Even before the spreading of computers and GPS, some gimmicks to save time and fuel have been devised: it is a well-known fact that UPS drivers almost never turn left [1]_._ Left turns are indeed less safe and time-waster in a right-based driving system such as the one adopted in a major part of the world. This weird trick due to drivers' insight avoids emissions equivalent to over 20,000 passenger cars. At the beginning of 2008, UPS started its investments in a more scientific route optimization algorithm, the so-called On-Road Integrated Optimisation, and Navigation (ORION). Without surprise, in 2012 ORION confirmed what the drives guessed and applied since the 1970 and pushed further UPS fuel-saving reaching over 38 million liters per year [2]. The kind of optimization problems ORION deals with, known as Traveling Salesman Problem (TSP) and Vehicle Route Problem (VRP) (see Fig. 2), increases faster than exponentially: for only 16 delivery stops already over 20 trillion possible routes can connect them all_._ Until now, ORION is not able to solve the TSP but it bases the optimization process on Machine Learning (ML) using training sets based on years of data to identify route combinations that are efficient enough [4]. Anyway, dealing with a brand new set of routes makes ML useless and imposes solving such a problem from scratch. Once again, so many possible trajectories should be tested that such a problem would be unsolvable even for the most powerful supercomputers. Quantum computing might once again represent the key to facing this need, as supply chains and logistics become more fundamental for our society. Nonetheless, the work on this topic is still in the early stages, so that is hard to say if quantum would be really more efficient than classic in this optimization task. Anyway, some interesting results have already been obtained using a quantum-classical hybrid approach, based on quantum annealing technology [5, 6]. Many other ways to optimize the energy consumption of transportation means could be discovered as soon as the resolution of PDE with a quantum computer will be cracked. New airplane designs saving each year tons of CO₂ would be then easy to find, leading us towards the green revolution we already desperately need. **References**: [1] [Why UPS trucks (almost) never turn left — CNN](https://edition.cnn.com/2017/02/16/world/ups-trucks-no-left-turns/index.html#:~:text=UPS%20trucks%20almost%20never%20take%20left-hand%20turns.%20By,avoids%20emissions%20equivalent%20to%20over%2020%2C000%20passenger%20cars.) [2] [Analytics Success Story: UPS’s ORION Project | Introduction to Business Analytics and Decision-Making | InformIT](https://www.informit.com/articles/article.aspx?p=2992600&seqNum=6) [3] [Minimizing the Carbon Footprint for the Time-Dependent Heterogeneous-Fleet Vehicle Routing Problem with Alternative Paths (mdpi.com)](https://www.mdpi.com/2071-1050/6/7/4658) [4] [How Quantum Computers Could Cut Millions Of Miles From Supply Chains And Transform Logistics (forbes.com)](https://www.forbes.com/sites/forbestechcouncil/2021/02/05/how-quantum-computers-could-cut-millions-of-miles-from-supply-chains-and-transform-logistics/?sh=76f525e25a92) [5] [A Hybrid Solution Method for the Capacitated Vehicle Routing Problem Using a Quantum Annealer (arxiv.org)](https://arxiv.org/abs/1811.07403) [6] [University of Warsaw: Solving Vehicle Routing Problem Using Quantum Annealing — YouTube](https://www.youtube.com/watch?v=0_huQXg4sjI) #quantum