When it comes to complex tasks under dynamic conditions, the buzzwords are automation and artificial intelligence (AI). Logistics involves many such tasks, including route planning, which is an ideal application for AI. Let’s explore how AI can support route planning and identify the characteristics of an effective route optimization tool.
Route Planning: A Core Task in Logistics
At first glance, route planning seems simple: Which vehicle will carry which load on which route, and in what order will they head to their destinations? However, this is only simple for a small service provider with a limited order volume and few vehicles. For everyone else in the logistics business, it is a highly complex and critical challenge.
Decisive for Customer Experience, Efficiency, and Eco-Balance
For transport logistics service providers, retailers, and manufacturers, reliable logistics is essential for customer satisfaction and loyalty. High-quality route planning ensures that products arrive on time and are readily available to industry, retailers, and consumers. Optimized route planning is also an effective tool for increasing efficiency: the better the planning, the fewer resources, such as time, materials, and energy, are consumed. Lower energy consumption results in a lower environmental impact. Thus, route planning is an economic and ecological factor.
Route Planning in Logistics Without Automation and AI
At logistics companies, dispatchers are responsible for route planning. Based on current orders, available loading space, and personnel capacity, dispatchers allocate volumes to individual vehicles and design routes that ensure the fastest delivery with the fewest kilometers driven. This process involves more than just looking at digital maps and navigation systems. Many factors contribute to the decision-making process, such as:
- Traffic volume depending on times of day
- Weather conditions
- General traffic situation and restrictions (e.g., traffic jams, construction sites, and closures after accidents)
- Specific traffic restrictions for certain vehicle types (depending on weight, height, or emission class)
- Parking and turning options
- Traffic situation on company premises
Time-Consuming, Inflexible, and Error-Prone
Planning each route individually is very time-consuming. It also results in a rigid route plan that is difficult to adapt to sudden changes. There is also a risk of planning errors because it is difficult to monitor all planning factors and short-term events without automated systems. Even the most experienced dispatchers can experience planning errors, which can lead to less efficient routes, wasting resources and energy.
Artificial Intelligence Complements Human Intelligence
AI dominates discussions about technical innovations in a wide range of industries. Still, depending on the area of implementation, AI’s potential utility is (still) often limited. That said, one area in which AI can already be used optimally is route planning.
In the short and medium term, AI should support, rather than replace, human intelligence to make planning more efficient, flexible, and less prone to error. Given the growing demands on route planning due to higher transport volumes and rising customer expectations in terms of convenience and punctuality, dispatchers are increasingly exceeding their capacity. Automated and AI-supported processes can alleviate this situation.
On the other hand, humans remain a pivotal control instance. In day-to-day operations, experienced dispatchers evaluate the practicability of automatically generated route plans. Combining human perception and judgment with computational precision improves planning quality and optimizes the use of resources.
In the long term, the role of AI may expand. Good specialists are scarce in logistics, as they are in many other sectors. Gradually integrating AI applications into operational processes can prevent future staff shortages.
This Is Where AI Comes Into Play for Route Planning
The following AI features are particularly valuable for route planning:
- Ability to learn from historical data
- Pattern recognition
- Predictive ability
- Dynamic adaptability to sudden events
These four qualities also characterize good planning personnel. For AI to offer added value, it must do more than simply follow rigid algorithms. If AI only produced inflexible patterns of action, it would be neither intelligent nor helpful.
Instead, AI can draw conclusions similar to those of human dispatchers. For instance, a dispatcher might add empirical values to a report on an acute traffic jam. How long do traffic jams typically last on this section of road? For planning purposes, after a certain period of time has passed, a detour should no longer be necessary. However, compared to humans, AI can process real-time information for the entire route in real time during the planning process and therefore make adjustments more quickly and precisely.
In conclusion: A reliable AI system calculates complex routes instantly and accurately using a variety of historical and current parameters. Transport service providers can react faster and more effectively to unforeseen changes, such as traffic restrictions, vehicle breakdowns, and changes in customer requirements.
How Do Transport Companies Make Use of AI for Route Planning?
The performance and integration capabilities of an AI system naturally depend on the IT provider. For user companies, it is important that the system’s database is large enough and offers high levels of networking.
A Large Database and High Level of Networking Are a Must
In addition to historical data, real-time data on traffic, weather, customer requirements, stock levels, the vehicle fleet, and personnel is needed. When a dispatcher enters delivery requests into the AI system, the system compares the available resources with the requirements and destinations. Based on this information, the system assigns vehicles and personnel and designs routes to utilize resources in the best possible way.
Data networking is important even in the initial stage of route design. It is all the more crucial when it comes to adaptability. It integrates the scheduling department with all entities and process participants, including the warehouse, drivers, vehicles, consignors, and consignees, via mobile applications. This data is combined with real-time information from maps and services that provide traffic, news, and weather updates.
Once the system has all the relevant information, it is possible to conduct real-time data analyses for proactive forecasting models, as well as automatic, continuous route optimization and adjustments.
User-Friendliness for Everyone Involved Is Paramount
A clearly designed user interface and intuitive operation make the work of dispatchers easier. For example, dispatchers can easily make adjustments or take special customer requests into account. Drivers in particular benefit from easy-to-use programs. They must concentrate on traffic. If they need to adjust their route, they need clearly structured guidance.
Benefits of AI-Supported Route Planning
There is huge potential for increasing efficiency through AI applications in logistics scheduling, an area associated with a lot of volatile data.
Possible positive effects include:
- Improvement of delivery quality and, consequently, customer satisfaction
- Optimal utilization of freight capacities
- Reduction of kilometers driven
- Saving time
- Avoidance of empty runs
- Reduction of greenhouse gas emissions
- Reduction of energy consumption
- Conservation of materials and a longer vehicle service life
AI-powered route planning can create a triple-win situation: it strengthens customer loyalty, reduces operating costs due to greater efficiency, and reduces the ecological footprint. Looking beyond the company’s own horizons, this can also improve the environmental balance on a larger scale. When more and more transport companies run efficient routes, the overall volume of traffic, noise, and emissions decreases.
Given the growth of the e-commerce sector and its associated transportation needs, one might argue more cautiously: at the least, AI-powered route planning can limit the increase. Along with sustainable drive and fuel technologies, intelligent route planning will be an effective tool for environmentally friendly logistics in the future.
How You Can Benefit from GoGreen Plus
Climate change is the greatest challenge of our time – and it affects all of us. However, it is not equally easy for every industry and every company to reduce their respective ecological footprint. With GoGreen Plus, we offer you the opportunity to reduce emissions in a simple way thanks to insetting – exactly where they occur. Your investment goes 100% into the use of green technologies within our network.
The Routes of the Future Are Smart
Automated and intelligent route planning is nothing new to DHL Freight. We use RAPTOR, a self-developed tool with an algorithm that accelerates and optimizes decisions on delivery schedules and routes. More information about RAPTOR can be found in our DHL Freight Green Technology Roadmap.
The Roadmap also reveals what else DHL Freight is doing to streamline logistics processes and make them more sustainable. Beyond our own efforts, we believe that logistics must become smarter to balance growth and sustainability.
