136
7 Digitally Assisted Self-Organization
findings imply that most traffic jams are caused by a combination of three factors:
a bottleneck, dense traffic and a disruption to the traffic flow. Unfortunately, the
effective road capacity breaks down just when the full capacity of the road is needed
the most. The resulting traffic jam can last for hours and can increase travel times
by a factor of two, five or ten. The collapse of traffic flow can be even triggered by
a single truck overtaking another one!
It is perhaps even more surprising that the traffic flow becomes unstable when
the maximum traffic volume on the freeway is reached—exactly when traffic is most
efficient from an “economic” point of view. As a result of the resulting breakdown,
about 30% of the freeway capacity is lost due to unfavorable vehicle interactions.
This effect is called “capacity drop”. Therefore, in order to prevent a capacity drop
and to avoid traffic jams, we must either keep the traffic volume sufficiently below
its maximum value or stabilize high traffic flows by means of modern information
and communication technologies. In fact, as I will explain in the following, “assisted
self-organization” can do this by using real-time measurements and suitable adaptive
feedbacks, which slightly modify the interactions between cars.
7.4 Avoiding Traffic Jams
Since the early days of computers, traffic engineers always sought ways to improve
the flow of traffic. The traditional “telematics” approach to reduce congestion was
based on the concept of a traffic control center that collects information with a lot of
traffic sensors. This control center would then centrally determine the best strategy
and implement it in a top-down way, by introducing variable speed limits on motorways or using traffic lights at junctions, for example. Recently, however, researchers
and engineers have started to explore a different and more efficient approach, which
is based on distributed control.
In the following, I will show that local interactions may lead to a favorable kind of
self-organization of a complex dynamical system, if the components of the system
(in the above example, the vehicles) interact with each other in a suitable way.
Moreover, I will demonstrate that only a slight modification of these interactions
can turn bad outcomes (such as congestion) into good outcomes (such as free traffic
flow). Therefore, in complex dynamical systems, “interaction design”, also known
as “mechanism design”, is the secret of success.
7.5 Assisting Traffic Flow
Some years ago, Martin Treiber, Arne Kesting, Martin Schönhof, and I had the
pleasure of being involved in the development of a new traffic assistance system
together with a research team of Volkswagen. The system we invented is based on
the observation that, in order to prevent (or delay) the traffic flow from breaking
7 Digitally Assisted Self-Organization
findings imply that most traffic jams are caused by a combination of three factors:
a bottleneck, dense traffic and a disruption to the traffic flow. Unfortunately, the
effective road capacity breaks down just when the full capacity of the road is needed
the most. The resulting traffic jam can last for hours and can increase travel times
by a factor of two, five or ten. The collapse of traffic flow can be even triggered by
a single truck overtaking another one!
It is perhaps even more surprising that the traffic flow becomes unstable when
the maximum traffic volume on the freeway is reached—exactly when traffic is most
efficient from an “economic” point of view. As a result of the resulting breakdown,
about 30% of the freeway capacity is lost due to unfavorable vehicle interactions.
This effect is called “capacity drop”. Therefore, in order to prevent a capacity drop
and to avoid traffic jams, we must either keep the traffic volume sufficiently below
its maximum value or stabilize high traffic flows by means of modern information
and communication technologies. In fact, as I will explain in the following, “assisted
self-organization” can do this by using real-time measurements and suitable adaptive
feedbacks, which slightly modify the interactions between cars.
7.4 Avoiding Traffic Jams
Since the early days of computers, traffic engineers always sought ways to improve
the flow of traffic. The traditional “telematics” approach to reduce congestion was
based on the concept of a traffic control center that collects information with a lot of
traffic sensors. This control center would then centrally determine the best strategy
and implement it in a top-down way, by introducing variable speed limits on motorways or using traffic lights at junctions, for example. Recently, however, researchers
and engineers have started to explore a different and more efficient approach, which
is based on distributed control.
In the following, I will show that local interactions may lead to a favorable kind of
self-organization of a complex dynamical system, if the components of the system
(in the above example, the vehicles) interact with each other in a suitable way.
Moreover, I will demonstrate that only a slight modification of these interactions
can turn bad outcomes (such as congestion) into good outcomes (such as free traffic
flow). Therefore, in complex dynamical systems, “interaction design”, also known
as “mechanism design”, is the secret of success.
7.5 Assisting Traffic Flow
Some years ago, Martin Treiber, Arne Kesting, Martin Schönhof, and I had the
pleasure of being involved in the development of a new traffic assistance system
together with a research team of Volkswagen. The system we invented is based on
the observation that, in order to prevent (or delay) the traffic flow from breaking