Decentralized Approaches to Adaptive Traffic Control
Decentralized Approaches to Adaptive Traffic Control
复制标题
自适应交通控制的分散方法
DOI:
10.1007/978-3-540-75261-5_8
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发表时间:
2007
期刊:
影响因子:
--
通讯作者:
D. Helbing
中科院分区:
文献类型:
--
作者:
A. Kesting;M. Schönhof;S. Lämmer;M. Treiber;D. Helbing
Traffic congestion is a severe problem on freeways in many countries. According to a study of the European Commission [1], its impact amounts to 0.5% of the gross national product and will increase even up to 1% in the year 2010. Since in most countries, building new transport infrastructure is no longer an appropriate option, there are many approaches towards a more effective road usage and a more ‘intelligent’way of increasing the capacity of the road network and thus of decreasing congestion. Due to the potential benefits and the expected technological progress, there is considerable research in the area of intelligent transport systems (ITS)[2, 3]. Examples of advanced traffic control systems are, eg, ramp metering, adaptive speed limits, or dynamic and individual route guidance. The latter examples are based on a centralized traffic management, which controls the operation and the system’s response to a given traffic situation.However, 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), including cheap optical, radar, video, or infrared sensors and mobile communication technologies promise new solutions leading from the classical, centralized control to decentralized approaches in the sense of collective (swarm) intelligence and ad hoc networks. Such concepts reduce the problem of data flooding by restricting to the locally relevant information
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影响因子:
2.4
作者:
Brockfeld, E;Barlovic, R;Schreckenberg, M
通讯作者:
Schreckenberg, M
DOI:
--
发表时间:
2006
期刊:
影响因子:
--
作者:
M. Schönhof;M. Treiber;Arne Kesting;D. Helbing
通讯作者:
D. Helbing
DOI:
10.1016/j.physa.2006.01.047
发表时间:
2006-03
影响因子:
3.3
作者:
Stefan Lammer;H. Kori;K. Peters;D. Helbing
通讯作者:
Stefan Lammer;H. Kori;K. Peters;D. Helbing
DOI:
--
发表时间:
2006
期刊:
影响因子:
--
作者:
R. Lindgren;R. Bertini;D. Helbing;M. Schönhof
通讯作者:
M. Schönhof