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From Driving Error to Traffic Jam

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Traffic researcher and congestion expert Professor Michael Schreckenberg (University of Duisburg-Essen) talks about one of the main sources of aggravation in traffic. His work offers important insights into how to improve the mobility of the future.
Andreas Neemann, July 04, 2019
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Andreas Neemann wrote his first ZF text in 2001 about 6HP transmissions. Since then, the automotive writer has filled many publications for internal and external readers, showcasing his passion for the Group's more complex subjects.

Professor Schreckenberg, what actually causes traffic congestion?
On interstates, in 60 to 70 percent of cases, it is quite simply because there are too many vehicles on the road. There is too much traffic heading in the same direction. This rapidly gives rise to slow-moving traffic that is still flowing at between 10 and 30 km/h. It is not until individual road users brake sharply or, by changing lanes abruptly, force other drivers to apply their brakes that everything comes to a complete stop. A wave of congestion develops that extends in the opposite direction to the flow of traffic at a speed of 15 km/h. In some cases, waves of congestion of this kind can even switch interstates via the exit ramps.
So is human error at the heart of every traffic jam?
In the kind of overload congestion depicted above, that genuinely is the case. Between 30 and 40 percent of all traffic jams have a specific cause, such as an accident or a narrowing in lane due to roadwork. Here too, individual driving behavior can contribute to the formation of a traffic jam, but not to the same extent. One example of this is how well drivers apply the “zipper merge” – letting alternate vehicles merge into the open lane. The same applies to the two percent of traffic jams that are caused by weather conditions, such as poor visibility due to fog or heavy rain.

Are the (German) interstates becoming increasingly prone to congestion?
Yes, but that is hardly surprising. The German interstates have a total length of around 13,000 kilometers, which represents a comparably small proportion of the German road network. However, about one-third of all road traffic is concentrated on them.
What data do you draw upon as a congestion researcher?
We have access to digital traffic figures that are updated by the minute. We also make use of what is known as floating car data. This is anonymized data about vehicle movements that we obtain through cooperation with the manufacturers of navigation systems. For analyses on self-contained testing grounds, we collect movement and position data ourselves by using GPS devices.
"Companies must heavily invest in public transportation to reduce the number of traffic jams."
— Prof. Dr. Michael Schreckenberg

What do you do with the raw data?
We develop statistical models to gain a better understanding of the phenomenon of congestion, and ideally to become able to produce forecasts. You could say that we develop a theory about congestion that we then test in practice. We also use the insights we obtain to advise politicians, trade associations, and the industry.
Do gridlocks in downtown areas also have a role to play in the work you do?
Traffic in downtown areas is more difficult to capture in the form of simulations and theoretical models because a great deal of coincidences and reciprocal effects are involved there. Particular examples of this include intersections, stationary traffic, vehicles changing lanes, and other road users such as cyclists and pedestrians.

How great is the financial damage to the national economy caused by traffic congestion?
We produced a sample calculation based on the assumption of a four-kilometer-long traffic jam that has been in existence for four hours across two lanes. The average speed in this traffic jam is 10 km/h instead of 80 km/h. We assumed an average proportion of work-related trips in road traffic, a figure that includes transportation companies and employees. We then computed the total impact on the economy of delays caused solely by this traffic jam, arriving at a figure of between 50,000 and 100,000 euros. If you then extrapolate that figure to the total annual volume of traffic congestion in Germany, the damage amounts to about 80 billion euros each year. The additional environmental pollution caused by traffic congestion is not even included in this calculation yet.

80 billion euros
is approximately the annual financial damage to the German economy incurred by traffic congestion.

What can be done to reduce the number of traffic jams?
The only thing that can help is to reduce the number of vehicles, or at least not to increase that number yet further. This works if other means of transport are available. Public transportation in particular might be the solution here. Companies need to heavily invest in this area. Furthermore, the existing means of transport are not networked sufficiently.
Where does the challenge lie in relation to the intelligent networking of traffic?
If we talk about automated mobility, I see a problem in the traffic mix, because automated vehicles will be traveling alongside vehicles with human drivers. Since self-driving cars act defensively, estimates indicate that the flow of traffic will slow down by 20 percent. This situation changes once the vehicle population consists almost entirely of self-driving cars. At this early stage, I would not expect any miracles from autonomous driving.
What can be done to alleviate urban congestion?
Here too, I view the massive expansion of local public transportation as the best way forward. A few municipalities have already begun offering local public transportation free of charge. The success of intermodal traffic models, in particular those involving a change from private passenger cars to the S-Bahn suburban train services for commuting purposes, depends to a large extent on the availability of park-and-ride car parks. However, many urban centers still lack this parking capacity.

Prof. Dr. Michael Schreckenberg,
a theoretical physicist, conducts research into traffic congestion. The Nagel–Schreckenberg model that he coauthored in 1992 is the most frequently quoted scientific paper on traffic simulation. His institute deals with a vast array of different means of transport, including passenger cars, rail vehicles, ground transit vehicles at airports, and even festival cavalcades.

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