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A New Era in Transport Logistics with Big Data and Self-Driving Trucks

By December 7, 2022Uncategorized

Fuel prices and a shortage of drivers are putting transport logistics under immense pressure.

The biggest challenge in the transport sector today: there just aren’t enough drivers. A recent survey conducted by the International Road Transport Union (IRU) industry association shows that this bottleneck has exacerbated worldwide over the past two years. To make matters worse, this situation will worsen when most of the baby boomer generation hits retirement age in the upcoming years. It will be difficult to fill all these positions as the profession isn’t very attractive: There is very little flexibility in the working life of a truck driver, and the pay is bad. Add to that the rising fuel prices and inefficiencies – Eurostat has found that every fifth journey is an empty truck – and the transport industry is facing major challenges which must be addressed as quickly as possible.

Look at the big picture

The only solution is to boost efficiency by optimizing processes for the long term. This requires complete transparency across all steps and events along the entire supply chain. Taking all aspects into account is the only way for logistics companies to have a solid foundation for decision making and holistic optimization. This is where big data technologies come into play.

Big data for real-time optimizations in transport logistics

Logistics and transport service providers create enormous data records as they manage the flow of goods. These data include information such as types of goods, location, weight, size, origin, and destination. By collecting and analyzing these large amounts of data, big data technologies can optimize transport journeys in real time. The great thing about this: Process data is analyzed and merged with real-time route matrix and traffic data. The resulting insights enable optimal transport and route management: Which routes within the distribution network should be utilized? How can the fill level of goods be optimized? Which truck should be used for transportation? These are decisions that can be made repeatedly at every step of the journey based on informed calculations by a software ecosystem that leverages big data in real-time.

An operation that is optimizing the real time flow of goods is also well-positioned to manage unexpected events.  Real-time insights allow the operation to rapidly make informed decisions. This is the perfect way to balance logistics and transport issues and to avoid major peak loads. According to the results of a study published in Computers in Human Behavior, determining ideal transport routes in combination with a higher fill level of the trucks can lead to a significant mileage reduction. Additional benefits include lower energy consumption and lower CO2 emissions.

Massive potential – thanks to big data combined with self-driving trucks

Optimizing existing processes provides substantial performance improvements. But there is opportunity to take performance to the next level by incorporating self-driving trucks. These vehicles can enable operating companies to reduce their number of required vehicles and lower cost structures. These lower costs can then reduce the overall cost of consumer goods. which furthermore enables them to lower the costs for consumer goods.

By some estimates, 65 percent of consumer goods are delivered using trucks. The transition of an entire fleet to self-driving trucks can decrease operating by approximately 45 percent (according to McKinsey Route 2030, September 2030). Initial steps toward self-driving trucks are in process. For example, last year Germany established the legal framework to enable the introduction of self-driving trucks, And their use is already a reality in some states of the USA. This year, the ZF division Commercial Vehicle Solutions presented its first automated hub-to-hub transport solution with trucks driving autonomously up to 80 km/h (50 mi/h) on the highway.

Big data in transport logistics requires adjustments to the storage and turnover of goods

Not only has the labor shortage in transport logistics come to a head, but the changed consumer demands placed on logistics networks have also had a lasting impact. Consumers today expect same-day delivery. This requires intelligent urban logistics networks consisting of various regional and urban warehouses. Transportation from these new distribution centers to their final destination must also be balanced using data transparency across all nodes. This is a requirement to effectively satisfy today’s consumer demands.

Warehouses such as distribution and order processing centers will benefit from the new big data technologies. But other technologies such as autonomous forklift trucks will further optimize the storage and turnover of goods as well. The widespread use of these technologies will lower the storage costs per item as they can accelerate the turnover of stocks. Furthermore, autonomous vehicles will facilitate and simultaneously lower the costs for around-the-clock operation. We will see this development play out more and more as warehouses and fulfillment centers expand the automation of their processes. Why? The processing of e-commerce orders is accelerating continuously. As a result, more shifts are required in an environment with a lack of available human personnel. Thanks to automation, picking and shipping of orders will also be possible during night shifts.

This change, however, requires further adjustments to warehouse infrastructures. For example, entrances and docks suitable for autonomous trucks must be provided to ensure smooth workflows and to further lower transport costs. Lower transport costs can then allow operating companies to relocate their warehouses into more remote areas. Alternatively, companies can focus on saving costs at urban sites, thereby improving their ability to meet the rapid growth in demand for fast and free shipping.

Mix of measures opens up new era in transport logistics

The combination of transparency, real-time optimizations, and autonomous driving will be the long-term solution to the labor shortage in transport logistics. However, this new supply chain transparency will also raise the expectations of customers which in turn will profoundly change the logistics networks of the future.

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Jürgen Drobesch, Portfolio Manager at KNAPP, is responsible for Value Chain Solutions. Jürgen started his professional career in the development department at Philips while still studying to become a communications and IT technician. As a student, he also founded his own software development and business consulting company. After selling his company, he spent ten years working as the holder of a general commercial power of representation and managing director for a wholesale company running a manufacturing profit center. Jürgen has been part of the KNAPP team for three years now and readily contributes his experience from various industries to the new product portfolio.

 

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