The enviroCar platform offers a broad range of data about traffic that can be used by different stakeholder groups. Fuel consumption is of special interest, e.g. when trying to understand the environmental impact of traffic or when trying to minimize fuel consumption by individual drivers. In enviroCar, there are currently two models to calculate fuel consumption: 1) using motor data from the on-board diagnostics (OBD) and 2) using GPS data from mobile phones running the enviroCar app.
During Google Summer of Code 2020, I will be working on an enviroCar Android app, which is one of the 52° North GSoC projects. The project is based on sustainable mobility. The main goal of the enviroCar app is to collect track data and analyze data to reduce the costs of running a car and to advance effective traffic planning.
The question is, is this data dependent on the car type? Of course yes! The data is fully dependent on the car type because of different engine displacement and power, which in term lead to different CO2 emissions. Currently, enviroCar app is flexible for creating artificial types of cars with user-defined attribute values, like adding engine displacement and power value to any undefined or nonexistent value.
There have been many packages in R developed for handling trajectory data, however each package is limited to a specific domain and does not provide functionality for general purpose trajectory analysis and visualization. This Google Summer of Code 2020 project aims to generalize trajectory analysis and visualization by creating a package named traviz.
This post will also be EGU Session ITS1.8/SSS1.1/EOS2.3/CL5.10/HS12.7/SM3.3 Display D2462 at EGU2020: Sharing Geoscience Online. We will participate in the chat on Monday, 4 May 2020, 10:45–12:30 to discuss our approach and findings.
Improving the provision of information for traffic management and environmentally conscious driving
The CITRAM project aims to improve traffic quality in cities with the help of floating car data provided by citizens. In the course of the project, the partners develop a set of coordinated tools addressing the aim of CITRAM. The citizen science platform enviroCar is used for the collection of floating car data (FCD) in three German cities. This FCD is used in newly developed postprocessing services that derive traffic quality characteristics as valuable input for traffic planers. To support citizens in an eco-friendly driving manner, the consortium also developed a traffic light assistant app ([ui!] ECOMAT). This enables a foresighted driving style in urban traffic. In order to collect a variety of trajectories, citizens are encouraged to collect data in designated campaigns while driving their day-to-day routes with combustion and electric cars. These collected trajectories are anonymized, stored and published under an open data policy in a central server.