5 research outputs found
Deterministic approach to microscopic three-phase traffic theory
Two different deterministic microscopic traffic flow models, which are in the
context of the Kerner's there-phase traffic theory, are introduced. In an
acceleration time delay model (ATD-model), different time delays in driver
acceleration associated with driver behaviour in various local driving
situations are explicitly incorporated into the model. Vehicle acceleration
depends on local traffic situation, i.e., whether a driver is within the free
flow, or synchronized flow, or else wide moving jam traffic phase. In a speed
adaptation model (SA-model), vehicle speed adaptation occurs in synchronized
flow depending on driving conditions. It is found that the ATD- and SA-models
show spatiotemporal congested traffic patterns that are adequate with empirical
results. In the ATD- and SA-models, the onset of congestion in free flow at a
freeway bottleneck is associated with a first-order phase transition from free
flow to synchronized flow; moving jams emerge spontaneously in synchronized
flow only. Differences between the ATD- and SA-models are studied. A comparison
of the ATD- and SA-models with stochastic models in the context of three phase
traffic theory is made. A critical discussion of earlier traffic flow theories
and models based on the fundamental diagram approach is presented.Comment: 40 pages, 14 figure
Criterion for traffic phases in single vehicle data and empirical test of a microscopic three-phase traffic theory
A microscopic criterion for distinguishing synchronized flow and wide moving
jam phases in single vehicle data measured at a single freeway location is
presented. Empirical local congested traffic states in single vehicle data
measured on different days are classified into synchronized flow states and
states consisting of synchronized flow and wide moving jam(s). Then empirical
microscopic characteristics for these different local congested traffic states
are studied. Using these characteristics and empirical spatiotemporal
macroscopic traffic phenomena, an empirical test of a microscopic three-phase
traffic flow theory is performed. Simulations show that the microscopic
criterion and macroscopic spatiotemporal objective criteria lead to the same
identification of the synchronized flow and wide moving jam phases in congested
traffic. It is found that microscopic three-phase traffic models can explain
both microscopic and macroscopic empirical congested pattern features. It is
obtained that microscopic distributions for vehicle speed difference as well as
fundamental diagrams and speed correlation functions can depend on the spatial
co-ordinate considerably. It turns out that microscopic optimal velocity (OV)
functions and time headway distributions are not necessarily qualitatively
different, even if local congested traffic states are qualitatively different.
The reason for this is that important spatiotemporal features of congested
traffic patterns are it lost in these as well as in many other macroscopic and
microscopic traffic characteristics, which are widely used as the empirical
basis for a test of traffic flow models, specifically, cellular automata
traffic flow models.Comment: 27 pages, 16 figure
Optimised Traffic Flow at a Single Intersection: Traffic Responsive signalisation
We propose a stochastic model for the intersection of two urban streets. The
vehicular traffic at the intersection is controlled by a set of traffic lights
which can be operated subject to fix-time as well as traffic adaptive schemes.
Vehicular dynamics is simulated within the framework of the probabilistic
cellular automata and the delay experienced by the traffic at each individual
street is evaluated for specified time intervals. Minimising the total delay of
both streets gives rise to the optimum signalisation of traffic lights. We
propose some traffic responsive signalisation algorithms which are based on the
concept of cut-off queue length and cut-off density.Comment: 10 pages, 11 eps figs, to appear in J. Phys.
Traffic and Related Self-Driven Many-Particle Systems
Since the subject of traffic dynamics has captured the interest of
physicists, many astonishing effects have been revealed and explained. Some of
the questions now understood are the following: Why are vehicles sometimes
stopped by so-called ``phantom traffic jams'', although they all like to drive
fast? What are the mechanisms behind stop-and-go traffic? Why are there several
different kinds of congestion, and how are they related? Why do most traffic
jams occur considerably before the road capacity is reached? Can a temporary
reduction of the traffic volume cause a lasting traffic jam? Under which
conditions can speed limits speed up traffic? Why do pedestrians moving in
opposite directions normally organize in lanes, while similar systems are
``freezing by heating''? Why do self-organizing systems tend to reach an
optimal state? Why do panicking pedestrians produce dangerous deadlocks? All
these questions have been answered by applying and extending methods from
statistical physics and non-linear dynamics to self-driven many-particle
systems. This review article on traffic introduces (i) empirically data, facts,
and observations, (ii) the main approaches to pedestrian, highway, and city
traffic, (iii) microscopic (particle-based), mesoscopic (gas-kinetic), and
macroscopic (fluid-dynamic) models. Attention is also paid to the formulation
of a micro-macro link, to aspects of universality, and to other unifying
concepts like a general modelling framework for self-driven many-particle
systems, including spin systems. Subjects such as the optimization of traffic
flows and relations to biological or socio-economic systems such as bacterial
colonies, flocks of birds, panics, and stock market dynamics are discussed as
well.Comment: A shortened version of this article will appear in Reviews of Modern
Physics, an extended one as a book. The 63 figures were omitted because of
storage capacity. For related work see http://www.helbing.org