Characteristics Of Mixed Traffic Flow Research Articles

Analysis of Mixed Traffic Flow Characteristics Based on Fleet Composition

In urban road networks, the integration of connected and autonomous vehicles (CAV) significantly influences traffic flow patterns, with the Fleet Composition—representing the positioning of these vehicles within convoys—being crucial in dictating the symmetry of information exchange amongst them. First, the vehicle composition of the mixed traffic flow is analyzed, and the mathematical analytical expressions of the random distribution characteristics of different types of vehicles are constructed. Second, we analyze the vehicle according to human characteristics in different situations. Then, consider the following characteristics and reaction times of manual drivers, establish a mixed traffic flow following model, and validate the established following. Finally, the basic graph model considering Fleet Composition is derived, and the effects of reaction time, Fleet Composition, driver following characteristics, and other parameters on road capacity under different penetration rates of CAV are analyzed by a Python and SUMO joint simulation. Finally, the characteristics of mixed traffic flow at intersections were analyzed.

Analysis of Mixed Traffic Flow Characteristics Based on Fleet Composition

In urban road networks, the integration of connected and autonomous vehicles (CAV) significantly influences traffic flow patterns, with the Fleet Composition—representing the positioning of these vehicles within convoys—being crucial in dictating the symmetry of information exchange amongst them. First, the vehicle composition of the mixed traffic flow is analyzed, and the mathematical analytical expressions of the random distribution characteristics of different types of vehicles are constructed. Second, we analyze the vehicle according to human characteristics in different situations. Then, consider the following characteristics and reaction times of manual drivers, establish a mixed traffic flow following model, and validate the established following. Finally, the basic graph model considering Fleet Composition is derived, and the effects of reaction time, Fleet Composition, driver following characteristics, and other parameters on road capacity under different penetration rates of CAV are analyzed by a Python and SUMO joint simulation. Finally, the characteristics of mixed traffic flow at intersections were analyzed.

Motorized and non-motorized mixed traffic characteristics and lateral opening spacing calculation for the section of arterial highway through small towns

A large number of motor vehicles and non-motorized vehicles mixed in the section of arterial highway crossing the town leads to many traffic problems. Therefore, it is necessary to set up a side divider between motorized and non-motorized lanes, and the appropriate spacing of lateral crossing openings to meet the needs of non-motorized vehicles crossing the highway has become a key issue that must be resolved. This paper investigates the traffic flow characteristics of mixed traffic flow on arterial highways through small town sections, and from the two dimensions of highway access efficiency and the psychological characteristics of cyclists, it calibrates the setting range of the spacing of non-motorized lateral crossing openings under different design speeds, which is used to regulate the behavior of non-motorized vehicles crossing the street, improve the safety level of the highway, reduce the lateral interference of the highway, and improve the road access efficiency. The accuracy of the research results is verified by microscopic simulation experiments, which proves that they can meet good expectations in practical engineering. The research results have theoretical significance and reference value for improving the status quo of machine-non-mixed traffic in the section of arterial highway passing through small towns, and enhancing the efficiency and safety of highway traffic. It also provides corresponding reference for the areas facing similar problems worldwide.

Freeway capacity modeling and analysis for traffic mixed with human-driven and connected automated vehicles considering driver behavior characteristics

Future freeway traffic flow will include both Human-driven Vehicles (HV) and various sizes of Connected Automated Vehicles (CAV) platoons. When following CAV platoons, HV drivers may change the car-following distance for psychological reasons, which could further affect the road capacity under mixed traffic flow. In this paper, we constructed a capacity model that considered the spatial distribution characteristics of mixed traffic flow and the behavioral traits of HV drivers when they follow CAV platoons. We surveyed 331 HV drivers using a questionnaire. 51.1% of drivers opted to increase the car-following distance when following a CAV platoon, and the amount of change in distance increased in direct proportion to the size of the platoon. A Structural Equation Model (SEM) based on survey data was developed to examine the connection between psychological variables and HV drivers’ driving behaviors. These results of the questionnaire were introduced into the capacity model construction, and the trends of capacity with CAV penetration, maximum platoon size, platoon intensity, and time headways were revealed. The results show that previous studies overestimated the capacity under mixed traffic flow, especially when the maximum platoon size is equal to or greater than 6 or the CAV penetration is between [0.6, 0.8], the overestimation of the capacity is higher. CAV penetration, maximum platoon size, and platoon intensity are positively correlated with capacity, while time headway is negatively correlated with capacity. The capacity growth is not significant when CAV penetration is between (0, 0.4]. Six is the ideal size of CAV platoons under mixed traffic flow when considering the impact of CAV platoons on HV drivers’ driving behaviors. By taking measures to promote CAV aggregation and making platoon intensity greater than 0, the capacity will be improved more significantly. For a specific car-following type, a different value of time headway will lead to a different capacity, but the impact trends will be similar.

Platoon Intensity of Connected Automated Vehicles: Definition, Formulas, Examples, and Applications

The strength of connected automated vehicles (CAVs) clustering, namely, platoon intensity, has an essential impact on the traffic capacity, safety, and stability of the mixed traffic flow with CAVs and human-driven vehicles (HDVs). This article proposes the definition, formulas, examples, analysis, and applications of CAV platoon intensity. Firstly, the CAV platoon intensity considering the maximum platoon size is defined, and its mathematical calculation method is developed. Secondly, the three types of value ranges for platoon intensity are discussed. Thirdly, the distribution characteristics of five types of time headways were proposed. Finally, the influence of CAV platoon intensity on the fundamental diagram and traffic safety of mixed traffic flow are analyzed from theoretical derivation and simulation evaluation, respectively. The result suggests the following: (1) According to the sensitivity analysis, an optimal platoon size of 5 vehicles was suggested for the CAV platoon; (2) The penetration rates and platoon intensity of CAVs can improve the capacity of mixed traffic flow, and the increase is gradually more significant; (3) The effect of the increase in platoon intensity on the capacity is not significant enough when the CAV penetration rate is low; (4) A higher platoon intensity is good for dissipating disturbances in the mixed traffic flow; and (5) CAV platoon intensity has a marginal impact on the characteristics of mixed traffic flow with the low penetration rate. It is noteworthy that a reasonable increase in platoon intensity can improve the traffic capacity and safety of mixed traffic flow.

Analysis of the impact of maximum platoon size of CAVs on mixed traffic flow: An analytical and simulation method

This paper analyzes the characteristics of mixed traffic flow with maximum platoon size of connected automated vehicles (CAVs) based on analytical and simulation methods. First, we discuss the car-following and headway types of mixed traffic flows with human-driven vehicles (HDVs), connected human-driven vehicles (CHVs), automated vehicles (AVs), and CAVs. Second, the probability distribution of the CAVs platoon size is derived based on the Markov chain model. Subsequently, the capacity model and stability condition of mixed traffic flow are proposed based on the probability distribution of the CAVs platoon size, and some characteristics of the influence of the maximum platoon size on traffic capacity and stability are analyzed. A numerical experiment based on car-following models was conducted to investigate the effect of the maximum platoon size on capacity, stability, safety, fuel consumption, and emission of mixed traffic flow. The results show that (1) the capacity of mixed traffic flow increases with the maximum platoon size of CAVs; (2) the stability of mixed traffic flow deteriorates with the increase in the maximum platoon size of CAVs; (3) the safety risk of vehicles in mixed traffic flow increases with the maximum platoon size of CAVs; (4) the fuel consumption and emissions (e.g., CO, HC, and NOx) increase with the maximum platoon size of CAVs. This indicates that the larger maximum platoon size can only improve traffic capacity, which is not conducive to the stability, safety, fuel consumption, and emissions of mixed traffic flow.

Stability Analysis and Speed-Coordinated Control of Mixed Traffic Flow in Expressway Merging Area

This paper considers the stability of mixed traffic flow and the necessity of speed control to achieve safety and efficiency goals. Therefore, a speed-coordinated control model is proposed for mixed traffic flow based on stability analysis at an expressway merging area. Firstly, stability intervals are obtained by using an intracluster stability analysis in an intercluster. Secondly, a speed-coordinated control model is set up considering the stability characteristics in a merging area. Finally, an objective function is developed, which considers time-to-collision (TTC), dynamic space occupancy (DSO), and vehicle specific power (VSP). A numerical simulation is built up to analyze the traffic conditions and stability by using the proposed model against a null scenario without using the proposed model. The analysis results indicate that the stability of the intracluster has two regions, and the stability of the intercluster is mainly affected by the speed fluctuation and the distance between the merging cluster and the vehicles on the main road. Secondly, the proposed model tends to gradually achieve a steady state when the position reaches 180 m. Meanwhile, the efficiency of the model is found to be the best when the minimum safe-distance interval is set at (18, 27). In addition, the volatility of TTC drops by 5% and the DSO has reached 11.99% in the acceleration lane optimization together with 18.37% in the main lane optimization. The frequency is found to be the highest when the VSP reaches (10, 20), and the optimized efficiency reaches 45%–50%. The model proposed in this paper will effectively analyze the stability characteristics of mixed traffic flow and provides a research foundation for the stability of mixed traffic flow. Moreover, this model builds up a multi-objective-oriented speed-coordinated control scheme for high-efficiency operations in the merging area and provides technical support for traffic management in the future.

Modeling and Simulation of Traffic Congestion for Mixed Traffic Flow with Connected Automated Vehicles: A Cell Transmission Model Approach

Connected automated vehicles (CAVs) can significantly shorten the headway of car following, thereby effectively improving the traffic capacity and injecting new power to alleviate traffic congestion. To investigate the congestion characteristics of mixed traffic flow with CAVs and human-driven vehicles (HDVs), this paper proposes a cell transmission model to capture and simulate traffic congestion for mixed traffic flow. Firstly, the Newell, adaptive cruise control (ACC), and cooperative adaptive cruise control (CACC) models are adopted to capture the car-following behavior of different vehicles. Secondly, the fundamental diagram under different penetration rates of CAVs is derived based on car-following models. Then, the cell transmission model (CTM) of mixed traffic flow is developed based on the classical CTM and fundamental diagram of mixed traffic flow. Finally, two simulation methods, mixed traffic flow CTM and micro-simulation, are designed to verify the effectiveness of the proposed model. Moreover, taking the moving bottleneck on the expressway as an example, the congestion characteristics of mixed traffic flow are analyzed using multiple indexes, such as average travel speed, congestion delay, and congestion scale. The results show the following: (i) CAVs can significantly alleviate traffic congestion, (ii) the duration of the bottleneck is positively correlated with the degree of traffic congestion, and (iii) The traffic congestion assessment results under different model parameters slightly differ, but the impact is negligible.

Variable Cell Transmission Model for Mixed Traffic Flow with Connected Automated Vehicles and Human-Driven Vehicles

The current research on the mixed traffic flow characteristics of human-driven vehicles (HDVs) and connected automated vehicles (CAVs) mainly focuses on the micro-level. To study the characteristics of the mixed traffic flow from the medium and macro level, this paper proposes a variable cell transmission model (VCTM). First, the fundamental diagram is introduced based on the phenomena of hysteresis of traffic flow. Second, the VCTM with different market penetration rates (MPR) of CAVs is proposed based on the classical cell transmission model (CTM). Then, the effectiveness of VCTM is verified by micro-simulation based on the intelligent driver model (IDM). Finally, some congestion indexes are selected to discuss the characteristics of mixed traffic flow based on the VCTM with an expressway simulation. The results show that the traffic capacity and congestion dissipation capacity gradually are increased with the increase of MPR of CAVs. The homogeneous CAVs traffic flow capacity can reach 1.41 times that of the homogeneous HDVs traffic flow, and the congestion dissipation time can be reduced by 25%. The larger MPR is, the greater the improvement effect is. In addition, compared with CTM, VCTM can reflect the delay, queuing, and dissipation of mixed traffic flow more accurately, which is helpful to capture the evolution mechanism of mixed traffic flow in the future.

고속도로 자율주행 전용차로 도입 시 혼합교통류 특성 분석 시나리오 개발 연구

Recently, various laws and regulations to revitalize autonomous vehicles and national, private research, development tasks are underway and the commercialization of connected and autonomous vehicles driving technologies is approaching. Accordingly, it is necessary to review the introduction of exclusive lanes for autonomous vehicles to establish a new road ecosystem. In this study, a scenario for analyzing the characteristics of mixed traffic flow according to the introduction of exclusive lanes was developed, and the scenario was analyzed in terms of mobility. As a result, merging area and diverging area deteriorated traffic flow as the LOS and MPR increased when introducing exclusive lanes, resulting in a decrease in traffic volume. In addition, in the LOS D-E and MPR 10-20% sections, when exclusive lanes were introduced, a phenomenon occurred in which lanes other than exclusive lanes were supersaturated. Therefore, “no exclusive lane” without platooning was the best in terms of mobility, and the adverse effect of the introduction of exclusive lanes was most pronounced in the LOS D-E and 10-20% MPR sections. However, except for the section when introducing exclusive lanes for connected and autonomous vehicles, the introduction of “third lane” better results in terms of mobility than the introduction of “first lane”. In future studies, all variable values applied in this study should be redefined in consideration of the specifications and technologies of autonomous vehicles currently being developed. This study is meaningful in establishing various scenarios to be considered when introducing exclusive lanes for autonomous vehicles based on connected and autonomous vehicles, and it is suggested that the results of this study can be used as basic frame when conducting research on exclusive lanes for autonomous vehicles in the future.

Effect of autonomous driving on traffic breakdown in mixed traffic flow: A comparison of classical ACC with three-traffic-phase-ACC (TPACC)

In this paper, an analysis of the effect of autonomous driving vehicles on traffic breakdown in mixed traffic flow consisting of randomly distributed human driving and autonomous driving vehicles is made. Autonomous vehicles based on classical (standard) adaptive cruise control (ACC) in a vehicle and on an ACC in the framework of three-phase traffic theory (TPACC – Three-traffic-Phase ACC) introduced recently [Phys. Rev. E 97 (2018) 042303] are considered. Due to the particular importance of characteristics of traffic breakdown (transition from free traffic flow to congested traffic) for almost all approaches to traffic control and management in traffic networks, the basis of this paper is a study of the effect of autonomous vehicles on the probability of traffic breakdown and on stochastic highway capacity in mixed traffic flow. We show that within a wide range of dynamic parameters of classical ACC, the ACC-vehicles can deteriorate the traffic system considerably while initiating traffic breakdown and reducing highway capacity at a bottleneck. Contrarily, in the same range of parameters of dynamic rules of TPACC, the TPACC-vehicles either do not effect on traffic characteristics or sometimes can even improve them. To understand physical reasons for the effect of classical ACC- and TPACC-vehicles on traffic breakdown, we introduce a model of ACC that can be considered a combination of dynamic features of classical ACC and TPACC. With the use of this model, we find how the amplitude of a local speed disturbance caused by the ACC in a vicinity of a bottleneck and the probability of traffic breakdown depends on the dynamic parameters of the ACC. To emphasize that the deterioration of the characteristics of mixed traffic flow through classical ACC-vehicles is not associated with a well-known effect of string instability of platoons of autonomous vehicles, we limit by a consideration of only such classical ACC-vehicles whose platoon satisfies condition for string stability.

Research on the characteristics of mixed traffic flow based on an improved bicycle model

Mixed traffic flow is a main feature of urban traffic in developing countries. Mixed bicycle flow includes human-powered and electric-powered bicycles and plays an important role in this mixed traffic flow. In mixed bicycle flow, cyclist behavior is flexible and variable. Cyclists move arbitrarily in the road and may influence the vehicle flow at intersections. Therefore, we first propose an improved bicycle model that can reproduce the main features of cyclist behavior, such as overtaking and self-protection. Then a simulation model based on the improved bicycle model is proposed to research the characteristics of mixed traffic flow in intersections. The conflict avoidance rules are then applied in the simulation model to eliminate traffic accidents. The simulation results indicate that the improved bicycle model is practical and that the density–velocity diagram of bicycle flow is similar to real traffic data. The existence of bicycle flow decreases vehicle velocity and worsens traffic flow in mixed traffic flow. However, the influence of bicycle flow might disappear at a particular vehicle density.

Analytical studies on an extended car following model for mixed traffic flow with slow and fast vehicles

The car-following model is extended to take into account the characteristics of mixed traffic flow containing fast and slow vehicles. We conduct the linear stability analysis to the extended model with finding that the traffic flow can be stabilized with the increase of the percentage of the slow vehicle. It also can be concluded that the stabilization of the traffic flow closely depends on not only the average value of two maximum velocities characterizing two vehicle types, but also the standard deviation of the maximum velocities among all vehicles, when the percentage of the slow vehicles is the same as that of the fast ones. With increase of the average maximum velocity, the traffic flow becomes more and more unstable, while the increase of the standard deviation takes negative effect in stabilizing the traffic system. The direct numerical results are in good agreement with those of theoretical analysis. Moreover, the relation between the flux and the traffic density is investigated to simulate the effects of the percentage of slow vehicles on traffic flux in the whole density regions.

Operational characteristics of mixed traffic flow under bi-directional environment using cellular automaton

Mixed traffic flow composed of autos and non-autos widely exists in developing countries and areas. To investigate the operational characteristics of the mixed traffic flow consisting of vehicles in different types (large vehicles, cas, and bicycles), we develop a cellular automaton model to replicate the travel behaviors on a bi-directional road segment with respect to the physical and mechanic ftures of different vehicle types. By implementing the eesential parameters calibrated through the field data collection, a numerical study is carried out considering the variation in volume, density, and velocity with different compositions of mixed traffic flows. The primary findings include: the average velocity of traffic flow and total volume decrease 60% and 30% after incorporating 10% bicycles, respectively; the phenomenon of double-summit in terms of the total volume appears when the proportion of bicycle is beyond 60%; the maximal total volume starts to recover when the proportion of bicycle is higher than 10 %. Language: en

An Intelligent Traffic Signal Controller Based on CAN Bus

According to the characteristics of mixed traffic flow of China, An intelligent traffic signal controller is introduced. STM32F207 and w5500 are used to design hardware structure. The software design is completed based on CoOS. Single point fuzzy control is used to improve dynamic traffic flow. Experimental results show that the intelligent traffic controller has high level of integration, powerful functions, and reliable performance.

Optimization of Signal Timing for the Mixed Traffic Flow in Vissim Simulation Environment

In order to improve the capacity of urban roads and alleviate the intersections’ congestion, this paper analyses the characteristics of mixed traffic flow in China, considers non- motor vehicles’ impact to the intersections, uses definite number of conversion to convert non-motor vehicles to motor vehicles, and then recomposes the F-B signal timing formula based on the traditional F-B signal timing method. By an example and Vissim simulation, a reasonable conversion factor is computed, The recomposed F-B signal time formula can reduce the delay and improve the efficience of the intersections, providing a new idea to signal timing under the mixed traffic flow.

Characteristics of mixed traffic flow with non-motorized vehicles and motorized vehicles at an unsignalized intersection

In this paper, a new two-dimensional car-following model is proposed to depict the features of mixed traffic flow consisting of motorized vehicles ( m -vehicle) and non-motorized vehicles ( n m -vehicle), based on the two-dimensional optimal velocity (OV) model by Nakayama et al. [A. Nakayama, K. Hasebe, Y. Sugiyama, Phys. Rev. E 71 (2005) 036121]. In the proposed model, velocity difference terms are introduced, which are regarded as important factors for traffic behavior. Numerical simulations are carried out to investigate the interaction between left-turning n m -vehicle flow and straight-going m -vehicle flow at a typical unsignalized interaction. The results show that the straight-going m -vehicle flow just next to n m -lane is disturbed more seriously than others. In addition, a well-known phenomenon in reality is observed that groups of m -vehicles and n m -vehicles pass through the intersection alternately.

Cellular automata modeling of pedestrian’s crossing dynamics

Cellular automata modeling techniques and the characteristics of mixed traffic flow were used to derive the 2-dimensional model presented here for simulation of pedestrian's crossing dynamics. A conception of "stop point" is introduced to deal with traffic obstacles and resolve conflicts among pedestrians or between pedestrians and the other vehicles on the crosswalk. The model can be easily extended, is very efficient for simulation of pedestrian's crossing dynamics, can be integrated into traffic simulation software, and has been proved feasible by simulation experiments.

Analysis of characteristics of mixed traffic flow of autopilot vehicles and manual vehicles

This work examines the positive effects on highway capacity implementing automatic vehicle control. Mixed traffic streams of a mimic freeway interchange simulate an on-ramp section with autopilot-equipped vehicles and normal manual vehicles. The simulation illustrates characteristics of speed, volume and concentration of mixed flows. The capacity trend is presented with mixed ratios of equipped cars and its market occupation rate. In order to make current highways more efficient during the transition stage, general rules for traffic control are proposed.