We’ve been working in the oil and gas sector since we started out and we’ve noticed a common problem facing companies in frontier regions: how to move people safely and securely with limited resources.

The number of vehicles available in relation to the number of people being moved is normally an unfavourable ratio – there simply aren’t enough vehicles to keep up with demand in terms of journeys.

We’re also conscious of the risks and hazards that present themselves in frontier regions. These range from roads that are unsuitable for heavy loads, through to gatherings of people at certain times of day which not only delay journey time but can also have security implications. We want to figure out the best way to quantify and minimise any associated risks.

We’re interested in how we can make better use of GPS, telematics and transport data to increase safety for personnel and vehicles. The availability and affordability of ‘On Board Devices’ (OBDs), communications networks, transport network data and transport apps will have an increasing role to play in improving road safety in frontier regions.

Behind the scenes, we’re exploring how technology can help to optimise resources, for example by making sure managers have visibility of journey requests, minimising low-priority moves, or by doubling up payloads to make better use of available space. This helps improve the overall efficiency of existing fleets.

‘Routing engines’, familiar to all satnav users, are traditionally used to calculate the most efficient route along a set of specified waypoints. They can also help to estimate the total distance travelled on different types of roads for example urban, highway or off-road, which is a useful metric in the context of vehicle maintenance. Part of the challenge here is that the GPS data from vehicles we’ve worked with tends to be relatively sparse (sampled once every five minutes for example).

Other practical information on routing can be found in OpenStreetMap (OSM). OSM has an increasing amount of data relating to road safety including highway classifications, local speed limits and even highway lighting conditions.

We’ve been looking at open source routing algorithms (like the pgRouting and OSRM) to help make recommendations based on other information like journey time, fuel consumption, or the ability to avoid a hazard, such as a narrow bridge, or a known hotspot of some kind.

We’re inspired by the common practice in the space industry of carrying ‘secondary payloads’ exemplified by recent work by companies like SpaceX, whose secondary payload manifest allows others to ‘hitch a ride’ on an existing mission if there’s room. We can do this by databasing routes and cargo to make sure movements are not duplicated.

Another company that has done interesting work on this front is UPS, whose famous ‘no-left turn’ solution for optimizing circular route planning has significantly sped up delivery times, cut fuel consumption and reduced costs.

We’re in the research and development phase at the moment and are interested in hearing from people with experience of routing algorithms, or experience in logistics management.

Drop us an email if you have any thoughts or questions.