Mario Krumnow

Second Generation of Pollutant Emission Models for SUMO

Traffic puts a high burden on the environment in means of emitted pollutants and consumed fuel. Different attempts exist for reducing these impacts, ranging from traffic management actions to in-vehicle ITS solutions. When equipped with a model of vehicular pollutant emissions, microscopic traffic simulations are assumed to be helpful in predicting the performance of such approaches. SUMO includes a model for vehicular emissions since 2008. In the context of the projects COLOMBO and AMITRAN, two further models were implemented. Herein, these models are presented and discussed, pointing out the progress in emissions modelling.

Sumo as a Service – Building up a Web Service to Interact with SUMO

To interact with a simulation at runtime is often demanded within the scope of research studies. Therefore the microscopic traffic simulation software SUMO has a real-time I/O data interface (TraCI). This interface offers the possibility for a bidirectional communication between the user application and the simulation. Only few software implementations can handle that protocol, one of them is the Python TraCI Client being included into the simulation suite. Though depending on the preferred programming language, a specific implementation is needed. A solution designed to cover the problem is a standardized protocol interacting with SUMO, like the simple object access protocol (SOAP). This protocol can easily be integrated into a lot of programming languages, and is implemented as part of a Web service. This solution offers a lot of opportunities e.g. an unlimited number of clients.

Energy-efficient routing strategies based on real-time data of a local traffic management center

Electric cars form nowadays a competitive alternative to conventional cars with combustion engine. Unfortunately, there is still the problem of a relatively short range electric cars are able to reach which makes it quite unattractive to costumers. Many research projects deal with this issue to increase the range by following different approaches. E-City-Routing is one of those projects aiming to develop an energy-efficient routing algorithm especially for urban areas with its test field in Dresden, Germany. Thereby not only vehicle- and infrastructure-related impact factors are considered. Also dynamic traffic data provided by the local traffic management center such as current traffic situations and traffic signal states are taken into account in order to route electric cars with a minimum energy consumption through the city.

Modeling Mobility with Open Data

Introducing a new hobby for other people may inspire them to join with you. Reading, as one of mutual hobby, is considered as the very easy hobby to do. But, many people are not interested in this hobby. Why? Boring is the reason of why. However, this feel actually can deal with the book and time of you reading. Yeah, one that we will refer to break the boredom in reading is choosing modeling mobility with open data as the reading material.

Microscopic real-time traffic simulations to support advanced driver assistance systems

Over the past years improvements in the field of vehicle-2-infrastructure communication offer a lot of possibilities for interactive vehicle applications. The challenge of existing driver assistance algorithms is the fact that a lot of decisions are necessary to select the best driving strategy. The incoming information are mostly based on local sensor values. The disadvantage of this approach is that internal detectors can only gather information about the area really close to the vehicle. Within a new approach the traffic management center offers the possibility to evaluate specific driving regimes of single cars via a microscopic real-time traffic simulation. Furthermore, using online real-time data within the simulation might increase significantly a vehicles detection radius which helps finding an optimal driving strategy in current situations.

Real-Time Simulations Based on Live Detector Data – Experiences of Using SUMO in a Traffic Management System

An accurate real-time simulation of traffic behaviour requires a large amount of very specific data. It seems obvious that the use of currently measured data from the field is a great opportunity to lead a simulation as close to reality as possible. Once a realistic simulation of the traffic behaviour is available, many applications are imaginable. It is possible to simulate different scenarios to support the decision making process. Forecasts of the impacts of different management strategies can be analyzed fast and easily to help improving the quality of urban traffic. Furthermore a prediction of future traffic states can be made using currently measured data of the traffic situation.