Effect of adaptive cruise control systems on mixed traffic flow near an on-ramp

Mixed traffic flow consisting of vehicles equipped with adaptive cruise control (ACC) and manually driven vehicles is analyzed using car-following simulations. Simulations of merging from an on-ramp onto a freeway reported in the literature have not thus far demonstrated a substantial positive impact of ACC. In this paper cooperative merging for ACC vehicles is proposed to improve throughput and increase distance traveled in a fixed time. In such a system an ACC vehicle senses not only the preceding vehicle in the same lane but also the vehicle immediately in front in the other lane. Prior to reaching the merge region, the ACC vehicle adjusts its velocity to ensure that a safe gap for merging is obtained. If on-ramp demand is moderate, cooperative merging produces significant improvement in throughput (20%) and increases up to 3.6 km in distance traveled in 600 s for 50% ACC mixed flow relative to the flow of all-manual vehicles. For large demand, it is shown that autonomous merging with cooperation in the flow of all ACC vehicles leads to throughput limited only by the downstream capacity, which is determined by speed limit and headway time.     

Multiple jamming transitions in traffic flow

The effect of accelerating stepwise on the jamming transition is investigated in the extended car-following model. The optimal velocity function is modified to take into account accelerating stepwise vehicles. It is shown that the multiple phase transitions occur on varying the car density. The multiple transitions change with the delay time. The flow-density curves and the velocity-headway curves are presented for various delay times. It is also shown that the multiple jamming transition lines are consistent with the neutral stability curves. The jamming transitions are closely related with the turning points of the optimal velocity function.     

Modeling U-turn traffic flow

Median U-turns are sometimes installed to improve the traffic flow at busy intersections by eliminating left turns. Using a microscopic traffic model, we confirmed the presence of transitions from free flow to congested flow with increasing car inflow density. In addition, our proposed rules inside a U-turn curve, which accounted for safety issues and an asymmetric lane changing behavior (outer-to-inner vs. inner-to-outer lane transitions), predicted the speed distribution of cars after the U-turn curve. We found that U-turn curves installed for improving traffic flow at busy intersections produced their desired effects only when there is minimal interaction between cars.     

A new lattice model of traffic flow with the consideration of the traffic interruption probability

In this paper, we present a new lattice model which involves the effects of traffic interruption probability to describe the traffic flow on single lane freeways. The stability condition of the new model is obtained by the linear stability analysis and the modified Korteweg-de Vries (KdV) equation is derived through nonlinear analysis. Thus, the space will be divided into three regions: stable, metastable and unstable. The simulation results also show that the traffic interruption probability could stabilize traffic flow.     

Analysis of maximum traffic flow and its breakdown on congested freeways

This study analyzes the dynamic behavior of traffic flow over time by deriving the theoretical value of flow oscillations convergence () following the breakdown of traffic flow. Modeling traffic flow fluctuations over time reflects two basic zones: the increasing demand zone that terminates approximately when the maximum flow is attained, and the oscillations zone that reflects the fluctuations of flow until its stabilization. The models in the flow-time plane introduce a new concept of “stable maximum flow” particularly for design purposes. Both converged values and observed recovery flow values represent the end of the recovery phase transition where the traffic stream approaches the free flow regime through lower flow conditions than the maximum flow conditions. A comparison between breakdown starting times and times of the maximum flow shows that in most cases, when one breakdown period (OB) is experienced, breakdown starts 21–50 min after observing the maximum flow. Modeling changes in traffic flows in the flow-time plane is emphasized for OB or multiple breakdown period (MBP) cases. The analysis of frequent OB and infrequent MBP cases allow for better controlling of the traffic flow by maintaining its flow level below maximum.     

Effect of driver over-acceleration on traffic breakdown in three-phase cellular automaton traffic flow models

Based on simulations with cellular automaton (CA) traffic flow models, a generic physical feature of the three-phase models studied in the paper is disclosed. The generic feature is a discontinuous character of driver over-acceleration caused by a combination of two qualitatively different mechanisms of over-acceleration: (i) Over-acceleration through lane changing to a faster lane, (ii) over-acceleration occurring in car-following without lane changing. Based on this generic feature a new three-phase CA traffic flow model is developed. This CA model explains the set of the fundamental empirical features of traffic breakdown in real heterogeneous traffic flow consisting of passenger vehicles and trucks. The model simulates also quantitative traffic pattern characteristics as measured in real heterogeneous flow.     

Synchronized flow and phase separations in single-lane mixed traffic flow

In this paper, we have studied synchronized flow and phase separations in mixed (heterogeneous) single-lane highway traffic. It is found that the flux–density (occupancy) curve of heterogeneous flow, as expected, lies in between two flux–density (occupancy) curves of homogeneous flow R=0$R=0$ (all vehicles are slow vehicles) and R=1$R=1$ (all vehicles are fast vehicles). However, unexpectedly, the velocity–density (occupancy) curve of heterogeneous flow does not. We also found that cross-correlation function (CCF) analysis shows that heterogeneous flow has almost the same strong coupling as homogeneous flow. In other words, when traffic is in free flow or jams, the value of CCF is approximate to be 1.0, while the value is about 0.1 in synchronized flow.     

Continuum modeling of cooperative traffic flow dynamics

This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.     

Impact of the honk effect on the stability of traffic flow

In this paper, we propose an extended car-following model which takes into account the honk effect. The analytical and numerical results show that the honk effect improves the stability of traffic flow. The dependence of the stability on the properties of the honk effect is investigated in this paper.     

Cellular automaton model for traffic flow based on safe driving policies and human reactions

This paper proposes a new single-lane cellular automaton model for traffic flow. The model takes into account normal drivers’ spacing policies and transportation engineering practices to guarantee that microscopic vehicle behavior is more in line with vehicular movement in the real world. As a result, drivers’ reactions are based on a safety analysis that determines the most appropriate action for a vehicle to take. Hence, the model introduces a new set of simple rules to change the speed of vehicles that incorporates three important thresholds required by the follower vehicle to accelerate, slow down or maintain its speed. Thus, the space gap, relative speed and limited acceleration/deceleration capabilities are introduced into simulations. Simulation results obtained from a system with periodic conditions show that the model can smooth the speed drop when vehicles approach the upstream front of the traffic jam. Therefore, the model avoids unrealistic deceleration behavior found in most previous cellular automata models. Besides, the model is also capable of reproducing most empirical findings including the three states of traffic flow, the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Moreover, the new model preserves the computational simplicity of the cellular automata models.     

A macro traffic flow model accounting for road capacity and reliability analysis

Based on existing traffic flow models, in this paper we develop a macro traffic flow model taking into consideration road capacity to study the impact of the road capacity on traffic flow. The numerical results show that the road capacity destroys the stability of uniform flow and produces stop-and-go traffic under a moderate density and that the road capacity enhances the traffic risk coefficient and reduces the traffic system’s reliability. In addition, the numerical results show that properly improving the road condition can enhance the road capacity, reduce the traffic risk coefficient and enhance the traffic system’s reliability.     

Simulating synchronized traffic flow and wide moving jam based on the brake light rule

A new cellular automaton (CA) model based on brake light rules is proposed, which considers the influence of deterministic deceleration on randomization probability and deceleration extent. To describe the synchronized flow phase of Kerner’s three-phase theory in accordance with empirical data, we have changed some rules of vehicle motion with the aim to improve speed and acceleration vehicle behavior in synchronized flow simulated with earlier cellular automaton models with brake lights. The fundamental diagrams and spatial–temporal diagrams are analyzed, as well as the complexity of the traffic evolution, the emergence process of wide moving jam. Simulation results show that our new model can reproduce the three traffic phases: free flow, synchronized flow and wide moving jam. In addition, our new model can well describe the complexity of traffic evolution: (1) with initial homogeneous distribution and large densities, the traffic will evolve into multiple steady states, in which the numbers of wide moving jams are not invariable. (2) With initial homogeneous distribution and the middle range of density, the wide moving jam will emerge stochastically. (3) With initial mega-jam distribution and the density close to a point with the low value, the initial mega-jam will disappear stochastically. (4) For the cases with multiple wide moving jams, the process is analyzed involving the generation of narrow moving jam due to “pinch effect”, which leads to wide moving jam emergence.     

Effect of looking backward on traffic flow in an extended multiple car-following model

In this paper, a new car-following model is proposed by incorporating the backward looking effect under certain conditions and multiple information of preceding cars in traffic flow. And the neutral stability condition of this model can be obtained by using the linear stability theory. Numerical simulation shows that the proposed model is theoretically an improvement over previous ones.     

Freezing transition in a four-directional traffic model for facing and crossing pedestrian flow

We study the traffic behavior in the facing and crossing traffic of pedestrians numerically and analytically. There are four kinds of walkers, those moving to east, to west, to north, and to south. We present the mean-field approximation (MFA) model for the four-directional traffic. The model is described in terms of four nonlinear difference equations. The excluded-volume effect and directionality are taken into account. The fundamental diagrams (current-density diagrams) are derived. When pedestrian density is higher than a critical value, the dynamical phase transition occurs from the free flow to the frozen (stopping) state. The critical density is derived by using the linear stability analysis. The velocity and current (flow) at the steady state are derived analytically. The analytical result is consistent with that obtained by the numerical simulation.     

An extended macro model for traffic flow with consideration of multi static bottlenecks

In this paper, we propose a macro model with consideration of multi static bottlenecks to study the impacts of multi static bottlenecks on traffic flow. The numerical results show that the influences are related to the number of static bottlenecks, the distance between two adjacent static bottlenecks and the initial density.     

A new lattice model of traffic flow with the anticipation effect of potential lane changing

A new lattice model of traffic flow is presented by taking into account the anticipation of potential lane changing on front site on single lane. The stability condition of the extended model is obtained by using the linear stability theory. The modified KdV equation near the critical point is constructed and solved through nonlinear analysis. And the phase space of traffic flow in the density-sensitivity space could be divided into three regions: stable, metastable and unstable ones, respectively. Numerical simulation also shows that the consideration of lane changing probability in lattice model can stabilize traffic flow, which implies that the new consideration has an important effect on traffic flow in lattice models.     

A two-dimensional CA model for traffic flow with car origin and destination

Dynamic phase transitions in a two-dimensional traffic flow model defined on a decorated square-lattice are studied numerically. The square-lattice point and the decorated site denote intersections and roads, respectively. In the present model, a car has a finite deterministic path between the origin and the destination, which is assigned to the car from the beginning. In this new model, we found a new phase between the free-flow phase and the frozen-jam phase that is absent from previous models. The new model is characterized by the persistence of a macroscopic cluster. Furthermore, the behavior in this macroscopic cluster phase is classified into three regions characterized by the shape of the cluster. The boundary of the three regions is phenomenologically estimated. When the trip length is short and the car density is high, both ends of the belt-like cluster connect to each other through the periodic boundary with some probability. This type of cluster is classified topologically as a string on a two-dimensional torus.