Urban-Engine objectively evaluates mobility networks by leveraging big data. It gives insight in the strength and weaknesses of transport service plans including bike, bus, train and car.
Mobility by public transport as a function of time.
Urban-Engine shows visually how a transport network is performing. A mobility score is assigned to every area based on how quick a passenger can travel towards other areas. The development of mobility plans relies heavily on domain knowledge and best practices.
Urban-Engine objectively evaluates the quality of these public transport, road and bicycle networks. By utilizing large amounts data and computing power Urban-Engine calculates the mobility score. The insights can be used to share, evaluate and optimize the current mobility network.
Areas are scored on mobility by requesting thousands of journey plans.
Urban-Engine uses maps, timetable data and a journey algorithm to request travel plans between points.
The initial journey request is repeated to all possible destinations in the surrounding area
This step is repeated for all possible origins to finally have a location matrix with travel plans
This matrix is enriched with meta-data, for example how many inhabitants within a city can be reached
This is in a nutshell the ❤ of the Urban-Engine.
Urban-Engine is constructed of multiple features that individually can be used
to highlight and strengthen analysis.
How far can you travel within a certain time period?
Reachability performance indicators on hectare level.
How many options can you take to your destination?
Evaluate current service plans and test future service plans.
Compare bike, bus, train and car or combine modalities to evaluate attractiveness for the traveler.
Want to know more about a specific topic? Please contact us and we’ll get back to you as soon as possible!
Want to read more about what the Urban-Engine does and can?
Read our white paper here!
Check below how the Urban-Engine is being used in different settings
to demonstrate the power of mobility insights produces by the engine.
The Urban Engine has been at the core of an empirical study of accessibility measures in house pricing models for the University of Amsterdam.
Using a bicycle as pre-transport for public transport significantly changes travel patterns. Still journey planners are not able to cope with this combination of modalities.
The majority of journey planning apps have the option to choose either public transport or bike as modality. However, the combination of using a bike with public transport is often overlooked as option.
Mobility affects us all and is one of the key drivers for an efficient economy. A technological revolution is causing the industry to rapidly change, driven by the vast availability of high quality data. Now is the time to put this data to use and fuel innovative initiatives.
We from Urban Engine have dedicated ourselves to do exactly that: boost innovation by using data to its full potential. All in pursue of our objective: improving mobility all around the world! Are you ready to join our endeavour?
We combine our years of experience in the mobility sector with creativity, pure data science and our love for coding to build the applications of tomorrow.
The availability of enormous amount of computing power in combination with multiple new data sources ask for a new approach in the industry.
Utilising the strength of geo-spatial visualisations helps us to understand complexity in an intuitive way and provides us with the insights used to fuel improvement. Our goal is to provide these insights and boost improvements while doing what we love.
Interested in what we can do for you? Check out our demo’s, our solutions or get in touch. We love to hear from you!
