966 research outputs found
Car-oriented mean-field theory for traffic flow models
We present a new analytical description of the cellular automaton model for
single-lane traffic. In contrast to previous approaches we do not use the
occupation number of sites as dynamical variable but rather the distance
between consecutive cars. Therefore certain longer-ranged correlations are
taken into account and even a mean-field approach yields non-trivial results.
In fact for the model with the exact solution is reproduced. For
the fundamental diagram shows a good agreement with results from
simulations.Comment: LaTex, 10 pages, 2 postscript figure
ΠΠ»ΠΈΡΠ½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π½Π°Π±ΠΎΡΠ° Π΄Π°Π½Π½ΡΡ Π½Π° ΠΏΠΎΠ³ΡΠ΅ΡΠ½ΠΎΡΡΡ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠ»ΠΎΡΠ°Π΄ΠΈ ΠΏΠΈΠΊΠ° Π² Π³Π°ΠΌΠΌΠ°-ΡΠΏΠ΅ΠΊΡΡΠΎΠΌΠ΅ΡΡΠΈΠΈ
Hysteresis phenomenon in deterministic traffic flows
We study phase transitions of a system of particles on the one-dimensional
integer lattice moving with constant acceleration, with a collision law
respecting slower particles. This simple deterministic ``particle-hopping''
traffic flow model being a straightforward generalization to the well known
Nagel-Schreckenberg model covers also a more recent slow-to-start model as a
special case. The model has two distinct ergodic (unmixed) phases with two
critical values. When traffic density is below the lowest critical value, the
steady state of the model corresponds to the ``free-flowing'' (or ``gaseous'')
phase. When the density exceeds the second critical value the model produces
large, persistent, well-defined traffic jams, which correspond to the
``jammed'' (or ``liquid'') phase. Between the two critical values each of these
phases may take place, which can be interpreted as an ``overcooled gas'' phase
when a small perturbation can change drastically gas into liquid. Mathematical
analysis is accomplished in part by the exact derivation of the life-time of
individual traffic jams for a given configuration of particles.Comment: 22 pages, 6 figures, corrected and improved version, to appear in the
Journal of Statistical Physic
Affective Experience, Desire, and Reasons for Action
What is the role of affective experience in explaining how our desires provide us with reasons for action? When we desire that p, we are thereby disposed to feel attracted to the prospect that p, or to feel averse to the prospect that not-p. In this paper, we argue that affective experiences β including feelings of attraction and aversion β provide us with reasons for action in virtue of their phenomenal character. Moreover, we argue that desires provide us with reasons for action only insofar as they are dispositions to have affective experiences. On this account, affective experience has a central role to play in explaining how desires provide reasons for action
A Model for the Propagation of Sound in Granular Materials
This paper presents a simple ball-and-spring model for the propagation of
small amplitude vibrations in a granular material. In this model, the
positional disorder in the sample is ignored and the particles are placed on
the vertices of a square lattice. The inter-particle forces are modeled as
linear springs, with the only disorder in the system coming from a random
distribution of spring constants. Despite its apparent simplicity, this model
is able to reproduce the complex frequency response seen in measurements of
sound propagation in a granular system. In order to understand this behavior,
the role of the resonance modes of the system is investigated. Finally, this
simple model is generalized to include relaxation behavior in the force network
-- a behavior which is also seen in real granular materials. This model gives
quantitative agreement with experimental observations of relaxation.Comment: 21 pages, requires Harvard macros (9/91), 12 postscript figures not
included, HLRZ preprint 6/93, (replacement has proper references included
Cellular Automata Simulating Experimental Properties of Traffic Flows
A model for 1D traffic flow is developed, which is discrete in space and
time. Like the cellular automaton model by Nagel and Schreckenberg [J. Phys. I
France 2, 2221 (1992)], it is simple, fast, and can describe stop-and-go
traffic. Due to its relation to the optimal velocity model by Bando et al.
[Phys. Rev. E 51, 1035 (1995)], its instability mechanism is of deterministic
nature. The model can be easily calibrated to empirical data and displays the
experimental features of traffic data recently reported by Kerner and Rehborn
[Phys. Rev. E 53, R1297 (1996)].Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.html and
http://traffic.comphys.uni-duisburg.de/member/home_schreck.htm
Π‘ΠΎΠ·Π΄Π°Π½ΠΈΠ΅ ΠΈΠ·Π½ΠΎΡΠΎΡΡΠΎΠΉΠΊΠΎΠ³ΠΎ ΠΏΠΎΠΊΡΡΡΠΈΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π½Π΅ΠΏΡΠ΅ΡΡΠ²Π½ΠΎΠ³ΠΎ ΠΈ ΠΈΠΌΠΏΡΠ»ΡΡΠ½ΠΎΠ³ΠΎ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠ³ΠΎ Π»ΡΡΠ°
Π Π½Π°ΡΡΠΎΡΡΠ΅ΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²Π»ΠΈΡΠ½ΠΈΡ ΠΈΠΌΠΏΡΠ»ΡΡΠ½ΠΎΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅Π³ΠΎ ΠΎΡΠΆΠΈΠ³Π° Π½Π° ΡΡΡΡΠΊΡΡΡΡ ΠΈ ΡΠ²Π΅ΡΠ΄ΠΎΡΡΡ ΠΏΠΎΠΊΡΡΡΠΈΠΉ ΠΈΠ· Ρ
ΡΠΎΠΌΠΎ-Π²Π°Π½Π°Π΄ΠΈΠ΅Π²ΠΎΠ³ΠΎ ΡΡΠ³ΡΠ½Π°. ΠΠΎΠΊΡΡΡΠΈΡ Π±ΡΠ»ΠΈ ΠΏΠΎΠ»ΡΡΠ΅Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎ-Π»ΡΡΠ΅Π²ΠΎΠΉ Π½Π°ΠΏΠ»Π°Π²ΠΊΠΈ Π½Π° ΠΏΠΎΠ΄Π»ΠΎΠΆΠΊΠ΅ ΠΈΠ· ΠΌΠ°Π»ΠΎΡΠ³Π»Π΅ΡΠΎΠ΄ΠΈΡΡΠΎΠΉ ΡΡΠ°Π»ΠΈ. ΠΠΎΡΠ»Π΅ ΡΠ»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠ²Π΅ΡΡ
Π½ΠΎΡΡΠΈ ΠΏΠΎΠΊΡΡΡΠΈΠΉ Π±ΡΠ»ΠΈ ΠΎΠ±ΡΠ°Π±ΠΎΡΠ°Π½Ρ Π»ΠΎΠΊΠ°Π»ΡΠ½ΠΎΠΈΠΌΠΏΡΠ»ΡΡΠ½ΡΠΌ ΡΡΠΎΠΊΡΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠΌ Π² ΡΠΎΡΠΊΡ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΡΠΌ ΠΏΡΡΠΊΠΎΠΌ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ, ΡΡΠΎ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ Π·ΠΎΠ½Ρ ΡΠΎΡΡΠΎΡΡ ΠΈΠ· Π΄Π²ΡΡ
ΡΠ°Π·. ΠΠ΅ΡΠ²Π°Ρ ΡΠ°Π·Π° - ΠΏΠ΅ΡΠ΅ΡΡΡΠ΅Π½Π½ΡΠΉ Π°ΡΡΡΠ΅Π½ΠΈΡ. ΠΡΠΎΡΠ°Ρ Π»ΠΎΠΊΠ°Π»ΡΠ½ΠΎ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΠ΅ Π² ΠΎΠ±ΡΠ΅ΠΌΠ΅ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π·ΠΎΠ½Ρ Π·Π°ΡΠΎΠ΄ΡΡΠΈ ΡΠ²ΡΠ΅ΠΊΡΠΈΠΊΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΠ·ΠΌΠ΅ΡΠ΅Π½ΠΈΠΉ ΡΠΈΡΡΠ΅ΠΌΠΎΠΉ NanoTest ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ, ΡΡΠΎ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ Π·ΠΎΠ½Ρ ΠΈΠΌΠ΅ΡΡ Π½ΠΈΠ·ΠΊΠΈΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΡΠ²Π΅ΡΠ΄ΠΎΡΡΠΈ. ΠΠΈΠ·ΠΊΠΈΠ΅ Π·Π½Π°ΡΠ΅Π½ΠΈΡ ΡΠ²Π΅ΡΠ΄ΠΎΡΡΠΈ, Π²Π΅ΡΠΎΡΡΠ½ΠΎ, ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½ΠΎ Π½Π°Π»ΠΈΡΠΈΠ΅ΠΌ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΌΠ° ΠΏΠ΅ΡΠ΅ΡΡΡΠ΅Π½Π½ΠΎΠ³ΠΎ Π°ΡΡΡΠ΅Π½ΠΈΡΠ° Π² ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠΉ Π·ΠΎΠ½Π΅. ΠΡΠΆΠΈΠ³ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΌΡ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΡ ΡΠ²Π΅ΡΠ΄ΠΎΡΡΠΈ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π·ΠΎΠ½. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΎΡΠΆΠΈΠ³Π° (500Β°Π‘ ) ΠΏΠ΅ΡΠ΅ΡΡΡΠ΅Π½Π½ΡΠΉ Π°ΡΡΡΠ΅Π½ΠΈΡ ΡΠ°ΡΠΏΠ°Π΄Π°Π΅ΡΡΡ. ΠΠΎΠ²ΡΡΠ΅Π½ΠΈΠ΅ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΡ ΠΎΡΠΆΠΈΠ³Π° Π΄ΠΎ 1100Β°Π‘ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ ΡΠΎΡΡΡ ΠΈ ΠΊΠΎΠ°Π³ΡΠ»ΡΡΠΈΠΈ ΠΊΠ°ΡΠ±ΠΈΠ΄Π½ΠΎΠΉ ΡΠ°Π·Ρ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
Π·ΠΎΠ½
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