Predicting travel time to limit congestion at a highway bottleneck

A new method is proposed to predict the travel time on a highway route with a bottleneck caused by an on-ramp. The method takes advantage of the slow variation of the bottleneck throughput when congestion exists. The predicted travel time for a vehicle leaving the origin is given by the current number of vehicles on the route divided by the estimated throughput. The latter is an average of N/T recorded as each vehicle reaches the destination where N is the number of vehicles at the start of the trip and T is the time to complete the trip. Drivers divert to an off-ramp when the predicted travel time exceeds a target value. The target could be historical average travel times of alternative routes or chosen to limit the amount of congestion. Simulations employing three-phase traffic theory show that the travel time converges to the target value and remains close to or below it with the proposed prediction strategy. Strong oscillations in travel time obtained when other strategies are used for diversion do not develop with the new method because the inherent delay is effectively removed.     

Influence of inter-vehicle communication on peak hour traffic flow

Mixed traffic flow consisting of vehicles equipped with wireless inter-vehicle communication devices and non-equipped vehicles is analyzed using bidirectionally coupled network traffic and road traffic simulators in a peak hour scenario. For equipped vehicles a strategy to stabilize traffic flow and to reduce travel time is proposed. The strategy comprises rules to determine both how and when to change driving behavior. Vehicles that detect perturbations downstream try to keep a larger gap to their predecessor by which they aim to compensate traffic inhomogeneities. Improvement of traffic flow was observed even for a ratio of equipped vehicles as low as five percent.     

Mitigation of congestion at a traffic bottleneck with diversion and lane restrictions

Mitigation of congestion on a two-lane highway with an off-ramp and an on-ramp is simulated with three-phase traffic theory. Advanced travel information-the average velocity of vehicles near the bottleneck at an on-ramp-is used to divert vehicles at an upstream off-ramp. If enough vehicles divert, previously expanding synchronous flow congestion can be stalled and isolated to the region between the ramps. The introduction of lane restrictions (forbidding lane changing on the portion of highway between the ramps) in addition to diversion substantially reduces and essentially eliminates the congestion, restoring flow to nearly free-flow conditions.     

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.     

Driver choice compared to controlled diversion for a freeway double on-ramp in the framework of three-phase traffic theory

Two diversion schemes that apportion demand between two on-ramps to reduce congestion and improve throughput on a freeway are analyzed. In the first scheme, drivers choose to merge or to divert to a downstream on-ramp based on information about average travel times for the two routes: (1) merge and travel on the freeway or (2) divert and travel on a surface street with merging downstream. The flow, rate of merging at the ramps, and the travel times oscillate strongly, but irregularly, due to delayed feedback. In the second scheme, diversion is controlled by the average mainline velocities just upstream of the on-ramps. Driver choice is not involved. If the average upstream velocity on the mainline drops below a predetermined value (20 m/s) vehicles are diverted to the downstream ramp. When the average mainline velocity downstream becomes too low, diversion is no longer permitted. The resultant oscillations in this scheme are nearly periodic. The period is dominated by the response time of the mainline to interruption of merging rather than delayed feedback, which contributes only a minor component linear in the distance separating the on-ramps. In general the second scheme produces more effective congestion reduction and greater throughput. Also the travel times for on-ramp drivers are less than that obtained by drivers who attempt to minimize their own travel times (first scheme). The simulations are done using the Kerner-Klenov stochastic three-phase theory of traffic [B.S. Kerner, S.L. Klenov, Phys. Rev. E 68 (2003) 036130].     

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.     

混有协同自适应巡航控制车辆的异质交通流稳定性解析与基本图模型

针对传统车辆和协同自适应巡航控制(cooperative adaptive cruise control,CACC)车辆构成的异质交通流,研究其稳定性与基本图模型.应用实车测试验证的CACC模型和智能驾驶员模型(intelligent driver model)分别作为CACC车辆和传统车辆的跟驰模型,建立异质流稳定性解析框架,研究不同平衡态速度、不同CACC车辆比例时的异质流稳定性.推导异质流基本图模型,并进行数值仿真实验.研究结果表明,在传统车辆稳定的速度范围,异质流处于稳定状态.在传统车辆不稳定的速度范围,CACC车辆比例增加以及平衡态速度远离9.6—18.6 m/s速度范围,均能够改善异质流的不稳定性.通行能力随着CACC车辆比例的增加而提高.此外,CACC模型的期望车间时距越大,异质流稳定域越大,但通行能力降低.因此,恒定车间时距CACC控制策略下的期望车间时距取值应权衡异质流稳定域和通行能力两个方面的影响.     

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.     

Cellular automata model for traffic flow with safe driving conditions

In this paper, a recently introduced cellular automata （CA） model is used for a statistical analysis of the inner micro-scopic structure of synchronized traffic flow. The analysis focuses on the formation and dissolution of clusters or platoons of vehicles, as the mechanism that causes the presence of this synchronized traffic state with a high flow. This platoon formation is one of the most interesting phenomena observed in traffic flows and plays an important role both in manual and automated highway systems （AHS）. Simulation results, obtained from a single-lane system under periodic boundary conditions indicate that in the density region where the synchronized state is observed, most vehicles travel together in pla- toons with approximately the same speed and small spatial distances. The examination of velocity variations and individual vehicle gaps shows that the flow corresponding to the synchronized state is stable, safe and highly correlated. Moreover, results indicate that the observed platoon formation in real traffic is reproduced in simulations by the relation between vehicle headway and velocity that is embedded in the dynamics definition of the CA model.     

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.     

Jamming transition of a two-dimensional traffic dynamics with consideration of optimal current difference

A modified two-dimensional lattice hydrodynamic traffic flow model is proposed by incorporating the optimal current difference effect of leading vehicles. Phase transitions and critical phenomenon are investigated near the critical point both analytically and numerically. Based on the configuration of vehicles, it is shown that two distinct jamming transitions occur: conventional jamming transition to the kink jam and jamming transition to the chaotic jam. It is shown that consideration of optimal current difference effect stabilizes the traffic flow and suppresses the traffic jam efficiently for all possible configurations of vehicles on a square lattice.     

Phase coexistence induced by a defensive reaction in a cellular automaton traffic flow model

Traffic flow modeling is an elusive example for the emergence of complexity in dynamical systems of interacting objects. In this work, we introduce an extension of the Nagel-Schreckenberg (NaSch) model of vehicle traffic flow that takes into account a defensive driver’s reaction. Such a mechanism acts as an additional nearest-neighbor coupling. The defensive reaction dynamical rule consists in reducing the driver’s velocity in response to deceleration of the vehicle immediately in front of it whenever the distance is smaller than a security minimum. This new mechanism, when associated with the random deceleration rule due to fluctuations, considerably reduces the mean velocity by adjusting the distance between the vehicles. It also produces the emergence of bottlenecks along the road on which the velocity is much lower than the road mean velocity. Besides the two standard phases of the NaSch model corresponding to the free flow and jammed flow, the present model also exhibits an intermediate phase on which these two flow regimes coexist, as it indeed occurs in real traffics. These findings are consistent with empirical results as well as with the general three-phase traffic theory.     

Behaviours in a dynamical model of traffic assignment with elastic demand

This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.     

混入智能车的下匝道瓶颈路段交通流建模与仿真分析

以下匝道瓶颈路段为研究背景,以手动驾驶汽车和两类智能车为研究对象,包括自适应巡航(ACC)汽车和协同自适应巡航(CACC)汽车,建立了混入智能车的混合交通流模型.在车辆的纵向控制层面,分别构建了手动驾驶汽车改进舒适驾驶元胞自动机规则和智能车的跟驰模型;基于车辆下匝道行驶特性,引入车辆感知范围R、换道控制区域LLC、换道冒险因子λ等参数,建立了控制车辆横向运动的自由换道和强制换道模型.通过对混合交通流模型进行数值仿真发现,CACC车辆混入率PCACC、车辆感知范围R、换道区域长度LLC和换道冒险程度λ均对下匝道交通系统产生影响.当CACC车辆混入率低于0.5时,CACC退化为ACC的概率增大,系统稳定性下降,交通拥堵呈恶化趋势;当CACC车辆混入率大于0.5时,车辆运行速度显著提升,拥堵消散能力提高.增大车辆感知范围、加长换道区域长度、提高换道冒险程度,都能够有效缓解改善下匝道瓶颈路段主线的拥挤状况,而对匝道运行效率影响并不明显.     

Fluctuation and transition of vehicular traffic through a sequence of traffic lights

We study the dynamical behavior of N vehicles with no passing, but are moving through a sequence of traffic lights on a single-lane highway, where the traffic lights turn on and off periodically with the synchronized strategy. The dynamical model of N vehicles controlled by traffic lights is described in terms of coupled maps with three parameters. The motions of vehicles display a complex behavior, interacting with other vehicles through the sequence of traffic lights. Fluctuation of the leading vehicle is amplified to the following vehicles. The amplification of fluctuation changes with cycle time. The dynamical behavior of vehicles depends highly on their position of grouping vehicles. Signal traffic at a low density changes at specific values of cycle time. The complex dynamical transitions occur by varying three parameters.     

Multiclass first-order simulation model to explain non-linear traffic phenomena

With the first-order traffic model of Lighthill, Whitham and Richard (LWR), many simple traffic problems can be represented analytically such as a shock formation. However, the LWR model has some deficiencies. For example, among the other things, it fails to replicate interesting non-linear phenomena such as hysteresis and capacity drop as well as the dispersion of traffic platoon when there exists a distribution of desired speeds in heterogeneous traffic. To this end, in this paper, we propose a novel multiclass first-order simulation model based on an approximation of Riemann solver. In the developed model, each vehicle class is only characterized by their desired speeds in a free-flow traffic state where overtaking is allowed. However, when traffic is congested, all vehicle classes must travel at the same congested speed and overtaking is not possible. Numerical results show that the proposed model is not only more accurate and reliable than the existing models but also able to explain non-linear traffic phenomena on freeways.     

基于车载电子标签数据的单交叉口状态判别研究

基于目前交叉口状态判别存在设备安装复杂度高,判别准确率低,受环境影响大、无法识别具体车辆等问题,提出基于车载电子标签数据的交叉口状态判别方法。通过简化模型,以两相位单交叉口为例,选择的参数为流量,交通密度,停车数量。最后经VISSIM交通仿真软件的二次开发,模拟车载电子标签运行环境,通过对比仿真试验所得与专家观察分析所得,相似度高达90%以上。证明该方法在克服以往方法缺陷的基础上可有效判别交叉口状态。     

Congestion analysis of traffic networks with direction-dependant heterogeneity

Traffic flow directionality and network weight asymmetry are widespread notions in traffic networks. This paper investigates the influence of direction-dependant heterogeneity on traffic congestion. To capture the effect of the link directionality and link weight asymmetry, the heterogeneity indexes of complex networks and the traffic flow model are introduced. The numerical results show that the critical value of heterogeneity determines congestion transition processes. The congestion degree increases with heterogeneity when the network heterogeneity is at a subcritical region. A network is more tolerant of congestion if the heterogeneity of the network is smaller or larger than the critical value. Furthermore, when heterogeneity reaches the critical value, the average number of accumulated vehicles arrives at the maximum and the traffic flow is under a serious congestion state. A significant improvement on the tolerance to congestion of traffic networks can be made if the network heterogeneity is controlled within a reasonable range.     

Navier-Stokes-like equations applicable to adaptive cruise control traffic flows

Under the scenario in which, within a traffic flow, each vehicle is controlled by adaptive cruise control (ACC), and the macroscopic one-vehicle probability distribution function fits the Paveri-Fontana hypothesis, a set of reduced Paveri-Fontana equations considering the ACC effect is derived. With the set, by maximizing the specially defined informational entropy deviating from a certain reference homogeneous steady state, the Navier-Stokes-like equations considering ACC are introduced. For a homogeneous steady traffic flow in a single circular lane, when the steady velocity or density is perturbed along the lane, numerical simulations indicate that ACC-controlled vehicles require less time for re-equilibration than manually driven vehicles. The re-equilibrated steady densities for ACC and manually driven traffic flows are all close to the original values; the same is true for the re-equilibrated steady velocity for manually driven traffic flows. For ACC traffic flows, the re-equilibrated steady velocity may be higher or lower than the original value, depending upon a parameter ω (introduced to solve the distribution function of the reference steady state), and the headway time (introduced in ACC models). Also, the simulations indicate that only an appropriate parameter set can ensure the performance of ACC; otherwise, ACC may result in low traffic running efficiency, although traffic flow stability becomes better.     

Biham–Middleton–Levine model with four-directional traffic

We study the four-directional traffic flow on a two-dimensional lattice. In the case of discrete densities, we assume equal number of vehicles in each lane. Except for the minimum density, the gridlock emerges swiftly. Two kinds of gridlock have been observed. The global gridlock dominates the system when the density is twice the minimum value. At higher densities, the system is pervaded by local gridlocks. We also analyze the time evolution of average speed. In the case of continuous densities, the vehicle numbers vary from lane to lane. The global gridlock is then destroyed by the fluctuations; while the local gridlock can still be observed.