Connected intersections and traffic signals have huge potential in terms of regulating traffic, reducing journey times, decreasing congestion, and supporting lower emissions. However, there are many questions still unanswered when it comes to this cutting-edge innovation.
- Do dynamic traffic signals really meet these goals and improve vehicle traffic flow, or is it a lot of hype?
- If put into place by governments and municipalities, will the benefits be worth the infrastructure costs?
- Will traditional vehicles suffer if signals are built with connected and autonomous vehicles in mind?
A recent study from the Università della Calabria, Floating Car Data Adaptive Traffic Signals: A Description of the First Real-Time Experiment with “Connected” Vehicles, showed the results of regulating traffic signal in real-time with connected vehicle data and can help us to answer these questions.
Reducing Congestion: By the Numbers
Based on their simulation, the researchers expected to find a significant benefit to using real-time car data to regulate the intersection and improve vehicle traffic flow in their experiment. However, their results exceeded their expectations in every way. While they assumed the total outflow to have a 44% gain based on their simulation, in their real-world experiment, it was actually 116%. Predictions put reduced travel time at 55% when in reality it was over 73%. The increase in speed jumped 272%, in comparison to 120% in simulation.
Currently, most adaptive traffic signals are regulated with technology such as induction loop detectors. As these are unable to access the speed and position of individual vehicles, the datasets this tech uses are limited to traffic flow counts at specific static locations. In contrast, connected vehicle data gives a lot more information, drilled down to specific vehicles, and is cheaper to benefit from, too. This means that using connected car data is actually more accurate and impactful, as well as easier and more cost-effective to implement.
Unsurprisingly, the researchers concluded that “These results demonstrated that according to simulations, the reduction in overall travel time justifies the implementation of the proposed system by city administrations that would be able to regulate traffic signals using inexpensive Floating Car Data (FCD).”
What about Traditional Vehicles?
In this case, the study was completed with 100% connected vehicle data, simulated by a smartphone application. Of course, the benefits will vary depending on how many connected vehicles are involved, and how badly regulated any given intersection is, to begin with. In the study, we discussed above for example, with the fewest number of connected vehicles the reduction in travel time was just 5%, while this increased to 70% when the connected vehicles increased to 100%.
If you’re worried about the cost/benefit analysis, however, this fear might be unwarranted. After all, according to McKinsey Research, by 2030, 95% of new vehicles will be connected, and even today that number stands at around 50%. If you consider that the average lifespan of a car is around 8 years or 150,000 miles – it’s safe to assume that by the late 2030s, almost all vehicles will be connected, with that number rising exponentially over the next decade to meet that prediction.
In general, studies have shown that the number of connected vehicles on the road only has to reach 30% before these kinds of benefits are seen for all vehicles, which means in developed countries we’re likely to already be there. When 30% of connected vehicles cooperate with the system by agreeing to share their real-time location, speed, and hazard information, traditional vehicles will all benefit from the connected system. This also offers an equitable solution for those who do not have a connected vehicle yet, if for example, they cannot afford an upgrade, and also allows ample room for the privacy rights of those who do not wish to share their data with the system.
What Else Could We Use Dynamic Traffic Signals for?
In this study, connected vehicle data was used to influence simple green traffic signals, looking at travel time to assess congestion. However, this data could also be used more widely to benefit from a lot more. For example, variable message signs could provide real-time insight into hazardous weather conditions, based on rain intensity data. Messages regarding an accident or incident could be provided from hard-braking information or vehicle breakdowns. This system could also integrate with emergency vehicles for incident response or to trigger chain controls in snowy weather for example.
Predictive traffic modeling is already being trialed for dynamic improvements to highways and other busy roads, such as automatically adapting the hard shoulder into an additional lane when congestion is at a high, dynamic merge control or speed limits, or innovation such as transit signal priority for emergency vehicles or public transport.
If You’re Not Using Connected Vehicle Data to Improve Vehicle Traffic Flow – Now’s the Time
It’s clear that connected vehicle data is the key to unlocking the impact of adaptive traffic signals to improve vehicle traffic flow, and has the potential to provide all the assumed benefits and more, reducing travel times through lowered congestion, having a knock-on impact on emissions and improving the regulation of traffic, especially in hazardous situations.
The full power of dynamic traffic signals and adaptive road systems are in their infancy, and the winners will be the early adopters of this innovative and low-risk technology.
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