 75%, the current light will switch at tick 15 of each cycle.

Switches

POWER? -- toggles the presence of traffic lights.

CURRENT-AUTO? -- toggles the current light between automatic mode, where it changes once per cycle (according to CURRENT-PHASE), and manual, in which you directly control it with CHANGE LIGHT.

Plots

STOPPED CARS -- displays the number of stopped cars over time.

AVERAGE SPEED OF CARS -- displays the average speed of cars over time.

AVERAGE WAIT TIME OF CARS -- displays the average time cars are stopped over time.

THINGS TO NOTICE

How is this model different than the Traffic Grid model? The one thing you may see at first glance is that cars move in all directions instead of only left to right and top to bottom. You will probably agree that this looks much more realistic.

Another thing to notice is that, sometimes, cars get stuck: as explained in the book this is because the cars are mesuring the distance to their goals "as the bird flies", but reaching the goal sometimes require temporarily moving further from it (to get around a corner, for instance). A good way to witness that is to try the WATCH A CAR button until you find a car that is stuck. This situation could be prevented if the agents were more cognitively sophisticated. Do you think that it could also be avoided if the streets were layed out in a pattern different from the current one?

THINGS TO TRY

You can change the "granularity" of the grid by using the GRID-SIZE-X and GRID-SIZE-Y sliders. Do cars get stuck more often with bigger values for GRID-SIZE-X and GRID-SIZE-Y, resulting in more streets, or smaller values, resulting in less streets? What if you use a big value for X and a small value for Y?

In the original Traffic Grid model from the model library, removing the traffic lights (by setting the POWER? switch to Off) quickly resulted in gridlock. Try it in this version of the model. Do you see a gridlock happening? Why do you think that is? Do you think it is more realistic than in the original model?

EXTENDING THE MODEL

Can you improve the efficiency of the cars in their commute? In particular, can you think of a way to avoid cars getting "stuck" like we noticed above? Perhaps a simple rule like "don't go back to the patch you were previously on" would help. This should be simple to implement by giving the cars a (very) short term memory: something like a previous-patch variable that would be checked at the time of choosing the next patch to move to. Does it help in all situations? How would you deal with situations where the cars still get stuck?

Can you enable the cars to stay at home and work for some time before leaving? This would involve writing a STAY procedure that would be called instead moving the car around if the right condition is met (i.e., if the car has reached its current goal).

At the moment, only two of the four arms of each intersection have traffic lights on them. Having only two lights made sense in the original Traffic Grid model because the streets in that model were one-way streets, with traffic always flowing in the same direction. In our more complex model, cars can go in all directions, so it would be better if all four arms of the intersection had lights. What happens if you make that modification? Is the flow of traffic better or worse?

RELATED MODELS

• "Traffic Basic": a simple model of the movement of cars on a highway.

• "Traffic Basic Utility": a version of "Traffic Basic" including a utility function for the cars.

• "Traffic Basic Adaptive": a version of "Traffic Basic" where cars adapt their acceleration to try and maintain a smooth flow of traffic.

• "Traffic Basic Adaptive Individuals": a version of "Traffic Basic Adaptive" where each car adapts individually, instead of all cars adapting in unison.

• "Traffic 2 Lanes": a more sophisticated two-lane version of the "Traffic Basic" model.

• "Traffic Intersection": a model of cars traveling through a single intersection.

• "Traffic Grid": a model of traffic moving in a city grid, with stoplights at the intersections.

• "Gridlock HubNet": a version of "Traffic Grid" where students control traffic lights in real-time.

• "Gridlock Alternate HubNet": a version of "Gridlock HubNet" where students can enter NetLogo code to plot custom metrics.

The traffic models from chapter 5 of the IABM textbook demonstrate different types of cognitive agents: "Traffic Basic Utility" demonstrates utility-based agents, "Traffic Grid Goal" demonstrates goal-based agents, and "Traffic Basic Adaptive" and "Traffic Basic Adaptive Individuals" demonstrate adaptive agents.

HOW TO CITE

This model is part of the textbook, “Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo.”

If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.

For the model itself:

• Rand, W., Wilensky, U. (2008). NetLogo Traffic Grid Goal model. http://ccl.northwestern.edu/netlogo/models/TrafficGridGoal. Center for Connected Learning and Computer-Based Modeling, Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL.

Please cite the NetLogo software as:

• Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Please cite the textbook as:

• Wilensky, U. & Rand, W. (2015). Introduction to Agent-Based Modeling: Modeling Natural, Social and Engineered Complex Systems with NetLogo. Cambridge, MA. MIT Press.

COPYRIGHT AND LICENSE

Copyright 2008 Uri Wilensky.

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu.

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