Homogeneous Traffic Flow Research Articles

Development of Capacity Estimation Models for Multi-lane Roads under Heterogeneous Traffic Conditions

The objective of this study is to develop capacity models to estimate the traffic carrying capacity of multi-lane roads with heterogeneous traffic flows. Since capacity is an important parameter in traffic engineering studies, it is vital that it is accurately estimated. Most of the current capacity estimation methodologies available are developed based on homogeneous traffic flows and hence not conducive for use in heterogeneous traffic conditions observed in Sri Lanka. Therefore, this study is done to fulfill the requirement of a capacity estimation model for this purpose. Fifty midblock sections were surveyed using manual flow data collection methods and a novel Google Application Program Interface (API) based method for speed data collection. Based on the collected data, capacity values were developed following the fundamentals of traffic flow. Regression models were built to estimate four-lane and six-lane capacity values based on roadway characteristics such as effective lane width, access point density, median type, and built environment condition. Separate models were developed because the impact these characteristics have on four-lane and six-lane roads are different. The models showed good fit with R2 values of 0.81 and 0.86 for four-lane and six-lane roads, respectively. The base capacity value of a four-lane urban road was estimated to be 2044 pcu/h/l and for a six-lane sub-urban road section 2108 pcu/h/l. The outcomes of this study can be used to develop capacity guidelines in countries with heterogeneous traffic conditions for capacity estimation.

Variable Speed Limit Control for the Motorway–Urban Merging Bottlenecks Using Multi-Agent Reinforcement Learning

Traffic congestion is a typical phenomenon when motorways meet urban road networks. At this special location, the weaving area is a recurrent traffic bottleneck. Numerous research activities have been conducted to improve traffic efficiency and sustainability at bottleneck areas. Variable speed limit control (VSL) is one of the effective control strategies. The primary objective of this paper is twofold. On the one hand, turbulent traffic flow is to be smoothed on the special weaving area of motorways and urban roads using VSL control. On the other hand, another control method is provided to tackle the carbon dioxide emission problem over the network. For both control methods, a multi-agent reinforcement learning algorithm is used (MAPPO: multi-agent proximal policy optimization). The VSL control framework utilizes the real-time traffic state and the speed limit value in the last control step as the input of the optimization algorithm. Two reward functions are constructed to guide the algorithm to output the value of the dynamic speed limit enforced within the VSL control area. The effectiveness of the proposed control framework is verified via microscopic traffic simulation using simulation of urban mobility (SUMO). The results show that the proposed control method could shape a more homogeneous traffic flow, and reduces the total waiting time over the network by 15.8%. In the case of the carbon dioxide minimization strategy, the carbon dioxide emission can be reduced by 10.79% in the recurrent bottleneck area caused by the transition from motorways to urban roads.

Hybrid characteristics of heterogeneous traffic flow mixed with electric vehicles considering the amplitude of acceleration and deceleration

In order to explore the influence of electric vehicles on the traffic flow characteristics of traditional fuel vehicles, this paper proposes an improved cellular automata model considering the physical properties of vehicles, such as, the acceleration and deceleration amplitude, relative speed and safety distance etc. Based on the sensitivity analysis of the randomization probability, combined with the actual data, the model parameters are quantified to simulate the electric-fuel vehicle mixed traffic flow. Through numerical simulation, the results show that compared with NS (Nagel–Schreckenberg) model and VE(Velocity Effect) model, the improved model can reproduce rich traffic phenomena and is closer to the measured data. With the increase of electric vehicle permeability, the flow rate and speed are increased, the congestion near the critical density is reduced and the traffic safety is improved. At high density, the congestion shows a trend of decreasing first, then increasing and then decreasing again, and the safety is lower than that of homogeneous traffic flow. The speed fluctuation of fuel vehicles is enlarged, and the speed of the overall traffic flow shows an upward trend. In addition, it is found that the TIT curve can identify the state change of traffic flow, and electric vehicles in high-density mixed flow cause greater disturbance to the speed of traffic flow and reduces traffic safety. The results of this paper can provide a basis for further research of electric-fuel vehicle hybrid traffic flow.

Service Function Chains Deployment for 5G Slice With Bandwidth Coupling

Network function virtualization (NFV) technology is the key technology to solve the flexibility problem of 5G network. Multiple service function chains (SFCs) that coexist on physical infrastructure within a slice share the resources of the infrastructure. Therefore, how to allocate resources to an SFC under QoS constraints and further, how to build a resource sharing model among multiple SFCs are significant. In this letter, we jointly consider the above problems and propose a coupling bandwidth resource allocation model (CBRA) for the resource sharing of multiple SFCs. In this model, we define the effective coupling bandwidth increment(ECBI) based on the statistical feature of traffic and construct the homogeneous traffic flows on the infrastructure within the slice as the coupled traffic. Furthermore, based on the CBRA model, we establish an integer linear programming (ILP) problem aiming at minimizing resource occupancy to solve the SFCs deployment and realize the joint resource allocation of multiple SFCs. Simulation results show that the deployment algorithm can achieve QoS guarantee and effectively save bandwidth for homogeneous business.

A Car-Following Model for Mixed Traffic Flows in Intelligent Connected Vehicle Environment Considering Driver Response Characteristics

Autonomous driving technology and vehicle-to-vehicle communication technology make the hybrid driving of connected and automated vehicles (CAVs) and regular vehicles (RVs) a long-existing phenomenon in the coming future. Among the existing studies, IDM models are mostly used to study the performance of homogeneous traffic flow. To explore the stability of mixed traffic flow, an extended intelligent driver model (IDM) based car-following model was proposed for mixed traffic flow (MTF) with both CAVs and RVs, considering the headway, the speed and acceleration of multiple front vehicles, as well as the response characteristics of RV drivers. Through the linear stability analysis, the criterion for the stability of MTFs was derived, and the relationship among the penetration rate of CAVs, equilibrium velocity and traffic stability in MTF are discussed. Based on the above theoretical model, a numerical simulation was conducted in two typical scenarios of starting and braking. The results showed that, at the microscopic scale, the vehicle in the Cooperative Adaptive Cruise Control (CACC) mode could significantly decelerate in response to the interference from other vehicles in the same traffic environment. At the macroscopic scale, as the penetration rate of CAVs increased, the overall acceleration fluctuation of the traffic flow decreased. At the same penetration rate of CAVs, the higher density of CAVs coincided with the higher stability of the MTF. When the penetration rate of CAVs was 50%, the degree of distribution had the greatest impact on the MTF. When the penetration rate of CAVs exceeded 70%, the degree of distribution had little impact on the MTF. This research can provide basic theoretical support for the management and control of MTF in the future.

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.

Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles

With the increasing maturity of automatic driving technology, the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow, which consists of human-driving and autonomous vehicles. To better study the characteristics of the heterogeneous traffic system, this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow, which considers the self-stabilizing effect of vehicles. Through linear and nonlinear methods, this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect. Finally, the model is verified by numerical simulation. Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable, and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively. In addition, the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.

A multi-class first-order traffic flow model to explain the disordered behaviour of vehicles

Disordered traffic streams are generally characterised by the presence of numerous vehicle classes having different sizes and operational characteristics. Unlike homogeneous traffic flow, smaller vehicles percolate between the bigger ones, invalidating the lane discipline and therefore requiring a different modelling approach. Each vehicle traverses through a series of opportunities created by other vehicles that are not only viable but also accessible, thus defining a permeable medium. Our objective is to develop an analytical traffic flow model that quantifies such opportunities for individual vehicle classes to traverse downstream. Equilibrium speed functions have been redefined based on a new metric termed as traversable distance. The inter-class flow dynamics of small-sized vehicles has further resulted in a significant reduction in their travel time.

Macroscopic Traffic-Flow Modelling Based on Gap-Filling Behavior of Heterogeneous Traffic

Traffic-flow modelling has been of prime interest to traffic engineers and planners since the mid-20th century. Most traffic-flow models were developed for the purpose of characterizing homogeneous traffic flow. Some of these models are extended to characterize the complex interactions involved in heterogeneous traffic flow. Existing heterogeneous traffic-flow models do not characterize the driver behavior leading to gap filling in heterogeneous traffic conditions. This study aimed at explaining the gap-filling behavior in heterogeneous traffic flow by using the effusion model of gas particles. The driver’s behavior leading to gap filling in heterogeneous traffic was characterized through developing analogies between the traffic flow and the Maxwell–Boltzmann equation for effusion of gases. This model was subsequently incorporated into the Payne–Whitham (PW) model by replacing the constant anticipation term. The proposed model was numerically approximated by using Roe’s scheme, and numerical simulation of the proposed model was then carried out by using MATLAB. The results of the proposed and PW models were therefore compared. It is concluded that the new model proposed in this study not only produces better results compared to the PW model, but also better captures the expected reality. The main difference between the behavior of the two models is that the effect of bottleneck in the density of traffic is propagated in the form of a shockwave travelling backwards in time in the new model, while the PW model does not exhibit this effect.

Intelligent back-looking distance driver model and stability analysis for connected and automated vehicles

The connected and automated vehicles (CAVs) technologies provide more information to drivers in the car-following (CF) process. Unlike the human-driven vehicles (HVs), which only considers information in front, the CAVs circumstance allows them to obtain information in front and behind, enhancing vehicles perception ability. This paper proposes an intelligent back-looking distance driver model (IBDM) considering the desired distance of the following vehicle in homogeneous CAVs environment. Based on intelligent driver model (IDM), the IBDM integrates behind information of vehicles as a control term. The stability condition against a small perturbation is analyzed using linear stability theory in the homogeneous traffic flow. To validate the theoretical analysis, simulations are carried out on a single lane under the open boundary condition, and compared with the IDM not considering the following vehicle and the extended IDM considering the information of vehicle preceding and next preceding. Six scenarios are designed to evaluate the results under different disturbance strength, disturbance location, and initial platoon space distance. The results reveal that the IBDM has an advantage over IDM and the extended IDM in control of CAVs car-following process in maintaining string stability, and the stability improves by increasing the proportion of the new item.

Features of the functional classification of roads

Problem The article is devoted to the functional classification of roads and the need for its application in modern standards for the roads design. In Ukraine the role and importance of the roads functional classification is clearly underestimated, which is due to the lack of a transport planning system, whose purpose is to establish a hierarchy of the road network taking into account the functions performed by each street or road (transit traffic, local traffic, and so on), and insufficient information on the benefits of functional systems. Goal. The objective of the work is to determine the criteria for the classification of roads by functional features and to modernize design standards in terms of establishing the category of road. Methodology. The need for a functional classification of roads was initially associated with the development of the road network and the need to streamline its planning. The growth of traffic flows required their optimization and the need to take into account their composition and traffic conditions when normalizing the main parameters of roads. This issue escalated with the beginning of the creation of a system for the formation and use of land, since land use is an important factor determining the function of roads. Given the low level of motorization in the past and the low density of the road network, this problem arose in our country much later. Accordingly, only at the end of the 80s did we have a functional classification in the norms of designing a road network. Already in the middle of the last century, it became apparent that individual roads or streets cannot serve any trip. Most trips involve traffic on a network of roads. For this, it is necessary to determine the conditions (routes) of the most efficient traffic, whose requirements the components of this network must satisfy. This problem is solved using the functional classification of roads, during which the streets and roads are divided into classes or systems, depending on the nature of the served connections. Results. One important advantage of the system of functional classification of roads cannot be overlooked: as you know, the main cause of accidents when driving in traffic flows is the difference in speeds. Due to the formation of roads with more homogeneous traffic flows, in which it is possible to provide similar speeds for different vehicles, the functional classification can significantly increase the level of road safety. It is advisable to start improving design standards by improving the classification of roads, which is an essential element of the regulatory system in the road sector. In this case, one must take into account foreign experience in classifying highways according to functional requirements. Originality. In Ukraine, insufficient attention is paid to the functional classification of roads. Publications covering the issues of functional classification of Ukrainian roads are very few. At present, the functional classification of roads is present in the norms of all developed countries of the world, The analysis of foreign experience confirms the validity of its introduction. Practical value. Functional classification can be used in planning the development of the road network, determining the appropriate administrative affiliation, and also as a guide for developing standards for the design of various types of roads.

Traffic Oscillations Mitigation in Vehicle Platoon Using a Car-Following Control Model for Connected and Autonomous Vehicle

Traffic oscillations often occur in road traffic, they make traffic flow unstable, unsafe and inefficient. Emerging connected and autonomous vehicle (CAV) technologies are potential solutions to mitigating the traffic oscillations for the advantages that CAVs are controllable and cooperative. In order to study a control strategy and the effectiveness of CAVs in mitigating traffic oscillations and improving traffic flow and analyse the characteristics of homogeneous traffic flow made up of CAVs and heterogeneous traffic flow made up of CAVs and RVs when traffic oscillations appear in traffic flow. Firstly, the formation and propagation of traffic oscillations in a platoon of RVs are simulated and analysed. Then, a car-following control model is built to control the longitudinal motion of CAVs, and real-time information of preceding CAV is used in the model and this can make the motion of CAVs more cooperative. The model reflects an idea named “slow-in” and “fast-out,” and this idea is helpful to mitigate traffic oscillations. Then, numerical simulations of homogeneous traffic flow of a platoon of CAVs and simulations of heterogeneous traffic flow containing CAVs and RVs are conducted, and different penetration rates (0, 0.2, 0.4, 0.6, 0.8, and 1) of CAVs are considered in the simulations of heterogeneous traffic flow. The characteristics and evolution of traffic flow are analysed and some indexes reflecting traffic efficiency and stability are calculated and analysed. Simulation results show that there are smaller velocity fluctuation, less stopping time and shorter length of road occupied when vehicle platoon contains CAVs (penetration rates are from 0.2 to 1) compared to the platoon containing only RVs (without CAVs). As for the heterogeneous traffic flow containing CAVs and RVs, these three indexes decrease with the increase of penetration rates (from 0.2 to 1) of CAVs. These results indicate that CAVs with the car-following control model in vehicle platoon are beneficial for mitigating traffic oscillations and improving traffic flow.

An efficient heterogeneous platoon dispersion model for real-time traffic signal control

In China, urban arterial traffic presents a heterogeneous flow feature because of a high proportion of buses. Existing research on heterogeneous platoon dispersion models is very complex, which are not suitable for real-time signal timing optimization. Considering the classic Robertson’s model has a simple form and high computation efficiency, an efficient heterogeneous platoon dispersion model is proposed based on Robertson’s model. Firstly, the classic Robertson’s model is used to capture different homogeneous platoon dispersion features. Then, these classic Robertson’s models for homogeneous traffic flow are superposed to capture the characteristic of heterogeneous traffic flow. Finally, based on field observations, the performance of the proposed model, the classic Robertson’s model, and the mixed Gaussian model are compared. The results show that the proposed model has a better prediction accuracy and higher computational efficiency, compared with the classic Robertson’s model and the mixed Gaussian model. It is noteworthy that the proposed model not only better describes the dispersion feature of heterogeneous traffic flow but also meets the requirement of real-time signal control.

Experimental investigation of the effect of roundabouts on noise emission level from motor vehicles

Roundabouts can provide benefits in many ways. They are safer, more efficient, less costly and more aesthetically appealing than standard at-grade intersections (controlled and signalized). The administrations have often identified roundabouts as a proven safety countermeasure for the following reasons: a) reduce overall conflict points and remove left-turn conflicts; b) reduce the vehicle speeds; and c) reduce accident severity for all users, allow safer merges into circulating traffic, and provide more time for all users to detect and correct their mistakes or the mistakes of others due to lower vehicle speeds. Also, from an operational point of view, roundabouts offer the following significant advantages: a) may reduce delays and queues than other forms of controlled intersections; b) can reduce lane requirements between intersections, including bridges between interchange ramp terminals; and c) create possibility for adjacent signals to operate with more efficient cycle lengths where the roundabout replaces a signal that is setting the controlling cycle length. Furthermore, roundabouts can provide important environmental benefits reducing delays and the number and duration of stops. Even in heavy traffic, vehicles keep moving in the queue rather than coming to a complete stop. This may reduce significantly noise and air quality impact as well as fuel consumption by reducing the number of acceleration/deceleration cycles and the time spent idling. In this article, the environmental aspects associated with roundabouts are treated with reference to issues related to noise production. The experimental investigation will refer to a heterogeneous succession of intersections (standard intersections, two-way stop-controlled and roundabouts) characterized by homogeneous traffic flows. The results of the research are interesting and contribute to consolidate the awareness, already highlighted by other international studies, of the role of roundabouts as effective measures to mitigate traffic noise. © 2019 Institute of Noise Control Engineering

Modelling of Noise Pollution Due to Heterogeneous Highway Traffic in India

Abstract Compared to homogeneous traffic flow, traffic speed variation is drastic with the involvement of heterogeneity. With an intent of studying the negative upshot of fluctuating speeds of heterogeneous traffic on the environment, the current paper is the outcome of the research done on various highways located in the states of Andhra Pradesh and Telangana in India, with an objective of developing a comprehensive noise prediction model by taking into account the traffic and roadway factors. Quantified noise levels [Leq (dBA) and L10 (dBA)] revealed that for the traffic speed variation of 10 to 95 kmph, the traffic noise levels were significantly affected by the variations in the proportion of the vehicle. On a specific note, the proposed model can be effectively used for the highway traffic noise prediction especially for the heterogeneous traffic, as the difference between the measured and predicted noise levels are within 1 to 10 dB (A).

An Ecological Adaptive Cruise Control for Mixed Traffic and Its Stabilization Effect

With the rapid development of technologies, the ecological control strategies of connected and autonomous vehicle (CAV) technologies are gaining more and more attention. In this paper, a rule-based ecological cruise control, called the ecological smart driver model (EcoSDM), is proposed to improve the fuel efficiency of an individual vehicle and the traffic flow. By adjusting the spacing between the leading and the following vehicles, EcoSDM provides smoother deceleration and acceleration than the enhanced intelligent driver model (Enhanced-IDM) and the smart driver model (SDM). The linear stability of EcoSDM is analyzed both theoretically and numerically. The numerical results validate the results of theoretical analysis. Moreover, the simulations results show that EcoSDM outperforms the Enhanced-IDM and SDM in terms of stabilization effect on homogeneous traffic flow. In addition, the calibrated VT-Micro model is used to estimate the fuel consumption of CAVs and manually driven vehicles. The result shows that CAVs have better fuel economy than the human-driven vehicles, which is consistent with existing studies. The EcoSDM outperforms Enhanced-IDM and SDM in terms of fuel consumption. For the EcoSDM-equipped CAVs, the fuel saving benefit is greatest when a CAV is at the front of the platoon.

A modified multilevel k-way partitioning algorithm for trip-based road networks

In today’s world, the traffic volume on urban road networks is multiplying rapidly due to the heavy usage of vehicles and mobility on demand services. Migration of people towards urban areas result in increasing size and complexity of urban road networks. When handling such complex traffic systems, partitioning the road network into multiple sub-regions and managing the identified sub regions is a popular approach. In this paper, we propose an algorithm to identify sub-regions of a road network that exhibit homogeneous traffic flow patterns. In a stage wise manner, we model the road network graph by using taxi-trip data obtained on the selected region. Then, we apply the proposed modified multilevel kway partitioning algorithm to obtain optimal number of partitions from the developed road graph. An interesting feature of this algorithm is, resulting partitions are geographically connected and consists minimal interpartition trip flow. Our results show that the proposed algorithm outperforms state-of-the-art multilevel partitioning algorithms for tripbased road networks. By this research, we demonstrate the ability of road network partitioning using trip data while preserving the partition homogeneity and connectivity.

A new adaptive cruise control strategy and its stabilization effect on traffic flow

Connected and autonomous vehicle (CAV) technologies are likely to be gradually implemented over time. In this paper, an adaptive cruise control, named Smart Driver Model (SDM), is proposed to describe the autonomous vehicles flow. The stability criteria is proposed for SDM to judge the stability of homogeneous traffic flow. Numerical simulations were conducted to verify the results of the theoretical analysis. Single-lane vehicle dynamics in a traffic stream with connected and autonomous vehicles are simulated by varying model parameters. Simulation results are consistent with the results of linear stability analysis. As a result, a set of parameters is proposed to investigate the stabilization effect of the proposed model on homogeneous traffic flow considering realistic driving cycle and cut-in condition. By simulating a platoon with a lead vehicle which follows the Urban Dynamometer Driving Schedule (UDDS), we find out that the proposed model can stabilize the traffic flow with proposed parameters. The results from simulation and linear stability analysis show that SDM outperforms the IDM-ACC and the ACC proposed by Milanés and Shladover in terms of stabilization effect on homogeneous traffic flow. The simulation result shows that the SDM-equipped vehicles are able to stabilize the homogeneous traffic flow under cut-in condition.

Control design and stability analysis of homogeneous traffic flow under time delay: A new spacing policy

This paper details control design and stability analysis of homogeneous traffic flow by considering it as the interaction between inter-connected vehicular platoons. A third-order linear differential model is used to describe the longitudinal motion of each vehicle. As the lead vehicle of the whole traffic flow may be not available, the inter-platoon communication structure is assumed to be a bidirectional virtual leader following (BDVLF) topology. Both communication and parasitic delays are considered in the system modeling and control design. By employing an appropriate state transformation, the 3 N-order closed-loop dynamics are decoupled to N third-order dynamical equations. The cluster treatment characteristic root (CTCR) method is employed to perform the inter-platoon stability analysis. The intra-platoon communication structure is assumed to be general. Therefore, the eigenvalues of matrix H maybe complex which makes the stability analysis more intricate. By introducing a new decoupling approach and applying a centralized control for each vehicle in the platoon, the necessary conditions on control parameters satisfying intra-platoon stability are presented. The most important merit of this method compared to previous works, is that control parameters are independent of eigenvalues of matrix H. Several simulation studies are provided to show the effectiveness of the proposed approaches.

Route Guidance Strategy for Heterogeneous Traffic Flow in an Asymmetric Two-Route Scenario

During serious emergencies or congestion, it is very important to alleviate road traffic congestion and improve the road capacity to reduce casualties. Most of the advanced route guidance strategies have been developed for homogeneous traffic flows, to reduce traffic congestion and enhance the road capacity in a symmetric multi-route scenario. Information guidance strategies have rarely been considered for heterogeneous traffic flows, including different types of vehicles with variable velocities and sizes in an asymmetric multi-route traffic system. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for heterogeneous traffic flows including large vehicles and small vehicles, which considers the characteristics of different types of vehicles, such as, maximum speed, sizes and position, using real-time information feedback technology to guide traffic flow. Based on comparisons with the two previously proposed advanced strategies, the simulation results obtained in an asymmetric two-route traffic scenarios demonstrate that the proposed strategy improves the road capacity, balances traffic states on two routes, achieves better spatial distribution of traffic flow and enhances the stability of traffic flow about flux, average speed and the number of vehicles.