WORKFORCE MANAGEMENT
Have a good trip: Intelligent decisions on the road
Why AI-based shift planning is an essential building block for tomorrow’s mobility, and why road traffic already benefits from it today.
As many as 48.5 million registered cars use Germany’s roads. Daily traffic is getting denser every year, and the network is becoming more complex. Mobility means freedom, but in its current form, it is extremely resource-intensive. Sustainability is a reason to rethink mobility, which should be easy to use, dynamic, and available on demand. Whether it’s buses, taxis, or trains, this will require people – a lot of people. Wisely allocating this labor – also a valuable “resource” in the broadest sense – to meet transportation needs is already a task for AI.
AI makes life on the road easier.
When you hear “AI” and “road traffic,” however, you’re more likely to think of the autonomous vehicles being produced by resourceful automakers. You may recall debates about ethics and safety or predictions that self-driving transportation will revolutionize logistics. The image of a vehicle that steers itself and makes decisions seems to have a synthetic counterpart, a kind of artificial chauffeur. No wonder this development is perceived as impressive, fascinating, and alarming at the same time – and it is not just a dream of the future everywhere in the world! Nevertheless, AI will certainly play a major role in shaping the future of transportation.
But that’s not what we’re talking about here. Before humans give up the wheel altogether, the focus will be on AI applications that are already working behind the scenes to make everyday life on our roads easier. No, we’re not talking about the navigation system that has become indispensable – with its route planning, one of the first real-time planning applications that many people can no longer imagine getting into a car without. Instead, we are staying in the realm of AI-based new mobility, but in a completely “human” subset of it: shift and duty planning in public transportation.
Intelligent driver scheduling
How many and which professional drivers are needed, where and when, to ensure that all passengers – whether by bus, taxi, or on-demand ride-pooling (on-demand taxis in which several passengers share a ride in the same direction, usually between the operator’s virtual stops) – get to the right place at the right time? And how do operators pay attention to the needs of their riders?
AI will play a big role in shaping the transportation of tomorrow!
The shortest route with the highest level of service
Whether it’s the morning commute to school, the family day trip, or the commute home from work, how does public and private transportation ensure that there are never too many or too few drivers but just the right number to provide the transportation needed? In the past, fixed schedules may have provided a clear framework for shift planning, but new mobility wants to meet every individual need. The more dynamic and demand-driven the mobility offering, the more complex the planning. In addition, for environmental reasons, providers strive to minimize trips while providing the highest level of service.
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Scheduling at the touch of a button
But even the most efficient resource planning is not enough. Drivers work to specific rates, need to be able to take breaks and vacations, are employed in different working time models, and also want to be able to make individual requests. Some want fixed schedules that allow them to reliably plan their personal lives. For example, knowing when work is scheduled for the weekend is important. Others want flexibility, dynamic schedules, and the ability to swap shifts with colleagues at short notice. In practice, the path is likely to lead to a company-specific “golden mean.” But to find it at all and to deal with the unimaginable complexity of such workforce scheduling, AI is the (only) tool of choice
When a request comes in from an employee, who (or what) else could, at the touch of a button, determine what impact a shift would have on the entire schedule, including all of the factors mentioned above, as well as others such as fairness criteria (e.g., to distribute weekend work)? The same goes for sickness, fluctuations in demand, or other last-minute changes that need to be quickly translated into a workable, efficient schedule. This can be achieved through AI applications that, based on ERP and HR tools, predict demand-based shift cores and then optimally fill them with the real resources available, taking into account all the above criteria and many more.
AI is the tool of choice to deal with the unimaginable complexity of modern workforce planning!
Many more opportunities for AI in transportation
But the above example by no means covers the potential of AI for the new mobility. Of course, many opportunities exist to use AI and intelligent algorithms in commercial transportation. In the industrial sector, this starts with the control of incoming truck traffic at companies. In some cases, dozens or hundreds of trucks arrive at industrial sites every day, and at peak times, they would back up for miles on the highways if their arrival were not intelligently scheduled into appropriate time windows using AI. Here, too, there is tremendous support for drivers. For example, modern applications can guide them through the entire registration process at a factory gate to the correct ramp. AI can also be used to manage the delivery of materials to construction sites, avoiding unnecessary backups that further congest already congested city centers. And yes, self-driving, autonomous vehicles will also help shape tomorrow’s mobility.