The combined bottleneck effect is investigated by modeling traffic systems with an on-ramp and a nearby bus stop in a two-lane cellular automaton model.Two cases,i.e.the bus stop locates in the downstream section of the on-ramp and the bus stop locates in the upstream section of the on-ramp,are considered separately.The upstream flux and downstream flux of the main road,as well as the on-ramp flux are analysed in detail,with respect to the entering probabilities and the distance between the on-ramp and the bus stop.It is found that the combination of the two bottlenecks causes the capacity to drop off,because the vehicles entering the main road from the on-ramp would interweave with the stopping (pulling-out) buses in the downstream (upstream) case.The traffic conflict in the former case is much heavier than that in the latter,causing the downstream main road to be utilized inefficiently.This suggests that the bus stop should be set in the upstream section of the on-ramp to enhance the capacity.The fluxes both on the main road and on the on-ramp vary with the distance between the two bottlenecks in both cases.However,the effects of distance disappear gradually at large distances.These findings might give some guidance to traffic optimization and management.
This paper studies the effect of adaptive cruise control (ACC) system on traffic flow by using simulations. The multiple headway and velocity difference (MHVD) model is used to depict the motion of ACC vehicles, and the simulation results are compared with the optimal velocity (OV) model which is used to depict the motion of manual vehicles. Compared the cases between the manual and the ACC vehicle flow, the fundamental diagram can be classified into four regions: I, II, III, IV. In low and high density the flux of the two models is the same; in region II the free flow region of the MHVD model is enlarged, and the flux of the MHVD model is larger than that of the OV model; in region III serious jams occur in the OV model while the ACC system suppresses the jams in the MHVD model and the traffic flow is in order, but the flux of the OV model is larger than that of the MHVD model. Similar phenomena also appeared in mixed traffic flow which consists of manual and ACC vehicles. The results indicate that ACC vehicles have significant effect on traffic flow. The improvement induced by ACC vehicles decreases with the increasing proportion of ACC vehicles.
This paper uses the cellular automaton model to study the dynamics of traffic flow around an on-ramp with an acceleration lane.It adopts a parameter,which can reflect different lane-changing behaviour,to represent the diversity of driving behaviour.The refined cellular automaton model is used to describe the lower acceleration rate of a vehicle.The phase diagram and the capacity of the on-ramp system are investigated.The simulation results show that in the single cell model,the capacity of the on-ramp system will stay at the highest flow of a one lane system when the driver is moderate and careful;it will be reduced when the driver is aggressive.In the refined cellular automaton model,the capacity is always reduced even when the driver is careful.It proposes that the capacity drop of the on-ramp system is caused by aggressive lane-changing behaviour and lower acceleration rate.
This paper modifies the weighted probabilistic cellular automaton model (Li X L,Kuang H,Song T,et al 2008 Chin.Phys.B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits.In the new model,the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account.The fundamental diagram,spatial-temporal diagram,and the time series of one-minute data are analyzed.The results show that this model reproduces synchronized flow.Finally,it simulates the on-ramp system with the proposed model.Some characteristics including the phase diagram are studied.
In this article,we investigate cascading failures in complex networks by introducing a feedback.To characterize the effect of the feedback,we define a procedure that involves a self-organization of trip distribution during the process of cascading failures.For this purpose,user equilibrium with variable demand is used as an alternative way to determine the traffic flow pattern throughout the network.Under the attack,cost function dynamics are introduced to discuss edge overload in complex networks,where each edge is assigned a finite capacity (controlled by parameter α).We find that scale-free networks without considering the effect of the feedback are expected to be very sensitive to α as compared with random networks,while this situation is largely improved after introducing the feedback.
The effect of cars with intelligent transportation systems(ITSs) on traffic flow near an on-ramp is investigated by car-following simulations.By numerical simulations,the dependences of flux on the inflow rate are investigated for various proportions of cars with ITSs.The phase diagrams as well as the spatiotemporal diagrams are presented to show different traffic flow states on the main road and the on-ramp.The results show that the saturated flux on the main road increases and the free flow region is enlarged with the increase of the proportion of cars with ITS.Interestingly,the congested regions of the main road disappear completely when the proportion is larger than a critical value.Further investigation shows that the capacity of the on-ramp system can be promoted by 13%by using the ITS information, and the saturated flux on the on-ramp can be kept at an appropriate value by adjusting the proportion of cars with ITS.
Considering the effect of multiple flux difference,an extended lattice model is proposed to improve the stability of traffic flow.The stability condition of the new model is obtained by using linear stability theory.The theoretical analysis result shows that considering the flux difference effect ahead can stabilize traffic flow.The nonlinear analysis is also conducted by using a reductive perturbation method.The modified KdV (mKdV) equation near the critical point is derived and the kink-antikink solution is obtained from the mKdV equation.Numerical simulation results show that the multiple flux difference effect can suppress the traffic jam considerably,which is in line with the analytical result.
