Abstract
The SUMO traffic simulator is a mainstream tool that allows to model and analyse traffic and mobility scenarios.
Fully realistic scenarios can be appealing for many use cases, but they require an initial large investment of resources for their creation. In fact, the usual workflow comprises the manual creation of a statistics file with detailed information about the city and its properties, up to describing how many people live and work on each road. This step is followed by the application of the tool ActivityGEN to generate activity-based traffic.
Current alternatives are based on simple randomly generated traffic, such as by means of the tool RandomTrips.
We present a compromise between the two approaches, consisting of mathematical techniques to generate schools, city gates, population density with residential and industrial areas, and a city centre. We also introduce an accompanying tool, \tool, which implements the approach to create ActivityGEN statistics files automatically. Evaluation of generated scenarios shows that population and industry density, schools, and city-gates are placed realistically through testing on five representative Danish cities. The approach is also compared with the output of the tool RandomTrips and the LuST scenario.
Fully realistic scenarios can be appealing for many use cases, but they require an initial large investment of resources for their creation. In fact, the usual workflow comprises the manual creation of a statistics file with detailed information about the city and its properties, up to describing how many people live and work on each road. This step is followed by the application of the tool ActivityGEN to generate activity-based traffic.
Current alternatives are based on simple randomly generated traffic, such as by means of the tool RandomTrips.
We present a compromise between the two approaches, consisting of mathematical techniques to generate schools, city gates, population density with residential and industrial areas, and a city centre. We also introduce an accompanying tool, \tool, which implements the approach to create ActivityGEN statistics files automatically. Evaluation of generated scenarios shows that population and industry density, schools, and city-gates are placed realistically through testing on five representative Danish cities. The approach is also compared with the output of the tool RandomTrips and the LuST scenario.
| Original language | English |
|---|---|
| Title of host publication | MobiQuitous '20: MobiQuitous 2020 - 17th EAI International Conference on Mobile and Ubiquitous Systems : Computing, Networking and Services |
| Publisher | Association for Computing Machinery (ACM) |
| Publication date | 7 Dec 2020 |
| Pages | 357–365 |
| ISBN (Electronic) | 978-1-4503-8840-5 |
| DOIs | |
| Publication status | Published - 7 Dec 2020 |
| Event | 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services - Darmstadt, Germany Duration: 9 Dec 2020 → 11 Dec 2020 |
Conference
| Conference | 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services |
|---|---|
| Country/Territory | Germany |
| City | Darmstadt |
| Period | 09/12/2020 → 11/12/2020 |
Keywords
- Simulation of Urban MObility
- ActivityGEN
- Perlin noise
- k-Means algorithm (KMA)