On-ramp Bottleneck Research Articles

Study on mixed traffic characteristics around highway on-ramp bottleneck using a microscopic simulation model

In the early mixed traffic environment, connected and automated vehicles (CAVs) tend to follow simple control rules for the sake of traffic safety and stability. Comprehensive analysis of overall mixed traffic performance and vehicle to vehicle interactions around highway on-ramp bottleneck is a basis for further traffic management and control. And yet CAVs in existing researches are mainly in the form of cooperative vehicular platoon, and mixed traffic scenarios within simulation software are not applicable for in-depth investigation. The purpose of this paper is to develop a microscopic simulation model to study in detail lane-based mixed traffic performance around the highway on-ramp. This model firstly considers vehicle characteristics of individual human vehicles (HVs) and CAVs by combining different microscopic traffic models. After the hypothetical on-ramp bottleneck structure is constructed, various simulation scenarios are developed under varying traffic volumes and changing market penetration rates (MPRs) of CAVs. Simulation results show that mixed traffic flow is improved in terms of congestion patterns and traffic capacity. For oscillating and nearly homogeneous congested traffic, congestion degrees are greatly reduced when CAV MPR above 30 % and 50 % respectively. Mixed traffic capacity is increased by 19.3 % when a smaller desired time gap set for CAVs, while it shows no significant change in a larger value. In the HV-HV interactions, traffic conflicts are slightly influenced by CAVs. Comparatively, conflict situations in HV-CAV interactions get worse, the proportion of time to collision (TTC) greater than 2 s monotonically declining with the rise in CAV MPR. It is concluded that traffic characteristics overall show a good momentum when MPR of CAV and the desired time gap of CAVs in mixed traffic are appropriate.

Physics of automated-driving vehicular traffic.

We have found that phase transitions occurring between three traffic phases [free flow (F), synchronized flow (S), and wide moving jam (J)] determine the spatiotemporal dynamics of traffic consisting of 100% automated-driving vehicles moving on a two-lane road with an on-ramp bottleneck. This means that three-phase traffic theory is a common framework for the description of traffic states independent of whether human-driving or automated-driving vehicles move in vehicular traffic. To prove this, we have studied automated-driving vehicular traffic with the use of classical Helly's model [Proceedings of the Symposium on Theory of Traffic Flow (Elsevier, Amsterdam, 1959), pp. 207-238] widely applied for automated vehicle motion. Although dynamic rules of the motion of automated-driving vehicles in a road lane are qualitatively different from those of human-driving vehicles, we have revealed that traffic breakdown (F→S transition) at the bottleneck exhibits the nucleation nature, which was observed in empirical field data measured in traffic consisting of 100% human-driving vehicles. The physics of the nucleation nature of the F→S transition in automated-driving traffic is associated with a discontinuity in the rate of lane-changing that causes the discontinuity in the rate of over-acceleration. This discontinuous character of over-acceleration leads to both the existence and self-maintaining of synchronized flow at the bottleneck in automated-driving vehicular traffic as well as to the existence at any time instant of a range of highway capacities between some minimum and maximum capacities. Within the capacity range, an F→S transition can be induced; however, when the maximum capacity is exceeded, then after some time-delay a spontaneous F→S transition occurs at the bottleneck. The phases F, S, and J can coexist each other in space and time.

Empirical Proof of the Characteristics of the Queue Discharge Rate under Different Rainfall Conditions on an Active On-Ramp Bottleneck

Empirical studies show that queue discharge rate is lower than pre-queue capacity in congestion. This is the the capacity drop phenomenon. All previous research about this event used data during clear weather conditions. This is the first time that empirical relationships between queue discharge rate and weather conditions have been studied. Previous studies show that the capacity drop is triggered by a critical density. Once this density is reached, a drop in the discharge rate is expected. We show that this critical density decreases during any weather condition. Previous studies also prove that the capacity drop is related to speed in congestion but that this might not be true during inclement weather. We show that queue discharge rate is correlated to the speed of congestion in any weather condition. We have also shown for the first time that the speed in congestion and the percentage of the capacity drop have a negative linear relationship.

The solid line prohibiting lane changing to improve traffic efficiency in the on-ramp merging area

When on-ramp bottlenecks are activated, road capacity on the mainline drops sharply. This paper presents a method of adding white solid lines between lanes of the mainline in the on-ramp area to prohibit lane-changing behaviour. The interference of on-ramp vehicles on mainline vehicles can be reduced, to improve traffic efficiency. By 2D-IDM car-following model and MOBIL lane-changing model, the simulation scene of an on-ramp bottleneck is built. In the case of a high inflow rate on the mainline, a solid line between the second and third lanes upstream of the merging area can reduce the travel time. Compared to no solid line, the density of the first and second lanes is lower, the speed is higher, and the frequency of stop-and-go waves decreases. An extra solid line between the first and second lanes cannot further improve traffic efficiency.

Statistical physics of the development of Kerner's synchronized-to-free-flow instability at a moving bottleneck in vehicular traffic.

With the use of simulations of a stochastic microscopic traffic model in the framework of the three-phase traffic theory, we have revealed the statistical physics of a traffic flow instability with respect to a transition from synchronized flow (S) to free flow (F) (Kerner's S→F instability) at a moving bottleneck (MB) occurring through a slow-moving vehicle in vehicular traffic. We have found that the S→F instability can occur at the MB more frequently than at an on-ramp bottleneck. From a comparison of the occurrence of the S→F instability at the MB and on-ramp bottleneck at the same probability of traffic breakdown and the same flow rate it has been found that, whereas the frequency of the S→F instability at the on-ramp bottleneck barely changes, the larger the velocity of the MB, the more frequently the S→F instability occurs at the MB. Contrarily, when the MB velocity decreases considerably, then rather than the S→F instability, in synchronized flow at the MB the classical traffic flow instability leading to the emergence of wide-moving jams (S→J instability) occurs. It has been found that the physics of the intensification of the S→F instability at the MB with the increase in the MB velocity is associated with the increase in the mean space gap (mean time headway) between vehicles in synchronized flow. For this reason, when the MB velocity increases, there is an MB velocity at which the S→F instability dominates the S→J instability: The MB velocity influences considerably on the competition between the S→F and classical traffic flow instabilities in synchronized flow.

Traffic flow modeling in fog with cellular automata model

To explore the traffic flow characteristics in fog, a modified one-dimensional cellular automata model is developed considering the limited visual distance of drivers in low visibility. We suppose that drivers can be categorized into seven groups according to the radical degree, and the number of drivers follows the Gaussian distribution in general road system. Capacity shrinkage is confirmed, and there is a positive correlation between the speed limits and extent of capacity shrinkage. When on-ramp bottleneck is considered in open boundary condition, bottleneck capacity fluctuates greatly when enter probability of on-ramp is lower than the threshold, and the dependency between main lane capacity and distance away from on-ramp is weak in most cases. Besides, capacity phase diagrams of various test scenario show that the bottleneck capacity will not improve after the entry probability of the main lane reaches a certain value. This study can be an inspiration for traffic flow modeling in fog and other infrequent weather.

Integrated mainline and ramp signal control for expressway on-ramp bottleneck with unequal lane-setting

Ramp metering is a major measure to reduce traffic congestion and prevent traffic breakdown at on-ramp bottlenecks. However, its efficiency is often limited by the excessive traffic demands on either the mainline or the on-ramp. Meanwhile, unequal lane-setting, in which the number of mainline lanes is more than on-ramp, is a common infrastructure setup in urban expressway system. In this paper, a novel Travel time balanced Mainline and Ramp integrated Control strategy (T-MRC) is proposed for unequal lane-setting on-ramp bottlenecks, which follows the feedback control framework. The control goal is to maximize the traffic efficiency, while in view of the typical early-onset phenomenon, productivity (efficiency index) is selected to replace the conventional outflow as the optimization objective. On this basis, the balance of travel time in different types of lanes (controlled on-ramp, controlled, and uncontrolled mainline lanes) is considered, and two regulators are used in the green time allocation algorithm. A high-precision microscopic simulation model in Shanghai is set up, and five control strategy scenarios are compared. Results indicate that the T-MRC strategy outperforms all others that the productivity is improved dramatically (>85%) and the vehicle total delay (VTD) of the system is reduced significantly (>30%) compared to no-control scenario.

Spatiotemporal trajectory characteristic analysis for traffic state transition prediction near expressway merge bottleneck

The theoretical analysis of traffic flow with empirical vehicle trajectory data contained within this study allows for the explanation, reconstruction, and prediction of spatiotemporal transition characteristics of traffic conditions. Using an unmanned aerial vehicle (UAV) during a morning rush hour on a working day, observations of congestion evolution near an on-ramp bottleneck of an expressway was captured. The empirical high-fidelity trajectory data of 621 vehicles were extracted. The major findings include:(1) Macroscopic perspective: Three traffic states (free flow, metastable traffic flow, and jam) were observed with different spatiotemporal physical structures and their critical characteristics in a continuous first-order phase transition. The spontaneous spatiotemporal traffic breakdown and capacity drop were also captured, the critical points of which were also recorded. The features of widening synchronized flow pattern, general pattern, and the nature of nucleation described in the three-phase traffic theory were identified, which provides a new observational cognition for congestion formation and development.(2) Microscopic perspective: The impact of lane changes on immediate vehicles were modeled and quantified with the fluctuation magnitude of speed and the theoretical lag distance, which provides a method to identify the source of perturbation and determine the microscopic critical threshold of vehicle between macroscopic phase transitions. The research shows a lane changer could cause a forced deceleration of an immediate vehicle on a target lane after inserting itself with critical spacing headway below approximately 15–20 m. The average deceleration duration of vehicles in different traffic states can be captured as crucial driving features from downstream to help predict traffic state transition in a real bottleneck.

Adaptive Cruise Control Operation for Improved Motorway Traffic Flow

This study presents an ACC (adaptive cruise control)–based traffic control strategy which aims to adapt in real time the driving behavior of ACC-equipped vehicles to the prevailing traffic conditions so that motorway traffic flow efficiency is improved. The potential benefits obtained by applying the proposed control concept are demonstrated for different ACC penetration rates by use of validated microscopic simulation applied to a real motorway stretch where recurrent traffic congestion is created under the current manual driving conditions because of an on-ramp bottleneck. The simulation results demonstrate that, even for low penetration rates of ACC vehicles, the proposed control concept improves the average vehicle delay and fuel consumption by reducing the space-time extent of congestion compared with the case of only manually driven or regular ACC vehicles.

Calibration of a micro-traffic simulation model with respect to the spatial-temporal evolution of expressway on-ramp bottlenecks

On-ramp bottlenecks are usually the direct cause of traffic breakdowns on expressways, affecting the overall traffic operation of the expressway. A high-precision simulation model is the basis of an on-ramp bottleneck active traffic management strategy design and evaluation. This paper presents a practical and effective calibration method with respect to the congestion spatial-temporal evolution and two-capacity phenomenon of bottlenecks. An integrated criterion is proposed to evaluate how well the micro-simulation model can replicate the breakdown process. The widely used micro-traffic simulation model VISSIM is selected to simulate two on-ramp bottlenecks on an expressway in Shanghai, China. Firstly, 28 parameters of car-following and lane-changing behaviors are analyzed, and nine significant parameters of the operation at on-ramp bottlenecks are selected using sensitive analysis. Then, an orthogonal experiment is conducted to seek the best parameter combination. Finally, the calibrated simulation model is validated using a dataset of other days. Moreover, the transferability of the calibrated model is tested at Wuning bottleneck. The results show that the calibrated model can not only replicate the congestion evolution process and the special early onset breakdown phenomenon, but it can also apply to other similar on-ramp bottlenecks directly. The proposed calibration procedure, the integrated criterion for precision evaluation, and the selected significant parameters are meaningful to inspire rapid and effective calibration for other simulators.

Macroscopic traffic flow modeling with adaptive cruise control: Development and numerical solution

The incorporation of two macroscopic approaches reflecting Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) traffic dynamics in a gas-kinetic (GKT) traffic flow model is presented. The first approach was recently analyzed in the literature aiming to describe the effects induced by the ACC and CACC systems due to changes of the speed of the leading car(s) by the introduction of an acceleration/deceleration term. The second approach is a novel one and is based on the introduction of a relaxation term that satisfies the time/space-gap principle of ACC or CACC systems. In both approaches, the relaxation time is assigned on multiple leading vehicles in the CACC case; whereas in the ACC case this relaxation time is only assigned to the direct leading vehicle. We numerically approximate the resulting models by an accurate and robust high-resolution finite volume relaxation scheme, where the nonlinear system of partial differential equations is first recast to a diagonalizable semi-linear system and is then discretized by a higher-order WENO scheme. Numerical simulations investigate the effect of the different ACC and CACC approaches to traffic flow macroscopic stability with respect to perturbations introduced in a ring road and to flow characteristics in open freeways with merging flows at an on-ramp. Following from the numerical results, it can be concluded that CACC vehicles increase the stabilization of traffic flow, with respect to both small and large perturbations, compared to ACC ones. Further, the proposed CACC approach can better improve the dynamic equilibrium capacity and traffic dynamics, especially at the on-ramp bottleneck.

Development and application of an integrated traffic simulation and multi-driving simulators

Professional virtual reality experiment tools, including driving simulators and traffic simulators, have their strengths and weaknesses. The integration of the two simulators will enhance the ability of both traffic modeling and driving simulation and present a new area of applications. This paper develops, implements, and validates an experimental platform that integrated a traffic simulator with multiple driving simulators (TSMDS). As a connected multi-user framework that allows multiple drivers who are simultaneously handling many driving simulators, it not only allows driver behavior experiments to be more accurate, controlled, and versatile but also simulates special driving behavior or multi-vehicle interactions under more realistic traffic flow environments. To validate the performance of TSMDS, 27 drivers were recruited to attend the lane changing experiments at a recurring on-ramp bottleneck and left-turn experiments at a two-phase signalized intersection in Shanghai. Both experiments required several drivers to drive the TSMDS and fulfill several complicated lane changing/crossing behaviors through their interaction. The results show that both the participants’ response and lane changing/crossing data that were obtained from the experiment are consistent with the field observation, which confirms the validity of the integrated platform.

Study on traffic characteristics for a typical expressway on-ramp bottleneck considering various merging behaviors

Recurring bottlenecks at freeway/expressway are considered as the main cause of traffic congestion in urban traffic system while on-ramp bottlenecks are the most significant sites that may result in congestion. In this paper, the traffic bottleneck characteristics for a simple and typical expressway on-ramp are investigated by the means of simulation modeling under the open boundary condition. In simulations, the running behaviors of each vehicle are described by a car-following model with a calibrated optimal velocity function, and lane changing actions at the merging section are modeled by a novel set of rules. We numerically derive the traffic volume of on-ramp bottleneck under different upstream arrival rates of mainline and ramp flows. It is found that the vehicles from the ramp strongly affect the pass of mainline vehicles and the merging ratio changes with the increasing of ramp vehicle, when the arrival rate of mainline flow is greater than a critical value. In addition, we clarify the dependence of the merging ratio of on-ramp bottleneck on the probability of lane changing and the length of the merging section, and some corresponding intelligent control strategies are proposed in actual traffic application.

Probabilistic physical characteristics of phase transitions at highway bottlenecks: incommensurability of three-phase and two-phase traffic-flow theories.

Physical features of induced phase transitions in a metastable free flow at an on-ramp bottleneck in three-phase and two-phase cellular automaton (CA) traffic-flow models have been revealed. It turns out that at given flow rates at the bottleneck, to induce a moving jam (F → J transition) in the metastable free flow through the application of a time-limited on-ramp inflow impulse, in both two-phase and three-phase CA models the same critical amplitude of the impulse is required. If a smaller impulse than this critical one is applied, neither F → J transition nor other phase transitions can occur in the two-phase CA model. We have found that in contrast with the two-phase CA model, in the three-phase CA model, if the same smaller impulse is applied, then a phase transition from free flow to synchronized flow (F → S transition) can be induced at the bottleneck. This explains why rather than the F → J transition, in the three-phase theory traffic breakdown at a highway bottleneck is governed by an F → S transition, as observed in real measured traffic data. None of two-phase traffic-flow theories incorporates an F → S transition in a metastable free flow at the bottleneck that is the main feature of the three-phase theory. On the one hand, this shows the incommensurability of three-phase and two-phase traffic-flow theories. On the other hand, this clarifies why none of the two-phase traffic-flow theories can explain the set of fundamental empirical features of traffic breakdown at highway bottlenecks.

Platoon-based macroscopic model for intelligent traffic flow

This paper proposes a macroscopic model to describe the dynamics of intelligent traffic flow where intelligent vehicles are driving closer to each other than manual vehicles and operating in a form of many platoons each of which contains several vehicles. The model is developed from a car-following model which allows us to obtain well tractable macroscopic equations for such platoon-based traffic operation. A linear stability diagram is constructed from the developed model based on the linear stability method for a certain model parameter set. It is found analytically that platoon-based driving behaviour of intelligent vehicles enhances the stabilisation of traffic flow with respect to a small perturbation. Numerical simulation of an open freeway with an on-ramp bottleneck supports our analytical results. We have argued that the newly developed macroscopic model will provide a better insight into the dynamics of intelligent traffic flow.

Driver relaxation impacts on bottleneck activation, capacity, and the fundamental relationship

This study examines traffic behavior in the vicinity of a freeway bottleneck, revisiting commonly held assumptions and uncovering systematic biases that likely have distorted empirical studies of bottleneck formation, capacity drop, and the fundamental relationship (FR). This simulation-based study examines an on-ramp bottleneck using Newell’s lower order car following model with a driver relaxation factor added for the vehicles that enter or are immediately behind an entering vehicle (termed “affected vehicles”). The affected vehicles will tolerate a truncated headway for a little while after an entrance but slowly relax back to their preferred speed–spacing relationship. All other vehicles remain on their preferred speed–spacing relationship throughout.Simulating conventional detector measurements, we show that flow is supersaturated in any sample containing an affected vehicle with a truncated headway, i.e., the flow is higher than the underlying FR would predict. This systematic bias is not readily apparent in the detector measurements, during the initial queue formation speeds remain close to free speed and the supersaturated states can exceed the bottleneck capacity. As the affected drivers relax, the high flows become unsustainable so a queue initially forms downstream of the on-ramp (consistent with earlier empirical results) only later receding upstream past the on-ramp. This initial phase of activation often lasts several minutes. Without any evidence of queuing upstream of the ramp, the conventional point bottleneck model would erroneously indicate that the bottleneck is inactive. Thus, an empirical study or traffic responsive ramp meter could easily mistake the supersaturated flows to be the bottleneck’s capacity flow, when in fact these supersaturated flows simply represent system loading during the earliest portion of bottleneck activation. Instead of flow dropping “from capacity”, we see flow drop “to capacity” from supersaturation. We also discuss how the supersaturated states distort empirically observed FR. We speculate that these subtle mechanisms are very common and have confounded the results of many past empirical studies.

Freeway On-ramp Bottleneck Activation, Capacity and the Fundamental Relationship

This study examines traffic behavior in the vicinity of a freeway bottleneck, revisiting commonly held assumptions and uncovering systematic biases that likely have distorted empirical studies of bottleneck formation, capacity drop, and the fundamental relationship (FR). This simulation-based study examines an on-ramp bottleneck using Newell's lower order car following model with a driver relaxation factor added for the vehicles that enter or are immediately behind an entering vehicle (termed “affected vehicles”). The affected vehicles will tolerate a truncated headway for a little while after an entrance but slowly relax back to their preferred speed-spacing relationship. All other vehicles remain on their preferred speed-spacing relationship throughout.Simulating conventional detector measurements, we show that flow is supersaturated in any sample containing an affected vehicle with a truncated headway, i.e., the flow is higher than the underlying FR would predict. This systematic bias is not readily apparent in the detector measurements and during the initial queue formation the supersaturated states can exceed the bottleneck capacity. As the affected drivers relax, the high flows become unsustainable so a queue initially forms downstream of the on-ramp (consistent with earlier empirical results) only later receding upstream past the on-ramp. This initial phase of activation often lasts several minutes. Without any evidence of queuing upstream of the ramp, the conventional point bottleneck model would erroneously indicate that the bottleneck is inactive. Thus, an empirical study or traffic responsive ramp meter could easily mistake the supersaturated flows to be capacity flow, when in fact these supersaturated flows simply represent system loading during the earliest portion of bottleneck activation. Instead of flow dropping “from capacity”, we see flow drop “to capacity” from supersaturation. We also discuss how the supersaturated states distort empirically observed FR. We speculate that these subtle mechanisms are very common and have confounded the results of many past empirical studies.

Extended bottlenecks, the fundamental relationship, and capacity drop on freeways

This paper presents evidence that the commonly used point bottleneck model is too simplistic for freeway bottlenecks, the actual mechanism appears to occur over an extended distance. We find evidence of subtle flow limiting and speed reducing phenomena more than a mile downstream of a lane drop bottleneck. These phenomena impact the fundamental relationship, FD. Close to the lane drop the free flow regime appears to come from a “parabolic” FD, but further downstream the relationship straightens to a “triangular” FD and throughput increases. We develop a theory to explain the underlying mechanisms. These insights should help resolve the decades long debate about the shape of the FD. The phenomena also provide a mechanism that may contribute to the empirically observed capacity drop often seen at bottlenecks. Although we study a lane drop, this work should be transferable to other bottlenecks where the capacity restriction persists for an extended distance, e.g., a corridor with a fixed number of lanes and an on-ramp bottleneck.

Extended Bottlenecks, the Fundamental Relationship, and Capacity Drop on Freeways

This paper presents evidence that the commonly used point bottleneck model is too simplistic for freeway bottlenecks, the actual mechanism appears to occur over an extended distance. We find evidence of subtle flow limiting and speed reducing phenomena more than a mile downstream of a lane drop bottleneck. These phenomena impact the fundamental relationship, FD. Close to the lane drop the free flow regime appears to come from a “parabolic” FD, but further downstream the relationship straightens to a “triangular” FD and throughput increases. We develop a theory to explain the underlying mechanisms. These insights should help resolve the decades long debate about the shape of the FD. The phenomena also provide a mechanism that may contribute to the empirically observed capacity drop often seen at bottlenecks. Although we study a lane drop, this work should be transferable to other bottlenecks where the capacity restriction persists for an extended distance, e.g., a corridor with a fixed number of lanes and an on-ramp bottleneck.

A theory of traffic congestion at moving bottlenecks

The physics of traffic congestion occurring at a moving bottleneck on a multi-lane road is revealed based on the numerical analyses of vehicular traffic with a discrete stochastic traffic flow model in the framework of three-phase traffic theory. We find that there is a critical speed of a moving bottleneck at which traffic breakdown, i.e. a first-order phase transition from free flow to synchronized flow, occurs spontaneously at the moving bottleneck, if the flow rate upstream of the bottleneck is great enough. The greater the flow rate, the higher the critical speed of the moving bottleneck. A diagram of congested traffic patterns at the moving bottleneck is found, which shows regions in the flow-rate–moving-bottleneck-speed plane in which congested patterns emerge spontaneously or can be induced through large enough disturbances in an initial free flow. A comparison of features of traffic breakdown and resulting congested patterns at the moving bottleneck with known ones at an on-ramp (and other motionless) bottleneck is made. Nonlinear features of complex interactions and transformations of congested traffic patterns occurring at on- and off-ramp bottlenecks due to the existence of the moving bottleneck are found. The physics of the phenomenon of traffic congestion due to ‘elephant racing’ on a multi-lane road is revealed.