What follows is an example of how to apply three concepts to drive innovation. It is not intended to comprehensively address the stated objective.
Reduce fuel consumption
- Consider the system in which the target of your innovation operates
- Look for ways to use or combine existing technologies, preferably ones that are inexpensive and easy to implement.
- Address issues as problems to be solved, not dead ends
Applying Concept #1
Attempts to reduce fuel consumption commonly focus on efficiency. While this approach will continue to be important, its application requires decades to achieve meaningful impact. What measures can be applied to complement it?
Applying the first concept, consider the "system" in which cars operate. This includes roads and traffic lights. How can these be optimized so that cars use less fuel?
Needless idling is only part of the problem, even more fuel is wasted regaining speed after an avoidable slowdown. Imagine the inefficiencies you personally encounter multiplied times the estimated 250 million plus vehicles just on US roadways. Improvements in traffic signal operation would dramatically impact fuel consumption.
The core problem is that traffic lights have a shortsighted view of approaching traffic. Currently sensors under the roadway provide only rudimentary information. As a substitute for more comprehensive awareness, engineers time light changes based upon traffic volume predictions for the time of day. By the most generous assessment, this is a crude substitute for data based decision making.
The solution to this problem lies in giving lights sufficient information on which to base decisions. One solution, already being tested, proposes installing "short-range wireless transmitters in cars and elements of the road infrastructure". However, this idea underscores the problems associated with applying innovations to system elements instead of the system itself. It requires each car to have a transmitter.
Another solution being tested leverages devices that are already in most cars: smartphones. SignalGuru attempts to use a "collection of mobile phones to detect and predict the traffic signal schedule. ... Based on when the signal ahead will turn green, drivers can then adjust speed so as to avoid coming to a complete halt." The developers claim that in tests "vehicle fuel consumption measurements show savings of 20.3%, on average".
While these results are impressive, this solution is still suboptimal and creates collateral problems. For example, drivers could be distracted by the need to monitor and act on the device's recommendations. More importantly, the device does nothing to reduce time wasted by the outdated traffic control technology.
Applying Concept #2
With the needed information, a traffic light could use computer algorithms to eliminate unnecessary slowdowns and stops. That makes the key question: "What existing technologies can be combined to cost-effectively provide traffic lights with the requisite information to change at optimal times?"
Hint: The crux of the solution may be sitting on your desk.
- Detect cars at varying distances on each side of the traffic control device.
- Transmit this information to a "smart" traffic light that decides when to change
Many inexpensive off-the-shelf webcams can detect motion (even at night) and with the proper hardware Wi-Fi can securely transmit information to nearby devices. The processor in most smartphones is powerful enough to quickly run the algorithms required to process the incoming information. Together these components (based on existing technologies) provide us with a conceptual framework to dramatically improve traffic light operation.
Applying Concept #3
With a conceptual framework in place, it's time to address the implementation details.
The good news is that even the most blurry eyed camera can detect the motion of a car. The communication that's required between devices shouldn't be much of a problem either. But, of course, there are still problems to solve - lots of them.
As an example, "off-the-shelf webcams" aren't going to endure the temperature extremes they'd experience in most of the world's cities. And how would engineers power the webcams? Can existing traffic lights be retrofitted with "brains" that allow them to process the incoming data? These are only a few of the implementation details that need to be addressed.
This is the moment where innovators need to continually ask, "How can we make this work?" The path from concept to implementation is often a difficult one. Engineers have to iteratively solve each problem until a feasible solution is reached.
Smart traffic lights aren't the only way to smooth traffic flow. Several effective low tech solutions already exist. While they limit unnecessary stops, their lack of widespread adoption limits their impact on fuel consumption. These solutions include traffic roundabouts, single-point urban interchanges (SPUI) and the so-called Michigan Left Turn.
The slow adoption of these ideas highlights a more significant problem that all innovators face: acceptance.