Transport impacts at every level of the sustainability hierarchy and drives the need to build sustainable ecosystems far into the future.
Issues such as greenhouse gases are obvious, as are the depletion of finite resources: from agricultural land that roads get built on, to the hydrocarbons and minerals that trucks consume, and road capacity itself.
Then there is the population health issue. Transport impacts everything from pollutants and particulates in the air (which in the UK, is linked to 40,000 premature deaths per year), through to noise and traffic disruption.
How do we fix it?
Long term, technological advancements ranging from electric vehicles to 3D printing may come to the rescue. In the meantime, the freight transport industry needs to show that it is reducing its impact by making the very best use of existing resources, before authorities decide to step in and regulate.
An obvious starting point is to reduce empty and partially loaded journeys. This is the primary aim of today’s typical freight matching systems. However, merely matching loads, pick-up/destination points, times and prices is not sufficient on its own. Intelligent freight matching systems, on the other hand, are starting to show greater possibilities.
TGMatrix uses sophisticated algorithms to analyse and compare data in close to real time, more accurately identifying the ‘best match’, including historic traffic and congestion information to achieve the lowest carbon output possible.
These algorithms could, for example:
- consider local restrictions on permitted load/unload hours, congestion charge rates and operating hours
- match loads not just to carriers, but to cross-dock facilities for transhipment into urban-friendly vehicles
- make bookings for street-side unloading slots to ease bottlenecks
- fill the missing arc in the circle (where the recipient of goods, say a retailer, may set stringent demands for delivery times, quantities or other factors, but doesn’t directly see the costs of these decisions)
The trade-offs in any road-charging schemes (which could conceivably include for example discounts for vehicles with high load factors) could be considered – and it would be possible to set up rules so that carriers don’t benefit by using non-chargeable ‘rat-runs’.
To promote the most efficient journey use, the management systems would have to create effective cooperation / collaboration and asset sharing, but this can be set up through a neutral third party, such as TGMatrix, without detriment to commercial competition or confidentiality.
There are all sorts of possibilities, and Intelligent systems could make these much more apparent.
In fact, the ability of intelligent systems to radically improve the sustainability profile of freight transport is immense – not just on roads, but across all multi-modal opportunities.
The IT works. The algorithms can deliver the results. The question is, are you ready to capitalise?
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