Beeline - Cycle Routing

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Current routing and mapping technology is not optimised for the needs of cyclists. At a macro level the impact is less people choosing to cycle which has a negative impact on health, congestion and pollution. 

The objective of the project is to demonstrate a routing and mapping service optimised for the needs of cyclists (be it speed, safety, pleasantness etc) and to validate that it is deemed better than the existing provisions. 

Users and their needs

There are three target user groups for this project:

  • Individual cyclists
  • Delivery companies using cyclists to move goods and hence needing fast but safe routes
  • Bike share companies renting out cycles to end users hence needing to guide them on safe, pleasant routes to ensure the best experience.

 For each of these groups Beeline has users who are involved in shaping the solution:

  • 10,000 existing private individual customers of Beeline who can feedback and provide data into the system
  • Deliveroo who are inputting their needs as a cycle delivery company
  • A European dockless bikeshare company (name under NDA) who are working with us to develop the solution for this customer segment

 The needs of these users (for the whole navigation system, not just the routing) are as below:

  • to be able to easily plan and adjust routes to set up prior to beginning a ride, to see where that route will take them.
  • to see relevant data on the map while planning a route so they can make decisions based on this information.
  • to be able to set and save preferences for different parameters within the route planning interface (e.g. optimizing for speed or safety)
  • to judge how long a journey will take for the purposes of planning their time and comparing to alternative transport modes
  • to plan the route on a mobile phone (or other detailed screen interface) but receive the instructions via a medium fit for purpose in the field of view while riding
  • to be able to mark their ratings for roads as they ride in order to prefer/avoid these roads in future and to automatically adjust their saved preferences
  • to be guided along an alternative route should they deviate from the original route (intentionally or accidentally)


  • Individual users are 40% UK, 30% other EU countries, 30% non-EU
  • Deliveroo is a UK based company
  • The bikeshare player is based in an EU country 

Service/ system concept

The system will allow a user to plan a cycling route on a map and modify the parameters for which they want to optimise (e.g. speed vs safety). The user will then be guided along that route using the intuitive interface of the Beeline hardware device (or a simulator or another device).

The below diagram shows how the various parts of the system interact with each other. A wide range of datasets (proprietary or external) are used as inputs to the routing engine which is the focus of this project. The user inputs a destination via the smartphone app and the start location is known from the smartphones’s GPS unit. A route is then requested from the Beeline routing engine and sent back to the smartphone which then controls the handlebar mounted Beeline hardware device in order to guide the user to their destination.

Space Added Value

The space assets used are all geodata relating to features of the map. For example road type, surface quality, elevation, bus routes, traffic, cyclist speed and many more. 

Some of these are openly available (e.g. elevation), some are obtainable through partners or at a cost (e.g. bus routes from TfL in London, traffic from commercial data providers). Others are proprietary data from our own user base (e.g. cyclist speed data and user input). 

The way in which the proposed system adds value is in the manner in which it combines all of these various space assets to be able to mimic human intelligence by weighting them in the correct manner. In the same way a cyclist with detailed knowledge of an area will consider many factors (such as time, distance, safety, elevation) and make a balanced decision on which route to take, so the system will mimic this through the routing engine. 

The below image is an output of a prototype in central London in which a safety rating has been calculated for each road by using a weighted blend of factors including distance, road size, bus route information, user rating, elevation, accident hotspots and several others.

Current Status

Beeline has built the map network for London, imported a variety of external sources of data onto that map, cleaned and imported our own data into the map, built weighting methodologies to be able to optimise for various parameters, built prototype routing algorithms for route selection and built the system to be able to enter start and end points and return a route optimised for with a certain weighting. 

Prime Contractor(s)


United Kingdom


Status Date

Updated: 08 April 2020 - Created: 23 May 2019