32,504 research outputs found
Hybrid deterministic stochastic systems with microscopic look-ahead dynamics
We study the impact of stochastic mechanisms on a coupled hybrid system consisting of a general advection-diffusion-reaction partial differential equation and a spatially distributed stochastic lattice noise model. The stochastic dynamics include both spin-flip and spin-exchange type interparticle interactions. Furthermore, we consider a new, asymmetric, single exclusion pro- cess, studied elsewhere in the context of traffic flow modeling, with an one-sided interaction potential which imposes advective trends on the stochastic dynamics. This look-ahead stochastic mechanism is responsible for rich nonlinear behavior in solutions. Our approach relies heavily on first deriving approximate differential mesoscopic equations. These approximations become exact either in the long range, Kac interaction partial differential equation case, or, given sufficient time separation con- ditions, between the partial differential equation and the stochastic model giving rise to a stochastic averaging partial differential equation. Although these approximations can in some cases be crude, they can still give a first indication, via linearized stability analysis, of the interesting regimes for the stochastic model. Motivated by this linearized stability analysis we choose particular regimes where interacting nonlinear stochastic waves are responsible for phenomena such as random switching, convective instability, and metastability, all driven by stochasticity. Numerical kinetic Monte Carlo simulations of the coarse grained hybrid system are implemented to assist in producing solutions and understanding their behavior
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
Agreeing to Cross: How Drivers and Pedestrians Communicate
The contribution of this paper is twofold. The first is a novel dataset for
studying behaviors of traffic participants while crossing. Our dataset contains
more than 650 samples of pedestrian behaviors in various street configurations
and weather conditions. These examples were selected from approx. 240 hours of
driving in the city, suburban and urban roads. The second contribution is an
analysis of our data from the point of view of joint attention. We identify
what types of non-verbal communication cues road users use at the point of
crossing, their responses, and under what circumstances the crossing event
takes place. It was found that in more than 90% of the cases pedestrians gaze
at the approaching cars prior to crossing in non-signalized crosswalks. The
crossing action, however, depends on additional factors such as time to
collision (TTC), explicit driver's reaction or structure of the crosswalk.Comment: 6 pages, 6 figure
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