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发表于 2005-11-23 01:44:11
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交通流文献(看参考目录和摘要,货真价实)
参考:文献目录及摘要
1.Macroscopic traffic models from microscopic car-following models
abstract:We present a method to derive macroscopic fluid-dynamic models from microscopic car-following models via a coarse-graining procedure. The method is first demonstrated for the optimal velocity model. The derived macroscopic model consists of a conservation equation and a momentum equation, and the latter contains a relaxation term, an anticipation term, and a diffusion term. Properties of the resulting macroscopic model are compared with those of the optimal velocity model through numerical simulations, and reasonable agreement
is found although there are deviations in the quantitative level. The derivation is also extended to general car-following models.
2.Memory effects in microscopic traffic models and wide scattering in flow-density data
abstract: By means of microscopic simulations we show that noninstantaneous adaptation of the driving behavior to the traffic situation together with the conventional method to measure flow-density data provides a possible
explanation for the observed inverse-l 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 an additional dynamical variable the ';subjective level of service';! describing the adaptation of drivers to the surrounding traffic situation during the past few minutes 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 the underlying model, characterize the level of service solely by the
velocity, and couple the internal variable to the IDM parameter ';time gap'; to model an increase of the time gap in congested traffic ';frustration effect';... ...
3.Micro- and Macro-Simulation of Freeway Traffic (推荐)
abstract:We present simulations of congested traffic in circular and open systems with a non-local, gas-kinetic-based traffic model and a novel car-following model. The model parameters are all intuitive and can be easily calibrated. Micro- and macro-simulations with these models for identical
vehicles on a single lane produce the same traffic states, which also qualitatively agree with empirical traffic observations. Moreover, the phase diagrams of traffic states in the presence of bottlenecks for the microscopic car-following model and the macroscopic gas-kinetic-based model almost agree. In
both cases, we found metastable regimes, spatially coexistent states, and a small region of tristability. The distinction of different types of vehicles (cars and long vehicles) yields additional insight and allows us to reproduce empirical data even more realistically, including the observed fluctuation
properties of traffic flows like the wide scattering of congested traffic data.
Finally, as an alternative to the gas-kinetic approach, we propose a new scheme for deriving non-local macroscopic traffic models from given microscopic car-following models. Assuming identical (macroscopic) initial and boundary conditions, we show that there are microscopic models for which the corresponding macroscopic version displays an almost identical dynamics. This enables us to combine micro- and macro-simulations of road sections by simple algorithms, and even to simulate them simultaneously.
4.Mixed manual/semi-automated traffic:a macroscopic analysis
abstract:The use of advanced technologies and intelligence in vehicles and infrastructure could make the current highway transportation system much more efficient. Semi-automated vehicles with the capability of automatically
following a vehicle in front as long as it is in the same lane and in the vicinity of the forward looking ranging sensor are expected to be deployed in the near future. Their penetration into the current manual traffic will give rise to mixed manual/semi-automated traffic. In this paper, we analyze the fundamental flow–density curve for mixed traffic using flow–density curves for 100% manual and 100% semiautomated traffic. Assuming that semi-automated vehicles use a time headway smaller than today';s manual traffic average due to the use of sensors and actuators, we have shown using the flow–density diagram that the traffic flow rate will increase in mixed traffic. ......
5.Modeling Traffic Flow at an Urban Unsignalized Intersection
abstract:This paper proposes a new way to study traffic flow at an urban
unsignalised intersection, through detailed space considerations, using cellular
automata (CA). Heterogeneity and inconsistency are simulated by incorporation
of different categories of driver behaviour and reassignment of categories with
given probabilities at each time step. The method is able to reproduce many
features of urban traffic, for which gap-acceptance models are less appropriate.
Capacities of the minor-stream in a TWSC intersection are found to depend on
flow rates of major-streams, also changes with flow rate ratio (FRR= flow rate
of near lane: flow rate of far lane). Hence flow rates corresponding to each
stream must be distinguished. The relationship between the performance of
intersections and other traffic flow parameters is also considered. Vehicle
movements in this paper relate to left-side driving, such as found in UK/Ireland. However, rules are generally applicable.
6.Multi-anticipative car-following model
abstract:The microscopic car-following model by Bando et al. [1{4] is extended by incorporating multivehicle interactions. It is shown that the reaction to more than one vehicle ahead leads to a stabilization of the dynamical behavior, i.e. the stable region increases. Still the fundamental macroscopic properties of traffic, free flow and congested flow, are described. More important, due to the multi-anticipative driving behavior driving in narrow platoons is forced such that a third fundamental property of traffic flow, the so-called synchronized flow, is modeled as well.
7.Multibunch solutions of the differential-difference equation for traffic flow
abstract:The Newell-Whitham type of car-following model, with a hyperbolic tangent as the optimal velocity function,has a finite number of exact steady traveling wave solutions that can be expressed in terms of elliptic theta
functions. Each such solution describes a density wave with a definite number of car bunches on a circuit. In our numerical simulations, we observe a transition process from uniform flow to congested flow described by a one-bunch analytic solution, which appears to be an attractor of the system. In this process, the system exhibits a series of transitions through which it comes to assume configurations closely approximating multibunch solutions with successively fewer bunches.
8.Optimization of congested traffic by controlling stop-and-go waves
abstract: We propose a new optimization strategy based on inducing stop-and-go waves on the main road and controlling their wavelength. Using numerical simulations of a recent stochastic car-following model we show that this strategy yields optimization of traffic flow when implemented in systems with a localized periodic inhomogeneity, such as signalized intersections and entry ramps. The optimization process is explained by our finding of a generalized fundamental diagram (GFD) for traffic, namely a flux-density-wavelength relation. Projecting the GFD on the density-flux plane yields a two-dimensional region of stable states, qualitatively similar to that found empirically in synchronized traffic.
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