A Multi-threaded Execution Model for the Agent-Based SEMSim Traffic Simulation

Abstract. An efficient simulation execution engine is crucial for agent-based traffic simulation. Depending on the size of the simulation sce-nario the execution engine would have to update several thousand agents during a single time step. This update may also include route calcula-tions which are computationally expensive. The ability to dynamically re-calculate the route of agents is a feature often not required in classical microscopic traffic simulations. However, for the agent-based traffic sim-ulation which is part of the Scalable Electro-Mobility Simulation (SEM-Sim) platform, the routing ability of agents is an important feature. In this paper, we describe a multi-threaded simulation engine that explic-itly supports routing capabilities for every agent. In addition, we analyse the efficiency and performance of our execution model in the context of a Singapore-based simulation scenario.

Memory effects in microscopic traffic models and wide scattering in flow-density data

By means of microscopic simulations we show that non-instantaneous adaptation of the driving behaviour to the traffic situation together with the conventional measurement method of flow-density data can explain the observed inverse-$\lambda$ shape and the wide scattering of flow-density data in ``synchronized'' congested traffic. We model a memory effect in the response of drivers to the traffic situation for a wide class of car-following models by introducing a new dynamical variable describing the adaptation of drivers to the surrounding traffic situation during the past few minutes (``subjective level of service'') and couple this internal state to parameters of the underlying model that are related to the driving style. % For illustration, we use the intelligent-driver model (IDM) as underlying model, characterize the level of service solely by the velocity and couple the internal variable to the IDM parameter ``netto time gap'', modelling an increase of the time gap in congested traffic (``frustration effect''), that is supported by single-vehicle data. % We simulate open systems with a bottleneck and obtain flow-density data by implementing ``virtual detectors''. Both the shape, relative size and apparent ``stochasticity'' of the region of the scattered data points agree nearly quantitatively with empirical data. Wide scattering is even observed for identical vehicles, although the proposed model is a time-continuous, deterministic, single-lane car-following model with a unique fundamental diagram.Comment: 8 pages, submitted to Physical Review

Congested Traffic States in Empirical Observations and Microscopic Simulations

We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. {\bf 82}, 4360 (1999)]. We simulate these situations with a novel continuous microscopic single-lane model, the ``intelligent driver model'' (IDM), using the empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has practically the same effect as an on-ramp.Comment: Now published in Phys. Rev. E. Minor changes suggested by a referee are incorporated; full bibliographic info added. For related work see http://www.mtreiber.de/ and http://www.helbing.org

Control of Spatial-Temporal Congested Traffic Patterns at Highway Bottlenecks

A microscopic theory of control of spatial-temporal congested traffic pattern at freeway bottlenecks is presented. Based on empirical spatial-temporal features of congested patterns at freeway bottlenecks which have recently been found, different control strategies for prevention or reducing of the patterns are simulated and compared. The studied control strategies include the on-ramp metering with feedback and automatic cruise control (ACC) vehicles. A recent microscopic traffic flow model within the author's three-phase traffic theory is used for validation of spatial-temporal congested pattern control.Comment: 19 pages, 7 figure

A behavioural car-following model for computer simulation

The ability to predict the response of a vehicle in a stream of traffic to the behaviour of its predecessor is important in estimating what effect changes to the driving environment will have on traffic flow. Various proposed to explain this behaviour have different strengths and weaknesses. The paper constructs a new model for the response of the following vehicle based on the assumption that each driver sets limits to his desired braking and acceleration rates. The parameters in the model correspond directly to obvious characteristics of driver behaviour and the paper goes on to show that when realistic values are assigned to the parameters in a simulation, the model reproduces the characteristics of real traffic flow.

Simulation of pedestrian traffic in buildings

SIGLETIB Hannover: RA 1756(35) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman