21 research outputs found
Autonomous detection and anticipation of jam fronts from messages propagated by inter-vehicle communication
In this paper, a minimalist, completely distributed freeway traffic
information system is introduced. It involves an autonomous, vehicle-based jam
front detection, the information transmission via inter-vehicle communication,
and the forecast of the spatial position of jam fronts by reconstructing the
spatiotemporal traffic situation based on the transmitted information. The
whole system is simulated with an integrated traffic simulator, that is based
on a realistic microscopic traffic model for longitudinal movements and lane
changes. The function of its communication module has been explicitly validated
by comparing the simulation results with analytical calculations. By means of
simulations, we show that the algorithms for a congestion-front recognition,
message transmission, and processing predict reliably the existence and
position of jam fronts for vehicle equipment rates as low as 3%. A reliable
mode of operation already for small market penetrations is crucial for the
successful introduction of inter-vehicle communication. The short-term
prediction of jam fronts is not only useful for the driver, but is essential
for enhancing road safety and road capacity by intelligent adaptive cruise
control systems.Comment: Published in the Proceedings of the Annual Meeting of the
Transportation Research Board 200
DECENTRALIZED APPROACHES TO ADAPTIVE TRAFFIC CONTROL AND AN EXTENDED LEVEL OF SERVICE CONCEPT
Traffic systems are highly complex multi-component systems suffering from instabilities and non-linear dynamics, including chaos. This is caused by the non-linearity of interactions, delays, and fluctuations, which can trigger phenomena such as stop-and-go waves, noise-induced breakdowns, or slower-is-faster effects. The recently upcoming information and communication technologies (ICT) promise new solutions leading from the classical, centralized control to decentralized approaches in the sense of collective (swarm) intelligence and ad hoc networks. An interesting application field is adaptive, self-organized traffic control in urban road networks. We present control principles that allow one to reach a self-organized synchronization of traffic lights. Furthermore, vehicles will become automatic traffic state detection, data management, and communication centers when forming ad hoc networks through inter-vehicle communication (IVC). We discuss the mechanisms and the efficiency of message propagation on freeways by short-range communication. Our main focus is on future adaptive cruise control systems (ACC), which will not only increase the comfort and safety of car passengers, but also enhance the stability of traffic flows and the capacity of the road (“traffic assistance”). We present an automated driving strategy that adapts the operation mode of an ACC system to the autonomously detected, local traffic situation. The impact on the traffic dynamics is investigated by means of a multi-lane microscopic traffic simulation. The simulation scenarios illustrate the efficiency of the proposed driving strategy. Already an ACC equipment level of 10% improves the traffic flow quality and reduces the travel times for the drivers drastically due to delaying or preventing a breakdown of the traffic flow. For the evaluation of the resulting traffic quality, we have recently developed an extended level of service concept (ELOS). We demonstrate our concept on the basis of travel times as the most important variable for a user-oriented quality of service
Volatile Decision Dynamics: Experiments, Stochastic Description, Intermittency Control, and Traffic Optimization
The coordinated and efficient distribution of limited resources by individual
decisions is a fundamental, unsolved problem. When individuals compete for road
capacities, time, space, money, goods, etc., they normally make decisions based
on aggregate rather than complete information, such as TV news or stock market
indices. In related experiments, we have observed a volatile decision dynamics
and far-from-optimal payoff distributions. We have also identified ways of
information presentation that can considerably improve the overall performance
of the system. In order to determine optimal strategies of decision guidance by
means of user-specific recommendations, a stochastic behavioural description is
developed. These strategies manage to increase the adaptibility to changing
conditions and to reduce the deviation from the time-dependent user
equilibrium, thereby enhancing the average and individual payoffs. Hence, our
guidance strategies can increase the performance of all users by reducing
overreaction and stabilizing the decision dynamics. These results are highly
significant for predicting decision behaviour, for reaching optimal behavioural
distributions by decision support systems, and for information service
providers. One of the promising fields of application is traffic optimization.Comment: For related work see http://www.helbing.or
Saving Human Lives: What Complexity Science and Information Systems can Contribute
We discuss models and data of crowd disasters, crime, terrorism, war and
disease spreading to show that conventional recipes, such as deterrence
strategies, are often not effective and sufficient to contain them. Many common
approaches do not provide a good picture of the actual system behavior, because
they neglect feedback loops, instabilities and cascade effects. The complex and
often counter-intuitive behavior of social systems and their macro-level
collective dynamics can be better understood by means of complexity science. We
highlight that a suitable system design and management can help to stop
undesirable cascade effects and to enable favorable kinds of self-organization
in the system. In such a way, complexity science can help to save human lives.Comment: 67 pages, 25 figures; accepted for publication in Journal of
Statistical Physics [for related work see http://www.futurict.eu/
The Relative Mobility of Vehicles Improves the Performance of Information Flow in Vehicle Ad Hoc Networks
Transportation networks, Vehicular ad hoc networks, Information flow, Reachability, Simulation,