Using microsimulation feedback for trip adaptation for realistic traffic in Dallas

This paper presents a day-to-day re-routing relaxation approach for traffic simulations. Starting from an initial planset for the routes, the route-based microsimulation is executed. The result of the microsimulation is fed into a re-router, which re-routes a certain percentage of all trips. This approach makes the traffic patterns in the microsimulation much more reasonable. Further, it is shown that the method described in this paper can lead to strong oscillations in the solutions.Comment: Accepted by International Journal of Modern Physics C. Complete postscript version including figures in http://www-transims.tsasa.lanl.gov/research_team/papers

The dynamics of iterated transportation simulations

Iterating between a router and a traffic micro-simulation is an increasibly accepted method for doing traffic assignment. This paper, after pointing out that the analytical theory of simulation-based assignment to-date is insufficient for some practical cases, presents results of simulation studies from a real world study. Specifically, we look into the issues of uniqueness, variability, and robustness and validation. Regarding uniqueness, despite some cautionary notes from a theoretical point of view, we find no indication of ``meta-stable'' states for the iterations. Variability however is considerable. By variability we mean the variation of the simulation of a given plan set by just changing the random seed. We show then results from three different micro-simulations under the same iteration scenario in order to test for the robustness of the results under different implementations. We find the results encouraging, also when comparing to reality and with a traditional assignment result. Keywords: dynamic traffic assignment (DTA); traffic micro-simulation; TRANSIMS; large-scale simulations; urban planningComment: 24 pages, 7 figure

MATSim-T : Architecture and Simulation Times

Micro-simulations for transport planning are becoming increasingly important in traffic simulation, traffic analysis, and traffic forecasting. In the last decades the shift from using typically aggregated data to more detailed, individual based, complex data (e.g. GPS tracking) andthe continuously growing computer performance on fixed price level leads to the possibility of using microscopic models for large scale planning regions. This chapter presents such a micro-simulation. The work is part of the research project MATSim (Multi Agent Transport Simulation, http://matsim.org). In the chapter here the focus lies on design and implementation issues as well as on computational performance of different parts of the system. Based on a study of Swiss daily traffic – ca. 2.3 million individuals using motorized individual transport producing about 7.1 million trips, assigned to a Swiss network model with about 60,000 links, simulated and optimized completely time-dynamic for a complete workday – it is shown that the system is able to generate those traffic patterns in about 36 hours computation time

Evolutionary Computation Applied to Urban Traffic Optimization

At the present time, many sings seem to indicate that we live a global energy and environmental crisis. The scientific community argues that the global warming process is, at least in some degree, a consequence of modern societies unsustainable development. A key area in that situation is the citizens mobility. World economies seem to require fast and efficient transportation infrastructures for a significant fraction of the population. The non-stopping overload process that traffic networks are suffering calls for new solutions. In the vast majority of cases it is not viable to extend that infrastructures due to costs, lack of available space, and environmental impacts. Thus, traffic departments all around the world are very interested in optimizing the existing infrastructures to obtain the very best service they can provide. In the last decade many initiatives have been developed to give the traffic network new management facilities for its better exploitation. They are grouped in the so called Intelligent Transportation Systems. Examples of these approaches are the Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS). Most of them provide drivers or traffic engineers the current traffic real/simulated situation or traffic forecasts. They may even suggest actions to improve the traffic flow. To do so, researchers have done a lot of work improving traffic simulations, specially through the development of accurate microscopic simulators. In the last decades the application of that family of simulators was restricted to small test cases due to its high computing requirements. Currently, the availability of cheap faster computers has changed this situation. Some famous microsimulators are MITSIM(Yang, Q., 1997), INTEGRATION (Rakha, H., et al., 1998), AIMSUN2 (Barcelo, J., et al., 1996), TRANSIMS (Nagel, K. & Barrett, C., 1997), etc. They will be briefly explained in the following section. Although traffic research is mainly targeted at obtaining accurate simulations there are few groups focused at the optimization or improvement of traffic in an automatic manner â not dependent on traffic engineers experience and âartâ. O pe n A cc es s D at ab as e w w w .ite ch on lin e. co

予期せぬブレーキおよび車線変更における車両間スペースを考慮したセルラーオートマトンに基づく交通流シミュレーション

博士(工学)佐賀大

Internet Data Transport - From the Perspective of Discrete Mass Transport Modeling

In recent years a new class of one-dimensional cellular automata (CA) models has attracted much attention. These so-called mass transport models can be characterized as nonequilibrium stochastic processes. In the presented thesis a new model of this class, the Asymmetric Multi Occupation Process (AMOP) is considered. This CA model was first introduced with open boundary conditions to simulate Internet data transport. It is defined on a one-dimensional lattice equipped with buffers of finite size that can be occupied by at most B particles. The local dynamics are implemented by the totally asymmetric shift of discrete mass variables respectively particles under consideration of hard-core repulsion and parallel dynamics. In the first part of this work the AMOP with periodic boundary conditions is investigated by means of numerical as well as analytical considerations. Regarding deterministic model dynamics the influence of finite buffer and system sizes onto the fundamental diagram (FD), i.e., flow-density relation is analyzed. Furthermore, for stochastic movement the FDs obtained by numerical simulations are compared with analytical results derived by Mean-Field (MF) approaches and a 2-cluster approximation. In the second part the AMOP with open boundary conditions is investigated in the context of boundary induced phase transitions. In case of deterministic bulk dynamics an analytical exact representation of the system inflow as well as the outflow is presented in dependence of the buffer size. As a result the deterministic phase diagram derived by numerical simulations could be verified by analytical considerations. Regarding stochastic particle movement the phase diagram is obtained by Monte Carlo simulations. In both cases it is shown that the jammed phase is strongly enlarged for increasing buffer sizes. Finally, in the third part of this thesis the influence of interacting boundaries on the model dynamics is analyzed. Therefore, a new fall back inflow strategy is introduced in order to stabilize high flow states and thus prevent the system from a complete jamming. Precisely, the inflow is determined by the state of the last site of the system. As a result the phase diagrams of the deterministic and the stochastic model obtained by means of numerical simulations are presented. Two new phases could be identified a free-flow as well as a jammed phase both characterized by a striped microscopic pattern. Especially in the arising striped jammed regime system flow and mean velocity are drastically enlarged compared to generic inflow strategies. Here, the fall back strategy is capable to prevent the system from a complete jamming. Thus, the introduced inflow procedure represents an effective strategy for establishing reliable connections

Development of a simulation and evaluation environment for a traffic flow analysis system.

A system for analysis of the traffic flow on public streets and highways through the use of Floating Car Data (FCD) relies completely on the number of simultaneously contributing vehicles, a fact that is no barrier for the phases of conception and development but poses a serious issue for the testing of such a system. Especially for smaller institutions or companies where the ability and resources to field the required number of participants is not given which in turn leads to the need for computational support to substitute the use of real vehicles by simulation. This thesis focuses on the task of the design and development of a simulation and evaluation environment for a pre-developed Traffic Flow Analysis System. The objective of this environment is to simulate the behavior of real vehicles on the existing street network including their most relevant characteristics for the purpose of congestion recognition. It is shown how simulation methods can be effectively used to create such an environment while using mathematical methods to model the characteristics of the participating system parts (vehicles) as well as the environmental influence on the external communication components (GPS, Radio)

Simple queueing model applied to the city of Portland

The authors present a simple traffic micro-simulation model that models the effects of capacity cut-off, i.e. the effect of queue built-up when demand is exceeding capacity, and queue spillback, i.e. the effect that queues can spill back across intersections when a congested link is filled up. They derive the model`s fundamental diagrams and explain it. The simulation is used to simulate traffic on the emme/2 network of the Portland (Oregon) metropolitan region (20,000 links). Demand is generated by a simplified home-to-work assignment which generates about half a million trips for the AM peak. Route assignment is done by iterative feedback between micro-simulation and router. Relaxation of the route assignment for the above problem can be achieved within about half a day of computing time on a desktop workstation