Systems: Making the World Move
ISA: The Framework for Mobility 4.0
This article is the second part of our deep dive into ISA: The Framework for Mobility 4.0.
Pieces of infrastructure are monuments of mobility. Our ports, energy networks, highways, and communications towers define our skylines and our built environment. While infrastructure is a physical manifestation of our capacity, systems represent our digital capacity. This layer of ISA is where the digital takes precedence over the material, where bytes dominate atoms. This article will explore how data within mobility systems is critical for realizing a new vision of mobility. Mass adoption of new mobility technologies over the last 100 years shifted our physical environments. In the coming years, digital mobility systems will become monuments in their own right because the movement they facilitate will change the landscape of our lives.
Mobility systems of the 20th century were primarily government managed. These large, mostly physical systems were sufficient for achieving our transportation goals of the time but are unprepared to realize the Mobility 4.0 vision. With private actors filling transportation and logistical gaps in our ecosystem, a new framework is needed to ensure the multi-actor, multi-polar mobility system of the 21st-century works for us and our environment.
Too many chefs, not enough cooks
The term system is derived from the Greek word synistanai. Synistanai comes from the prefix syn- which means “together” and the root of histanai- “cause to stand, make, or be firm.” Its use implies functionality and intentionality. Systems are designed to achieve specific results through sustained interactions between actors. Think of your smartphone’s operating system. It connects you to the telecommunications network, stores your photos, triangulates your GPS location, and much more. This system is working to coordinate, aggregate, and orchestrate disparate activities. It has one chef, the operating system, and many cooks, the applications and functions that work together to let users compute, store, and communicate.
In contrast, mobility systems today have many chefs and few cooks. Big ideas, strategy, and high-level targets dominate (chefs), but few are concerned with the details or operational incentives (cooks) needed to realize any goal. Paired with the fact that mobility systems often have varying goals, it makes it extremely difficult to agree on the right mobility system architecture. On which goals should our mobility systems focus? Should they focus on improving social good, increasing financial gain, or securing individual freedom? The diverse set of inter-industry stakeholders — including government regulators, startup founders, corporate middle management, and everyone in between — will approach these questions from their perspective, each with salient points. With a multitude of opinions, we may never agree on a definitive answer.
Interoperability is the key
Suppose we cannot agree on the overall objective for mobility systems. In that case, we should agree on one critical feature that would allow mobility systems to support whichever purpose we choose: interoperability. Mobility systems designed using the principle of interoperability ensure different systems with competing goals and objectives can cooperate. Siloed fiefdoms serve little benefit in a world with limited resources and space. As such, interoperability should be the founding principle of every 21st-century mobility system.
Without interoperable systems, it will be virtually impossible to take advantage of the vast datasets created within the mobility industry. Given that mobility activities are discrete, easily quantifiable, and rich with information, mobility datasets are among the most extensive, structured, and valuable datasets globally. As a result, they are prime candidates on which to release algorithms focused on optimization.
The Key Functions of Mobility Systems: Coordination, Aggregation, Orchestration
Now that we’ve explored the importance of interoperability as a critical feature of mobility systems, it’s essential to understand its vital functions. The system layer of the ISA model is concerned with communication and connectivity. It’s the layer in which data is collected, organized, and analyzed to enable movement. Without this layer, infrastructure would remain physical, “dumb,” and unable to interact with the broad array of new technologies. At their core, mobility systems serve as the connective tissue in our ISA framework. They are often overlooked because they can’t be touched or experienced like infrastructure or applications, respectively. However, they are indispensable for Mobility 4.0. Mobility systems serve three main functions: coordination, aggregation, and orchestration.
Coordination
Traditional logistics are a prime example of coordination. There, individuals use applications to plan daily delivery routes. Coordination in this context is generally designed to deliver one-way communication from a central body to field units. In a logistics company, a coordinator (human or non-human) will select the best route to deliver the goods based on that day’s requirements. Some would go so far as to call these coordinator systems “dumb” because they lack the capability to monitor or adjust routes. It is primarily concerned with completing an activity, and success is measured by answering yes to the question: was the package delivered? Coordinating systems continue to evolve from their more primitive days. Today, innovative firms enable logistics coordinators to minimize fuel consumption and maximize customer satisfaction. Even with these technological advances, coordination systems, alone, are insufficient.
Aggregation
Systems aggregate data so that operators can act upon insights gleaned from data. Compared with coordination systems where bi-directional movement is a nice-to-have feature, aggregating systems cannot exist without bi-directional data movement. In the logistics example, the data that fuels the design derives from observing the delivery outcome and, more importantly, observing how the driver arrived at that outcome.
We can explore an example of aggregating systems in the Open Mobility Foundation’s Mobility Data Specification (MDS) initiative. Through it, shared mobility operators provide real-time information about the numbers of vehicles in operation, vehicle location, physical condition, and a host of other data points through an Operator API. To date, this is the most comprehensive set of data standards for micro-mobility operators in cities, adopted by more than ninety cities worldwide. Systems like MDS can collect data from disparate operators to drive decisions on curb and sidewalk usage. MDS is far from perfect; legal challenges surrounding data usage will undoubtedly alter its final form. Regardless of legal outcomes, initiatives like MDS exemplify the power of mobility systems that aggregate data.
Aggregating systems also play a pivotal role in our logistics networks. When a company in Detroit orders a pallet of products from a Berlin-based entity, it must decide which combination of air, rail, and sea best meets its goals. If employees in Detroit are to have insight into their order’s status and location through the journey, every logistics company along the value chain would need to collaborate. Currently, that is not entirely possible, but promising startups like Tradelens are building open platforms that facilitate communication between logistics operators.
While Tradelens has taken an open approach to logistics operator communication, companies like Cainaio have taken a private system integrator approach. The initiative was initially launched as a joint venture between Alibaba and large operators to modernize China’s logistics system. At the time, China’s underdeveloped logistics network was a hindrance to Alibaba’s growth. Since 2014, Cainiao has collaborated with hundreds of logistics operators and aggregated an immense network whose aim is to deliver domestic parcels in less than 24 hours and worldwide in less than 72 hours.
Orchestration
Compared to the coordinating and aggregating functions of mobility systems, orchestration systems are the most developed. Orchestration takes full advantage of the aggregated data to finetune mobility systems in real-time. This could be a reaction to traffic patterns changing or automatically increasing public transport frequencies in populated areas during inclement weather. An example of this is Uber’s dynamic pricing model, which varies based on driver supply, ride demand, time of day, weather conditions, and even your phone’s battery level. Orchestrating systems like this ingest and analyze vast amounts of information to direct real-time movement within mobility systems.
While data like your battery level and road conditions may not always seem relevant, orchestrating systems gain their advantage from using this analogous information drive decision making. The use of this information can be thought of as oracles.
Oracles allow for external data to be fed into systems to facilitate more efficient operations. To borrow from biology, oracles are selectively permeable membranes, allowing only the designated data to cross boundaries. Oracles allow for two systems to work even when their overarching goals are dissimilar.
Outlook
Today’s mobility challenges were caused by entities working in silos. Moving forward, mobility systems, regardless of their objectives, must be designed with interoperable functionality. If we are to leverage the world’s best algorithms, we must work to ensure that our systems encourage entrepreneurs and long-established entities alike to develop technologies that are in the best interest of us, our communities, and the environment.
Systems like MDS can serve as a starting point for developing robust platforms that harmonize data collection and ease sharing in transportation. An open-source, consumer-privacy-focused approach to sharing data is necessary for the development of robust, interoperable systems. Hopefully, MDS can be used as a basis for the development of open mobility data standards that govern our streets, eventually including transportation network companies (Uber, Lyft, and taxis) and public transportation companies. These standard data protocols allow our mobility systems to move to the next level in which relevant operators could use the power of aggregated solutions to drive better provisioning of roadways and more efficient operations that would make all of our lives better.
We’ve focused on the logistics examples in this article for ease of understanding, but issues surrounding mobility systems apply to public transportation, personal transportation, fleet management, and many others. As we stated, mobility data sets are robust and extensive, providing opportunities for systems to coordinate, aggregate, and orchestrate irrespective of the material being moved (person, energy, data, goods) and transportation mode. The more robust our mobility systems, the easier it will be to build and deploy applications targeted towards end-users. Over the last decade, much of our attention has focused on applications, but the applications (and those we’ve yet to download) require a solid infrastructure base and a robust systems layer. Mobility 4.0 can only be realized with a balanced structure that includes all three.
Our next article will discuss the third and final layer of the ISA Framework: applications.
This article would not have been possible without the invaluable input of Christian Saur, Brian Hotani, and the Assembly Ventures Team.
