 We live in an increasingly smart world. There are smart grids to help deliver electricity more efficiently, smart phones to connect us to each other and to a universe of information, and, just around the corner, smart driverless cars. But for all the intelligence of these devices, they're still rather oblivious to how we live and act. So how can smart systems be made smarter? A recent study proposes a new computational framework to help bring humans and social factors into the loop. Many familiar smart systems are formally referred to as cyber-physical systems, or collectively, industry 4.0. That's because they merge traditional physical processes with virtual monitoring and control. A self-driving car, for example, relies on a bevy of physical sensors that acquire traffic information and virtual processors that crunch the data to ensure accurate steering and to avoid collisions. The problem with these computational systems is that they generally don't factor humans into the equation. They might appear to adapt to our habits, for example, knowing what time we leave for work in the morning. But this knowledge is purely statistical, drawn from historical data and past experience. The systems aren't responding to decisions in real time. That's one reason why self-driving cars still find it difficult to navigate through complex traffic environments, such as a crowded intersection. Fortunately, cyber-physical systems can acquire, analyze, and use elements of social behavior to become cyber-physical social systems. The key is to revamp how smart systems model complex situations in the real world. This is possible through a novel approach called ACP, which is short for artificial systems, computational experiments, and parallel execution. Using ACP would allow for a more intelligent transportation system that could harness knowledge about how drivers make decisions and how they interact with each other. It would discover patterns and even predict future situations that, while entirely possible, have not been previously observed, like a traffic jam outside of rush hour. This transportation system would also leverage the power of social networks to learn about possible emergencies, such as a pile-up on the interstate or potential ride-sharing opportunities that are lacking in a conventional cyber-physical system. Welcome to Transportation 5.0. Although predicting the unpredictable is certainly a tall order, this ACP approach to integrating social aspects into smart systems has worked well in other complex environments, including the military and oil industry. Still, further research is needed to make these systems safer and more secure, as well as adaptable to new situations. Closer collaboration between physical, social, and cognitive scientists will therefore be required to make smart transportation smarter and better.