Autonomous logistics

What is autonomous logistics management?

Autonomous logistics is defined as the use of technology devices to execute supply chain processes or movements of vehicles, freight, equipment, people, information or resources without direct human control.

Autonomous logistics management relies on artificial intelligence (AI) and machine learning to evolve smart transportation movements and improve supply chain processes.

Autonomous logistics technology adjusts delivery routes and predicted arrival times based on real-time conditions, such as weather, traffic, order cancellations, new orders or driver exceptions. Related automated tasks, such as instant push notifications and delivery alerts, change in response, improving communication among supply chain partners.

Logistics management of automated tasks uses robotic process automation (RPA) to complete manual tasks. For example, automation supports digital freight matching, load management, shipment execution, freight claims management, invoice audit and payment, and other supply chain management functions.

Autonomous logistics vs. automation

Compared to automation, autonomous logistics technology collects data and applies the information in ways that improve the performance or efficiency of the machine activity. In short, autonomous processes become smarter based on information collected during operation.

Automation uses a well-defined, static set of parameters to execute tasks. Some decision-making is supported by predetermined information, but an automated system performs specific tasks based on original inputs and outputs.

Autonomous vehicles in logistics networks

Autonomous or "self-driving" vehicles process large amounts of information to make rapid operational decisions without human involvement. In freight transportation networks, autonomous trucks are being tested in both long, over-the-road journeys and last-mile routes with multiple, frequent stops. In these cases, human drivers still work as an on-board co-pilot to the autonomous technology.

Autonomous vehicles in supply chain warehouses or other controlled environments execute a variety of tasks. Forklifts, picking and packing processes, and other activities supported by autonomous vehicles and robotics are increasingly used in fulfillment and freight management. Drones operating in an autonomous logistics information system can complete product inventory scans or execute small package deliveries, capable of smooth operation without the need for a human driver or operator.

Benefits of autonomous logistics

In an autonomous supply chain, standardization, connectivity and intelligence support the ability to anticipate events, develop plans and improve logistics. Benefits derived from this functionality include:

  • Time savings and productivity: eliminating repetitive manual processes through robotic process automation

  • Increased agility: anticipating and adjusting a delivery route, process plan or other exception before a disruption occurs

  • Cost reduction: deploying machines for tasks that are routinely plagued by human error, moving and delivering goods more quickly and efficiently, and optimizing routes to limit vehicle miles or avoid time lost in traffic

  • Improved planning: using technology to automate supply chain decisions and transportation execution based on real-time data

How technology supports autonomous logistics technology

Shippers, logistics services providers (LSPs), brokers and third-party logistics (3PLs) providers increasingly rely on autonomous logistics and process automation across their transportation management and the broader logistics supply chain, which can improve cost control, optimize freight movements and enhance service to end customers.


Robotic process automation for transportation workflows

Rules-based processes and dynamic workflows complete repetitive, manual and error-prone activities, as well as those that are seasonal or time-critical, saving keystrokes, reducing errors and expediting supply chain movements.


Automation in shipment execution

Advanced algorithms and rulesets plan loads, direct carrier selection, tender shipments, track charges, manage and store contracts, audit freight invoices, manage returns and complete claims filing. Combined with human-managed exceptions, automation supports freight cost reduction.


Autonomous rerouting in final mile delivery

While shipments are in transit, dynamic rerouting and optimized response based on changing weather, traffic, order or delivery conditions can help avoid service failures and a diminished customer experience.


Dynamic control and visibility across modes

Visibility across the entire supply chain enables proactive freight management, supporting the ability to select and manage the best transportation mode for a given service need, whether that's a truckload or less-than-truckload journey in a driver-operated truck, a freight cargo movement by robot or a final mile delivery by drone.