Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Intelligent Algorithm Finds Available Carsharing Vehicles

22.01.2015

A new program will make it easier to combine different modes of transport. Siemens is developing a service for predicting the availability of carsharing vehicles at a given location at specific times.

The forecasting tool will be incorporated into the integrated SiMobility Connect mobility platform, which links carsharing firms, public transport companies, taxis, and bike-rental services.

Customers will then be able to use just one app to plan all segments of their trip and immediately see which combinations of transport modes are most advantageous at the moment or at a later time. The goal is to make the planning of inter-modal journeys (combinations of different forms of transport) more effective in order to combat growing traffic congestion in metropolitan areas. The new software also incorporates car-sharing users whose cars do not have a permanent parking space.

This "free floating carsharing" is a relatively new concept made possible by state-of-the-art information technology systems. The vehicles here do not have a permanent location but can instead be parked anywhere within a specific region.

They then report their position to a control center. Users can then check the current availability of vehicles in their area with an app and book a car right when they're ready to take it. This system offers the benefit of great flexibility because vehicles no longer have to be returned to a specific place at a set time. Planning is more difficult, however, because the cars cannot be booked well in advance and users cannot be sure whether a vehicle will be available at an acceptable distance from the desired location in the future.

Position of all carsharing vehicles in realtime

The researchers from Siemens Corporate Technology focused on this aspect. They developed an algorithm that uses realtime data on the position of all carsharing vehicles to predict where and when they will be available in the future. The process begins with historical data on the locations and availability of all vehicles over time.

When such data is monitored over a longer period, it becomes possible to recognize patterns in the distribution of vehicles, and these patterns can then be used to make forecasts. A range of external influencing factors, such as weather, holidays, vacation periods, and major events, can also be incorporated into the analyses. The distribution of cars will also be affected by measures taken by carsharing firms, such as the provision of additional vehicles.

In order to manage this huge amount of data, the researchers divide the area for which forecasts are to be made into individual grid cells. The algorithm uses the historical data on these cells to learn how to predict future vehicle distribution as accurately as possible. The learned model gets better as the amount of data increases over time, which means its predictions become increasingly accurate even when it's already operating.
If the algorithm is integrated into a trip-planning app, users can look up the probability that a vehicle will be available within a user-defined radius of their desired location, thus enabling them to better plan their journey. Carsharing firms benefit from the app because it helps them utilize their vehicles more effectively.

Press Picture: http://www.siemens.com/press/en/presspicture/innovationnews/2015/im2015010379coe...

Weitere Informationen:

http://www.siemens.com/innovationnews

Dr. Norbert Aschenbrenner | Siemens InnovationNews

More articles from Information Technology:

nachricht New 3-D display takes the eye fatigue out of virtual reality
22.06.2017 | The Optical Society

nachricht Modeling the brain with 'Lego bricks'
19.06.2017 | University of Luxembourg

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Climate satellite: Tracking methane with robust laser technology

Heatwaves in the Arctic, longer periods of vegetation in Europe, severe floods in West Africa – starting in 2021, scientists want to explore the emissions of the greenhouse gas methane with the German-French satellite MERLIN. This is made possible by a new robust laser system of the Fraunhofer Institute for Laser Technology ILT in Aachen, which achieves unprecedented measurement accuracy.

Methane is primarily the result of the decomposition of organic matter. The gas has a 25 times greater warming potential than carbon dioxide, but is not as...

Im Focus: How protons move through a fuel cell

Hydrogen is regarded as the energy source of the future: It is produced with solar power and can be used to generate heat and electricity in fuel cells. Empa researchers have now succeeded in decoding the movement of hydrogen ions in crystals – a key step towards more efficient energy conversion in the hydrogen industry of tomorrow.

As charge carriers, electrons and ions play the leading role in electrochemical energy storage devices and converters such as batteries and fuel cells. Proton...

Im Focus: A unique data centre for cosmological simulations

Scientists from the Excellence Cluster Universe at the Ludwig-Maximilians-Universität Munich have establised "Cosmowebportal", a unique data centre for cosmological simulations located at the Leibniz Supercomputing Centre (LRZ) of the Bavarian Academy of Sciences. The complete results of a series of large hydrodynamical cosmological simulations are available, with data volumes typically exceeding several hundred terabytes. Scientists worldwide can interactively explore these complex simulations via a web interface and directly access the results.

With current telescopes, scientists can observe our Universe’s galaxies and galaxy clusters and their distribution along an invisible cosmic web. From the...

Im Focus: Scientists develop molecular thermometer for contactless measurement using infrared light

Temperature measurements possible even on the smallest scale / Molecular ruby for use in material sciences, biology, and medicine

Chemists at Johannes Gutenberg University Mainz (JGU) in cooperation with researchers of the German Federal Institute for Materials Research and Testing (BAM)...

Im Focus: Optoelectronic Inline Measurement – Accurate to the Nanometer

Germany counts high-precision manufacturing processes among its advantages as a location. It’s not just the aerospace and automotive industries that require almost waste-free, high-precision manufacturing to provide an efficient way of testing the shape and orientation tolerances of products. Since current inline measurement technology not yet provides the required accuracy, the Fraunhofer Institute for Laser Technology ILT is collaborating with four renowned industry partners in the INSPIRE project to develop inline sensors with a new accuracy class. Funded by the German Federal Ministry of Education and Research (BMBF), the project is scheduled to run until the end of 2019.

New Manufacturing Technologies for New Products

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

Plants are networkers

19.06.2017 | Event News

Digital Survival Training for Executives

13.06.2017 | Event News

Global Learning Council Summit 2017

13.06.2017 | Event News

 
Latest News

A new technique isolates neuronal activity during memory consolidation

22.06.2017 | Life Sciences

Plant inspiration could lead to flexible electronics

22.06.2017 | Materials Sciences

A rhodium-based catalyst for making organosilicon using less precious metal

22.06.2017 | Materials Sciences

VideoLinks
B2B-VideoLinks
More VideoLinks >>>