PRE2018 3 Group14
Group Members
| Name | Study | Student ID |
|---|---|---|
| Joost de Boer | Software Science | 1016745 |
| Yanic Dobler | Software Science | 1007100 |
| Leon Kersten | Software Science | 1006966 |
| Pietro Maschera | Psychology and Technology | 1220953 |
| Koen Vlaswinkel | Software Science | 1016271 |
Problem statement
Traffic management and prediction is a major concern and industry all over the world. City planers are always on the lookout for new methods, algorithms and procedures to guide the ever-growing car masses through the narrow streets of urban areas. These engineers focus mostly on developing means of controlling traffic light switching and while it is an important area to optimize, it has one looming downfall: It can only dictate the paste and rythm at which traffic flows through a specific intersection and not how traffic is split among possible intersections. This is where our product comes in, instead of pushing the state of the art on traffic light control, we aim to develop methodologies to direct single cars to take an alternative route with less traffic. This is a trivial problem when applied to a single car, but quite an algorithmic challenge when all traffic tries to find alternative routes in real time and they are able to communicate their current location to each other.
Objectives
- To evaluate the current state of the art on individual traffic advice.
- To evaluate the current state of the art of traffic light control based on actuators.
- To investigate potentials and threats when the above technologies work alongside each other.
- To interpret real-life traffic data provided in real time to feed the simulation (below).
- To develop an algorithm to solve the aforementioned problem.
- To develop a traffic simulation showing the effects with and without the algorithm on heavy traffic in urban areas.
Target users
Our project aims to provide motorized traffic (with and hopefully without drivers) with individual traffic advice, hence our main target users are traffic users. However, we aim to develop an algorithm and a simulation to show the effect of the algorithm, not a user friendly interface to make the algorithm usable by the average car user. Hence self-driving car manufacturers, city planners and traffic management engineers are also part of our target users as they ought to profit from the algorithm and simulation software when solving their own challenges.