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 Terahertz spectroscopy goes nano
20.10.2017 | Brown University

nachricht New software speeds origami structure designs
12.10.2017 | Georgia Institute of Technology

All articles from Information Technology >>>

The most recent press releases about innovation >>>

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

Im Focus: Neutron star merger directly observed for the first time

University of Maryland researchers contribute to historic detection of gravitational waves and light created by event

On August 17, 2017, at 12:41:04 UTC, scientists made the first direct observation of a merger between two neutron stars--the dense, collapsed cores that remain...

Im Focus: Breaking: the first light from two neutron stars merging

Seven new papers describe the first-ever detection of light from a gravitational wave source. The event, caused by two neutron stars colliding and merging together, was dubbed GW170817 because it sent ripples through space-time that reached Earth on 2017 August 17. Around the world, hundreds of excited astronomers mobilized quickly and were able to observe the event using numerous telescopes, providing a wealth of new data.

Previous detections of gravitational waves have all involved the merger of two black holes, a feat that won the 2017 Nobel Prize in Physics earlier this month....

Im Focus: Smart sensors for efficient processes

Material defects in end products can quickly result in failures in many areas of industry, and have a massive impact on the safe use of their products. This is why, in the field of quality assurance, intelligent, nondestructive sensor systems play a key role. They allow testing components and parts in a rapid and cost-efficient manner without destroying the actual product or changing its surface. Experts from the Fraunhofer IZFP in Saarbrücken will be presenting two exhibits at the Blechexpo in Stuttgart from 7–10 November 2017 that allow fast, reliable, and automated characterization of materials and detection of defects (Hall 5, Booth 5306).

When quality testing uses time-consuming destructive test methods, it can result in enormous costs due to damaging or destroying the products. And given that...

Im Focus: Cold molecules on collision course

Using a new cooling technique MPQ scientists succeed at observing collisions in a dense beam of cold and slow dipolar molecules.

How do chemical reactions proceed at extremely low temperatures? The answer requires the investigation of molecular samples that are cold, dense, and slow at...

Im Focus: Shrinking the proton again!

Scientists from the Max Planck Institute of Quantum Optics, using high precision laser spectroscopy of atomic hydrogen, confirm the surprisingly small value of the proton radius determined from muonic hydrogen.

It was one of the breakthroughs of the year 2010: Laser spectroscopy of muonic hydrogen resulted in a value for the proton charge radius that was significantly...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

ASEAN Member States discuss the future role of renewable energy

17.10.2017 | Event News

World Health Summit 2017: International experts set the course for the future of Global Health

10.10.2017 | Event News

Climate Engineering Conference 2017 Opens in Berlin

10.10.2017 | Event News

 
Latest News

Terahertz spectroscopy goes nano

20.10.2017 | Information Technology

Strange but true: Turning a material upside down can sometimes make it softer

20.10.2017 | Materials Sciences

NRL clarifies valley polarization for electronic and optoelectronic technologies

20.10.2017 | Interdisciplinary Research

VideoLinks
B2B-VideoLinks
More VideoLinks >>>