with OpenStreetMap data.
The bachelor thesis about Uncertainty Quantification and multilane traffic simulation is finally linked in the wiki. A new release containing the multilane logic has been published.
The next few months will be attended to maintenance. In general, the project should be prepared for workers other than project's initiators. This includes:
- A lot of Documentation (besides existing comments)
- Writing/extending a Github Wiki including explanations about the code structure itself
- Include Travis CI for doing (JUnit) tests automatically on serverside.
- Improvements for interacting with the simulator, e.g. simple scenario creations for developers outside this project. The simulation code has many lines being able to support some interesting features like different driver profiles, but the simulator is not prepared to fully support these features' potential (mixed driver profiles at once).
In addition to that, some maintainability issues occured:
- In this project, JOGL is used as Java binding for the OpenGL API. Regarding this link in May 2018, JOGL hasn't been updated since 2015. Thus the project will use another binding. LWJGL is a good alternative.
- This project uses own math-code to handle calculations. It is helpful to "outsource" this code. JOML - Java OpenGL Math Library seems to meet our needs. JOML has been updated recently (May 2018), it is usable in concurrent execution environments and, on its main page, it has an own chapter about its usage with LWJGL (among others).
Last but not least, sometimes, when writing Java, you miss kind of handy "syntactical sugar". Two alternatives for Java are Kotlin vs. Scala. The syntax of both languages is fresh and modern. Since respectively Kotlin or Scala files can be added to a Java-project and their compiler are able to handle it, Kotlin and Scala are 100% interoperable with Java. Unfortunately, both languages aren't fully supported by many IDEs yet (Jan 2019). Therefore, for the moment, the traffic simulation code will still be written in Java.
Demonstrations and examples can be executed using gradle.
This project contains a gradle wrapper file, so you don't need to install it.
A (somewhat) stable demonstration can be executed from the master-branch.
For the execution commands and helpful information, please refer to our wiki.
For contributing the project, please refer to our contribution section.
- different vehicle types (inclusive different max velocities, acceleration functions etc.)
- static routing: fastest vs. shortest route
- streets' max velocity
- multilaned streets
- driver behaviour (e.g. in acceleration) limited by the vehicles "physical" behaviour
All following attributes can be en-/disabled.
- street priorities
- right-before-left XOR left-before-right XOR random
- more than one vehicle can cross a crossroad if the are not intersecting eachother's ways
- "friendly-standing-in-jam": If a vehicle has to wait at a crossroad, it relinquishes its right of way for an other vehicle that has not to wait.
- parse any map file in OSM MAP format
- start and end areas can be chosen using the shortcuts described in our wiki
- interrupt parsing or route calculations without exiting the main-ui
- routes can be serialized
- different style sheets can be used (the preferred style sheet has to be chosen in code for now)
- different vehicle colors depending on the vehicle's attributes (e.g. anger of its driver or the vehicle's velocity)
This software is still in an experimental state.