3,676 research outputs found
Reconstructing the Traffic State by Fusion of Heterogeneous Data
We present an advanced interpolation method for estimating smooth
spatiotemporal profiles for local highway traffic variables such as flow, speed
and density. The method is based on stationary detector data as typically
collected by traffic control centres, and may be augmented by floating car data
or other traffic information. The resulting profiles display transitions
between free and congested traffic in great detail, as well as fine structures
such as stop-and-go waves. We establish the accuracy and robustness of the
method and demonstrate three potential applications: 1. compensation for gaps
in data caused by detector failure; 2. separation of noise from dynamic traffic
information; and 3. the fusion of floating car data with stationary detector
data.Comment: For more information see http://www.mtreiber.de or
http://www.akesting.d
Delays, Inaccuracies and Anticipation in Microscopic Traffic Models
We generalize a wide class of time-continuous microscopic traffic models to
include essential aspects of driver behaviour not captured by these models.
Specifically, we consider (i) finite reaction times, (ii) estimation errors,
(iii) looking several vehicles ahead (spatial anticipation), and (iv) temporal
anticipation. The estimation errors are modelled as stochastic Wiener processes
and lead to time-correlated fluctuations of the acceleration.
We show that the destabilizing effects of reaction times and estimation
errors can essentially be compensated for by spatial and temporal anticipation,
that is, the combination of stabilizing and destabilizing effects results in
the same qualitative macroscopic dynamics as that of the respectively
underlying simple car-following model. In many cases, this justifies the use of
simplified, physics-oriented models with a few parameters only. Although the
qualitative dynamics is unchanged, multi-anticipation increase both spatial and
temporal scales of stop-and-go waves and other complex patterns of congested
traffic in agreement with real traffic data. Remarkably, the anticipation
allows accident-free smooth driving in complex traffic situations even if
reaction times exceed typical time headways.Comment: Major revision of the model and the simulations. Particularly, the
number of model parameters has been reduce
Automatic and efficient driving strategies while approaching a traffic light
Vehicle-infrastructure communication opens up new ways to improve traffic
flow efficiency at signalized intersections. In this study, we assume that
equipped vehicles can obtain information about switching times of relevant
traffic lights in advance. This information is used to improve traffic flow by
the strategies 'early braking', 'anticipative start', and 'flying start'. The
strategies can be implemented in driver-information mode, or in automatic mode
by an Adaptive Cruise Controller (ACC). Quality criteria include cycle-averaged
capacity, driving comfort, fuel consumption, travel time, and the number of
stops. By means of simulation, we investigate the isolated strategies and the
complex interactions between the strategies and between equipped and
non-equipped vehicles. As universal approach to assess equipment level effects
we propose relative performance indexes and found, at a maximum speed of 50
km/h, improvements of about 15% for the number of stops and about 4% for the
other criteria. All figures double when increasing the maximum speed to 70
km/h.Comment: Submitted to ITSC - 17th International IEEE Conference on Intelligent
Transportation System
An Open-Source Microscopic Traffic Simulator
We present the interactive Java-based open-source traffic simulator available
at www.traffic-simulation.de. In contrast to most closed-source commercial
simulators, the focus is on investigating fundamental issues of traffic
dynamics rather than simulating specific road networks. This includes testing
theories for the spatiotemporal evolution of traffic jams, comparing and
testing different microscopic traffic models, modeling the effects of driving
styles and traffic rules on the efficiency and stability of traffic flow, and
investigating novel ITS technologies such as adaptive cruise control,
inter-vehicle and vehicle-infrastructure communication
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