Effect of signals on two-route traffic system with real-time information

We study the effect of signals on the vehicular traffic in the two-route system at the tour-time feedback strategy where the vehicles move ahead through a series of signals. The Nagel–Schreckenberg model is applied to the vehicular motion. The traffic signals are controlled by both cycle time and split. The tour times on two routes fluctuate periodically and alternately. The period increases with decreasing the split. Also, the tour time on each route varies with time by synchronizing with the density. The dependences of tour times and densities on both split and cycle time are clarified.     

Traffic states and fundamental diagram in cellular automaton model of vehicular traffic controlled by signals

We present a cellular automaton (CA) model for vehicular traffic controlled by traffic lights. The CA model is not described by a set of rules, but is given by a simple difference equation. The vehicular motion varies highly with both signals’ characteristics and vehicular density. The dependence of tour time on both cycle time and vehicular density is clarified. In the dilute limit of vehicles, the vehicular motion is compared with that by the nonlinear-map model. The fundamental diagrams are derived numerically. It is shown that the fundamental diagram depends highly on the signals’ characteristics. The traffic states are shown for various values of cycle time in the fundamental diagram. We also study the effect of a slow vehicle on the traffic flow.     

Vehicular motion in 2D city traffic network with signals controlled by phase shift

We study the dynamic behavior of vehicular traffic through the series of traffic lights controlled by phase shift in two-dimensional (2D) city traffic network. The nonlinear-map model is presented for the vehicular traffic. The city traffic network is made of one-way perpendicular streets arranged in a square lattice with traffic signals where vertical streets are oriented upwards and horizontal streets are oriented rightwards. There are two traffic lights for the movement to north or that to east at each crossing. The traffic lights are controlled by the cycle time, split, and phase shift. The vehicle moves through the series of signals on a path selected by the driver. The city traffic with a heterogeneous density distribution is also studied. The dependence of the arrival time on cycle time, split, phase shift, selected path, and density is clarified for 2D city traffic. It is shown that the vehicular traffic is efficiently controlled by the phase shift.     

Tour time in a two-route traffic system controlled by signals

We study the dynamic behavior of vehicular traffic in a two-route system with a series of signals (traffic lights) at low density where the number of signals on route A is different from that on route B. We investigate the dependence of the tour time on the route for some strategies of signal control. The nonlinear dynamic model of a two-route traffic system controlled by signals is presented by nonlinear maps. The vehicular traffic exhibits a very complex behavior, depending on the cycle time, the phase difference, and the irregularity. The dependence of the tour time on the route choice is clarified for the signal strategies.     

Vehicular motion in counter traffic flow through a series of signals controlled by a phase shift

We study the dynamical behavior of counter traffic flow through a sequence of signals (traffic lights) controlled by a phase shift. There are two lanes for the counter traffic flow: the first lane is for east-bound vehicles and the second lane is for west-bound vehicles. The green-wave strategy is studied in the counter traffic flow where the phase shift of signals in the second lane has opposite sign to that in the first lane. A nonlinear dynamic model of the vehicular motion is presented by nonlinear maps at a low density. There is a distinct difference between the traffic flow in the first lane and that in the second lane. The counter traffic flow exhibits very complex behavior on varying the cycle time, the phase difference, and the split. Also, the fundamental diagram is derived by the use of the cellular automaton (CA) model. The dependence of east-bound and west-bound vehicles on cycle time, phase difference, and density is clarified.     

高速车随机延迟逐步加速交通流元胞自动机模型

提出介于Nagel-Schreckenberg(NS)模型和Fukui-Ishibashi(FI)模型之间的一种新的一维交通流元胞自动机模型. 此模型采用NS模型中的车辆逐步加速方式,和FI模型中的仅最大速车可随机减速的车辆延迟方式.证明新模型的基本图,即车流渐近稳态的平均速度与道路上的车辆密度之间的函数关系与FI模型的完全相同.这也就是说,只允许最高速车辆可发生延迟的FI交通流模型,如果将其突然无限制加速方式(车辆可在一个时步内从零速加速到最高速限M或车头距离所允许的最大速度),改变为车辆的逐步有限加速 关键词： 交通流 元胞自动机模型 相变基本图 Nagel-Schreckenberg模型 Fukui-Ishibashi模型     

Vehicular motion on a selected path in a 2d traffic network controlled by signals

We study the dynamic behavior of vehicular traffic through a series of traffic lights on selected paths in a two-dimensional (2d) traffic network. The city traffic network is made of one-way perpendicular streets arranged in a square lattice with traffic signals where vertical streets are oriented upwards and horizontal streets are oriented rightwards. A vehicle moves through the series of signals on a path selected by the driver. The selected path is one of the straight, zigzag, and random paths in a 2d traffic network. The vehicular motion on a selected path is presented by the nonlinear-map model. Vehicular traffic exhibits very complex behavior with varying selected paths, cycle times, and vehicular density. The dependence of the arrival time on cycle time, selected path, and density is clarified for 2d city traffic.     

决定论性逐步加速交通流模型的渐近稳态行为

研究Nagel-Schreckenberg(NS)交通流元胞自动机模型在不考虑车辆随机延迟情况下的决定论性模型的基本图,即渐近稳态的车流平均速度作为车辆密度的函数关系．证明决定论性NS模型,在车流的自组织作用下,其渐近稳态的基本图,与决定论性Fukui-Ishibashi(FI)交通流模型的基本图完全相同．这个结果表明,若把FI交通流模型中的车辆突然加速方式（即车辆速度可以在仅仅一个时步内加速到其最高速限M或前方空距所允许的最大速度）,改变为车辆逐步加速方式（车辆速度在每一时步中最多仅能增加一个速度单位）,则车辆的自组织相互作用,并不会改变其车流的长时间渐近稳态行为． 关键词：     

Clustering and maximal flow in vehicular traffic through a sequence of traffic lights

We study the maximal current (maximum traffic capacity) of vehicular traffic through a sequence of traffic lights on a highway, where all signals turn on and off synchronously. The dynamical model of vehicular traffic controlled by signals is expressed in terms of a nonlinear map, where the excluded-volume effect is taken into account. The dynamical behaviors of vehicles are clarified by analyzing traffic patterns. The clustering of vehicles varies with the cycle time of signals. The maximum current is closely connected to vehicular clustering. Clustering of vehicles is controlled by varying both split and cycle time of signals. The dependence of the maximal current on both split and cycle time is derived.     

Traffic dispersion induced by noise in off-lattice model

We study the dispersion of vehicles induced by speed fluctuation on a single-lane highway under open boundary. We extend the cellular automaton model on one-dimensional lattice to the real-variable model on off-lattice (continuous-in space model) in order to take into account the fluctuation of vehicular speed. Vehicles extend over the highway when moving forward. The characteristics of traffic dispersion are derived. It is shown that vehicular traffic exhibits scaling property. When a vehicle accelerates for following the vehicle ahead, vehicles move forming a cluster without dispersion. The relationship between the width of vehicular cluster and acceleration rate is clarified.     

Effect of speed fluctuations on a green-light path in a 2d traffic network controlled by signals

When a vehicle moves through a series of green lights, avoiding red signals in a two-dimensional (2d) city traffic network, the vehicle describes a characteristic trajectory (green-light path) and the travel time has a minimal value. The green-light path depends on the cycle time, split, signal-control strategy, and fluctuations of vehicular speed. We clarify the effect of speed fluctuations on a green-light path in a 2d traffic network controlled by signals. Even if an extremely small quantity of speed fluctuation is added, the green-light path changes greatly. It is shown that the root-mean square (RMS) of the deviation from the mean path depends highly on the cycle time. Also, the dependence of the green-light path on the speed-fluctuation strength is shown under a constant value of cycle time.     

Effect of irregularity on vehicular traffic through a sequence of traffic lights

We present the stochastic nonlinear-map model of vehicular traffic controlled by irregular signals. The signal’s interval, the split of signal, and the offset time changes irregularly from signal to signal on a roadway. We study the effect of irregularity on dynamical behavior of vehicular traffic through a sequence of traffic lights. The vehicle exhibits the very complex behavior with varying cycle time. When the strength of irregularity is small, the arrival time does not change with irregularity for some values of cycle time, while it changes for other values of cycle time. The region in which the arrival time changes is expanding with increasing irregularity’s strength. The region map (phase diagram) is shown in the cycle time-irregularity’s strength space.     

Vehicular traffic flow through a series of signals with cycle time generated by a logistic map

We study the dynamical behavior of vehicular traffic through a series of traffic signals. The vehicular traffic is controlled with the use of the cycle time generated by a logistic map. Each signal changes periodically with a cycle time, and the cycle time varies from signal to signal. The nonlinear dynamic model of the vehicular motion is presented by a nonlinear map including the logistic map. The vehicular traffic exhibits very complex behavior on varying both the cycle time and the logistic-map parameter a$a$. For a>3$a>3$, the arrival time shows a linear dependence on the cycle time. Also, the dependence of vehicular motion on parameter a$a$ is clarified.     

Nonlinear-map model for split effect on vehicular traffic through periodic signals

We study the effects of both split and cycle time on dynamical behavior of vehicles moving through a sequence of traffic lights on a highway, where the traffic lights turn on and off periodically. The dynamical model of vehicular traffic controlled by signals is expressed in terms of a nonlinear map. The vehicle exhibits complex behavior with varying split and cycle time. The tour time between signals shows a self-similar behavior. When split s_p is lower than 0.5, vehicular traffic shows a similar behavior as that of s_p=0.5, while vehicular traffic of s_p  >0.5 is definitely different from that of _sp?0.5$s_p?0.5$. The algebraic expression among the tour time, cycle time, and split is derived.     

Regularization and control of irregular vehicular motion through a series of signals at disordered intervals

We study the control and regularization of irregular motion of a vehicle moving through the series of traffic signals positioned at disordered intervals. All signals are controlled by both cycle time and phase shift. The nonlinear dynamic model of the vehicular motion controlled by signals is described in terms of the stochastic nonlinear map. The vehicle exhibits a very complex behavior with varying both cycle time and strength of disordered intervals. The delay or advance of tour time is compensated by synchronizing the phase shift with disordered intervals. The irregular motion induced by the disordered configuration of signals is regularized for various values of cycle time.     

双车道多速车辆混合交通流元胞自动机模型的研究

把NaSch模型的刹车概率分开为独立的加速和减速概率，引入转道规则，建立了双车道多速车辆的混合交通流模型.通过计算机数值模拟，得出了不同参数下混合交通的速度和流量与 密度关系的基本图.结果表明，转道概率、混合比例和加减速概率对混合交通都有重要的影 响，慢车的特性对混合交通起着决定性的作用. 关键词： 元胞自动机 混合交通流 NaSch模型     

Randomness control of vehicular motion through a sequence of traffic signals at irregular intervals

We study the regularization of irregular motion of a vehicle moving through the sequence of traffic signals with a disordered configuration. Each traffic signal is controlled by both cycle time and phase shift. The cycle time is the same for all signals, while the phase shift varies from signal to signal by synchronizing with intervals between a signal and the next signal. The nonlinear dynamic model of the vehicular motion is presented by the stochastic nonlinear map. The vehicle exhibits the very complex behavior with varying both cycle time and strength of irregular intervals. The irregular motion induced by the disordered configuration is regularized by adjusting the phase shift within the regularization regions.     

Influences of overtaking on two-lane traffic with signals

Based on the cellular automata method (CA method), two-lane traffic flow with the consideration of overtaking is investigated. Discrete equations are proposed to describe the traffic dynamics by using the rules of CA model. Influences of signal cycle time (t_s) and vehicular density (ρ) on the mean velocity 〈v〉 and mean overtaking times 〈c〉 of the traffic flow are discussed. The effects of slow vehicles and road barricades on the traffic flow are also studied. Simulation results shows that the vehicular density and the signal cycle time have significant influences on the traffic flow. The mean velocity of the traffic flow could keep a comparatively large value when ρ≤0.45. For a certain value of ρ, 〈v〉 displays a serrated fluctuation with t_s. Therefore, there may exist a certain combination of ρ and t_s which optimizes the traffic flow efficiency. As compared with the results in Nagatani (2009) [7], the model proposed here and the simulation results which took into account the effects of signal cycle time, slow vehicles, and road barricades on the traffic flow with overtaking allowed, can reflect the situation of traffic flow in a more realistic way.     

Fundamental diagram in traffic flow of mixed vehicles on multi-lane highway

We study the fundamental diagram for traffic flow of vehicular mixture on a multi-lane highway. We present the car-following model of multi-lane traffic in which slow and fast vehicles flow with changing lanes. We investigate the traffic states of the vehicular mixture under the periodic boundary. Two values of the current appear at a density and two current curves are obtained. Vehicles move with changing lanes in the traffic state of high current, while vehicles move without changing lanes in the traffic state of low current. They depend on the density, the fraction of slow vehicles, and the initial condition. In the high-current curve, the jamming transition between the free flow and the jammed state occurs at a low density. The fundamental diagrams (current-density diagrams) are shown for the single-lane, two-lane, three-lane, and four-lane traffics.     

Green-wave control of an unbalanced two-route traffic system with signals

We introduce the preference parameter into the two-route dynamic model proposed by Wahle et al. The parameter represents the driver’s preference for the route choice. When the driver prefers a route, the traffic flow on route A does not balance with that on route B. We study the signal control for the unbalanced two-route traffic flow at the tour-time feedback strategy where the vehicles move ahead through a series of signals. The traffic signals are controlled by both cycle time and phase shift (offset time). We find that the mean tour time can be balanced by selecting the offset time successfully. We derive the relationship between the mean tour time and offset time (phase shift). Also, the dependences of the mean density and mean current on the offset time are derived.