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Macroscopic traffic flow modeling is essential for describing and forecasting the characteristics of traffic flow. However, the classic Lighthill–Whitham–Richards (LWR) model only provides equilibrium values for steady‐state conditions and fails to capture common stochastic variabilities, which are a necessary component of accurate modeling of real‐time traffic management and control. In this paper, a stochastic LWR (SLWR) model that randomizes free‐flow speed is developed to account for the stochasticity incurred by the heterogeneity of drivers, while holding individual drivers' behavior constant. The SLWR model follows a conservation law of stochastic traffic density and flow and is formulated as a time‐dependent stochastic partial differential equation. The model is solved using a dynamically bi‐orthogonal (DyBO) method based on a spatial basis and stochastic basis. Various scenarios are simulated and compared with the Monte Carlo (MC) method, and the results show that the SLWR model can effectively describe dynamic traffic evolutions and reproduce some commonly observed traffic phenomena. Furthermore, the DyBO method shows significant computational advantages over the MC method. [ABSTRACT FROM AUTHOR]

In the conventional human driving environment, due to poor traffic information transmission and the inability to actively control vehicles, variable speed limits (VSLs) and ramp metering (RM) strategies often fail to achieve the desired results when dealing with the merging zone of an expressway under high traffic demand. To improve traffic efficiency, an integrated control method for traffic flow in the merging area of expressways is proposed by combining connected and autonomous vehicle (CAV) active lane change (LC) technology with traditional VSL and entrance RM strategies. This method uses an upgraded cell transmission model (CTM) to estimate the state of the mainline and ramp input traffic volume and then uses the genetic algorithm (GA) to solve for the optimal combination of the mainline speed limit, number of mainline vehicles changing lanes, and ramp regulation under maximized flow in the merging zone. This integrated control strategy incorporating VSL, LC, and RM (VSL-LC-RM) enables synergistic control of the mainline and ramp traffic entering the merging zone in time-space. Finally, simulation experiments are conducted with the mainline two-lane and on-ramp singlelane expressway merging zone scenarios. The results show that compared with the VSL strategy and the strategy incorporating only VSL and RM (VSL-RM), the proposed VSL-LC-RM strategy can enhance the regulation of traffic flow, improve the flow of merging bottlenecks, and make full use of the road space-time resources. [ABSTRACT FROM AUTHOR]

With rapid development of the urbanization, how to improve the traffic lights efficiency has become an urgent issue. The traditional traffic light control is a method that calculates a series of corresponding timing parameters by optimizing the cycle length. However, fixing sequence and duration of traffic lights is inefficient for dynamic traffic flow regulation. In order to solve the above problem, this study proposes a traffic light timing optimization scheme based on deep reinforcement learning (DRL). In this scheme, the traffic lights can output an appropriate phase according to the traffic flow state of each direction at the intersection and dynamically adjust the phase length. Specifically, we first adopt Proximal Policy Optimization (PPO) to improve the convergence speed of the model. Then, we elaborate the design of state, action, and reward, with the vehicle state defined by Discrete Traffic State Encoding (DTSE) method. Finally, we conduct experiments on real traffic data via the traffic simulation platform SUMO. The results show that, compared to the traditional timing control, the proposed scheme can effectively reduce the waiting time of vehicles and queue length in various traffic flow modes. [ABSTRACT FROM AUTHOR]

The study of traffic flow bifurcation control analysis is of great significance for understanding the essential evolution law of traffic flow, controlling traffic flow with practical means and alleviating traffic congestion. This paper describes the influence of lateral distance compensation in the process of lane change, and adjusts the traffic flow from the perspective of bifurcation control, which can capture the characteristics of traffic flow better, so as to describe the practical significance of the actual traffic phenomenon better. For example, the green ratio of traffic lights in the road, the planning and design of traffic signs, and the guidance of traffic condition prediction in ITS. In addition, the traffic flow is introduced and applied to the traffic model from the perspective of random function, and the bifurcation control is carried out according to the bifurcation behavior in traffic. That is, the bifurcation characteristics of the system are modified by the designed feedback controller, and the appearance of the equilibrium point of the system is adjusted to make it move forward, backward or disappear, so as to prevent or alleviate traffic congestion. There are few researches on bifurcation control of traffic flow model with lateral distance compensation. This paper introduces stochastic function based on lateral compensation model to study Hopf bifurcation phenomenon and Hopf bifurcation control. Firstly, the existence condition of Hopf bifurcation at the equilibrium point in the model is proved theoretically. Then, a feedback controller is designed to control the amplitudes of the Hopf bifurcation and the limit cycles formed by the Hopf bifurcation. Finally, the theoretical results are verified by numerical simulation. The research shows that by adjusting the control parameters in the feedback controller, the influence of boundary conditions on the stability of the traffic system is fully described, the effect of unstable focus and saddle point on the system is inhibited, and the traffic flow is slowed down. In addition, the unstable bifurcation points can be eliminated, and the amplitude of the limit cycle formed by Hopf bifurcation can be adjusted, so as to achieve the stability of the control system. • A new continuum model is proposed taking into account the lateral offset compensation. • Introducing the traffic flow into the traffic model from the perspective of the random function. • The designed feedback controller corrects the bifurcation characteristics of the system and adjusts the appearance of the balance point of the system to make it forward, backward or disappear, so as to prevent or reduce traffic jams. [ABSTRACT FROM AUTHOR]

Urban road dynamic impedance calculation is the important basis of dynamic traffic assignment and real-time traffic management and control scheme. The current impedance calculation is mostly based on BPR function, and the BPR function is derived from macroscopic statistical laws, in which the microscopic characteristics of traffic flow are insufficiently described. In order to more accurately express the change laws of traffic impedance at the microscopic level, a stochastic dynamic traffic assignment algorithm based on road impedance function is designed to analyze the time impedance of congested roads under random dynamic traffic assignment under different conditions of road network saturation. Compared with the current model, the comprehensiveness and portability are greatly improved. The results show that the impedance calculation error of this method is less than 10% when the load degree of the road is lower than 0.85, which proves that the method has good precision under unsaturated flow conditions. [ABSTRACT FROM AUTHOR]

We consider a strongly coupled ODE-PDE system representing moving bottlenecks immersed in vehicular traffic. The systems can be used to represent the effect of autonomous vehicles immersed in the bulk traffic. The PDE consists of a scalar conservation law modeling the traffic flow evolution and the ODE models the trajectory of a slow moving vehicle. The moving bottleneck influences the bulk traffic flow via a point flux constraint, which is given by an inequality on the flux at the slow vehicle position. We prove uniqueness and continuous dependence of solutions with respect to initial data of bounded variation. The proof is based on a new backward in time method established to capture the values of the norm of generalized tangent vectors at every time. The results are the first step to study control problems for traffic flow via the action of autonomous vehicles. [ABSTRACT FROM AUTHOR]

Variable speed limit (VSL) is becoming recognized as an effective way to improve traffic throughput and road safety. In particular, methods based on traffic state prediction exhibit promising potential to prevent future traffic congestion and collisions. However, field observations indicate that the traffic state prediction model results in nonnegligible error that impacts the next step decision making of VSL. Thus, this paper investigates how to eliminate this prediction error within a VSL environment. In this study, the traffic state prediction model is a second-order traffic flow model named METANET, while the VSL control is model predictive control (MPC) based, and the VSL decision is discrete optimized choice. A simplified version of the switching mode stochastic cell transmission model (SCTM) is integrated with the METANET model to eliminate the prediction error. The performance of the proposed method is assessed using field data from a VSL pilot test in Edmonton, Canada, and is compared with the prediction results of the baseline METANET model during the road test. The results show that during the most congested period the proposed SCTM-METANET model significantly improves the prediction accuracy of regular METANET model. [ABSTRACT FROM AUTHOR]

In this work, moving synchronized flow patterns (MSP) in empirical city traffic at signals have been observed which was predicted by Kerner (2013, 2014). The single vehicle data has been obtained through aerial observations. Based on this microscopic data, we have found trajectories for all vehicles together with vehicle speeds as functions of time and space. This has allowed us to find empirical MSPs in oversaturated city traffic as well as to perform microscopic analysis, that revealed the following empirical spatiotemporal features of MSPs: (i) MSPs emerge upstream of the queue at the signal and then they can propagate through the complete road section, (ii) merging of several MSPs into a single MSP, (iii) dissolving MSPs and (iv) spontaneous emerging of MSPs faraway upstream of the signal, (v) spontaneous emerging of moving queue within an MSP that is far away upstream of the signal. As a base for this work, we used an unmanned aerial vehicle (UAV) to record videos of inner city traffic situations and supervised tracking methods to gather the vehicle trajectories. [ABSTRACT FROM AUTHOR]

• Propose a cooperative signal-free intersection control framework under V2X communications. • Proposed framework integrates virtual platooning control and traffic flow regulation. • Virtual platooning controller mitigates effects of parametric inaccuracies and unparameterized disturbances. • Virtual platooning controller guarantees string stability. • Traffic flow regulation alleviates traffic spillbacks and travel delays. The emerging technologies of connectivity and automation enable the potential for signal-free intersection control. In this context, virtual platooning is posited to be an innovative, decentralized control strategy that maps two-dimensional vehicle movements onto a one-dimension virtual platoon to enable intersection operations. However, the effectiveness of virtual platooning-based control can be limited or degraded by parametric inaccuracies and unparameterized disturbances in vehicle dynamics, heavy traffic congestion, and/or uncoordinated platoons in multi-lane intersections. To explicitly address these limitations, this study proposes a hybrid cooperative intersection control framework consisting of microscopic-level virtual platooning control and macroscopic-level traffic flow regulation for traffic environments with connected autonomous vehicles. In virtual platooning control, vehicles approaching an intersection are organized into coordinated independent virtual platoons to avoid potential conflicts triggered by platoon formation changes. Through coordination, vehicles in a platoon are grouped into compatible passing sets to maintain desired safe spacing when proceeding through the intersection. We propose a distributed adaptive sliding mode controller (DASMC) which uses the backstepping control method and model reference adaptive control method to address parametric inaccuracies, and the sliding mode control method to consistently suppress the negative effects of the unparameterized disturbances. Each vehicle approaching the intersection utilizes the kinematic information from neighboring vehicles to implement the DASMC in a distributed manner such that vehicles within the same virtual platoon can achieve consensus safely. However, virtual platooning control cannot preclude excessive traffic from approaching the intersection, which can cause undesired spillbacks and degrade intersection control performance. To address this issue, traffic flow regulation is integrated with the virtual platooning control using an iterative feedback loop mechanism. In each iteration of the iterative feedback loop, a constrained finite-time optimal control (CFTOC) problem is solved to determine the optimal input flow permitted to proceed through the intersection, and the virtual platooning control provides feedback on the queue status to the CFTOC to initiate the next iteration. The effectiveness of the proposed intersection control framework is evaluated through numerical experiments. The results indicate that the proposed virtual platooning DASMC controller can mitigate the effects of parametric inaccuracies and unparameterized disturbances to achieve consensus for approaching vehicles, as well as guarantee string stability. Further, the proposed framework can alleviate traffic spillbacks and travel delays effectively through traffic flow regulation. [ABSTRACT FROM AUTHOR]

This research aims at developing a system of real-time simulation-based dynamic traffic model under mixed traffic flow conditions. The system consists of two layers, namely, simulation layer and real-time control layer. The system is implemented based on rolling horizon approach, which is advanced for each stage; thus real-time data can be incorporated within the framework. In order to predict normative, as well as predictive, information, a simulation-based dynamic traffic assignment model is employed within each stage. Empirical data for a real city network, such as flows from vehicle detectors, are used to validate the model in a real-time environment. The values of mean absolute percentage error and root-mean-squared percentage error are within 15%, and the results show promising agreements between observed and simulated flows. [ABSTRACT FROM AUTHOR]

Abstract: The continuously increasing daily traffic congestions on motorway networks around the world call for innovative control measures that would drastically improve the current traffic conditions. Mainstream traffic flow control (MTFC) is proposed as a novel and efficient motorway traffic management tool, and its possible implementation and principal impact on traffic flow efficiency is analysed. Variable speed limits, suitably operated and enforced, is considered as one (out of several possible) way(s) for MTFC realisation, either as a stand-alone measure or in combination with ramp metering. A previously developed, computationally efficient software tool for optimal integrated motorway network traffic control including MTFC is applied to a large-scale motorway ring-road. It is demonstrated via several investigated control scenarios that traffic flow can be substantially improved via MTFC with or without integration with coordinated ramp metering actions. [Copyright &y& Elsevier]

Traffic-responsive plan selection (TRPS) control is one of the largely underutilized control features in National Electircal Manufacturers Association traffic controllers. This control feature allows the controller to change timing plans in arterials or networks in response to changes in traffic patterns automatically, and can therefore result in better performance of the signal system. However, there is limited number of studies that document the procedure of TRPS configuration. The authors have previously published general guidelines on TRPS system setup and configuration, laying out a comprehensive approach that assumes general traffic patterns, a standardized arterial network, and some generic system detector locations. This paper fills a significant gap in literature by providing an illustrative procedure of actual field implementation of a TRPS system in Mexia, Texas. The paper demonstrates the configuration methodology on an arterial network that does not conform to the standardized guidelines. This implementation resulted in up to 75% reduction in delay and up to 33% increase in the lower arterial speed. In this paper, the authors provide some findings and insights into the TRPS configuration process, highlighting some solutions for potential field problems that the engineer might face when configuring a TRPS control system. [ABSTRACT FROM AUTHOR]

An urban traffic network of signalised intersections can be suitably modelled as a discrete event system, in which the traffic light alternations are described by means of timed coloured Petri nets (TCPNs). A module of basic traffic TCPN model with a signal timing plan for a day is successfully constructed. The traffic operations are ruled by the control logic of TCPN and an analysis method using place invariant is verified. From the basic TCPN model, some of the complicated traffic signal models will be easily obtained. Moreover, a real-world supervisor of the urban traffic light system is implemented by the new methodology. Finally, an urban traffic light control system with five intersections is realised. Also, the performance of the supervisor of the urban traffic light system can be confirmed by the simulation results. [ABSTRACT FROM AUTHOR]

Abstract: Multi-agent systems allow the simulation of complex phenomena that cannot easily be described analytically. Multi-agent approaches are often based on coordinating agents whose actions and interactions are related to the emergence of the phenomenon to be simulated. In this article, we focus on road traffic simulation, specifically the design of a road traffic simulation tool able to deal realistically with road junctions. We propose a multi-agent behavioral model based on (i) the opportunistic individual behaviors that describe the norm violation and (ii) the anticipatory individual abilities of simulated drivers that allow critical situations to be detected. Our proposition has been validated for different traffic scenarios. Specifically, we simulated the traffic in a real intersection and then compared the simulated traffic flow with the real flow to highlight the relevance of our approach. [Copyright &y& Elsevier]

This paper investigates traffic dynamics of two-lane mixed traffic flow system composed of cars and buses, which are characterized by different lengths and different maximum velocities. Four lane changing regulations are studied, which reveals effect of lane changing ban, symmetric and asymmetric lane changing rules on traffic flow characteristics (flow rate, carry capability, lane changing frequency, and lane usage). We expect that our results could be useful for traffic management. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we use a two-lane CA model to investigate the effect of a bus stop between two neighbouring intersections on the capacity of the bus. Both the case of a bus stop with a special stopping lane and that of one without are considered. The capacity versus the distance () between the stop and the upstream (downstream) intersection is studied, with respect to the entering probability and the traffic light cycle . It is found that a bus stop near an intersection can act as a bottleneck and cause a drop in the capacity when the (or ) is below a critical point (or ). However, the situation when the stop is located near the downstream intersection is worse than that of the upstream one. Furthermore, the simulation results show that the negative effect varies with the increase of the cycle time and the capacity can be maximized by adjusting . Comparisons between the two cases suggest that the stopping lane can improve the capacity to some extent. These results mean that the capacity can be exploited by changing the position of the bus stop or the cycle time, and adding a stopping lane if necessary. These findings may be useful in offering scientific guidance for the management and design of traffic networks. [Copyright &y& Elsevier]

Abstract: The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights in traffic dynamics in the temporal domain, this paper explored traffic patterns in higher-dimensional state spaces, where we attempted to map the one-dimensional traffic series into appropriate multidimensional spaces by Takens’ algorithm. After such a state space reconstruction, we then made use of the largest Lyapunov exponent to depict the rate of expansion or contraction of traffic state trajectories in the reconstructed spaces. The correlation dimension was further estimated to examine if the traffic state trajectories exhibited chaotic-like or stochastic-like motions. An empirical study using flow, speed, and occupancy time-series data as well as the speed-flow, speed-occupancy, and flow-occupancy paired data collected from dual-loop detectors on a freeway of Taiwan was conducted. The numerical results revealed that different nonlinear traffic patterns could emerge depending on the observed time-scale, history data and time-of-day. In addition, with consideration of sequential order and spatiotemporal features, more information about traffic dynamical evolution was extracted. [Copyright &y& Elsevier]

Abstract: In this work, we apply the iterative learning control approach to address the traffic density control problem in a macroscopic level freeway environment with ramp metering. The traffic density control problem is first formulated into an output tracking and disturbance rejection problem. Through rigorous analysis, it is shown that the iterative learning control method can effectively deal with this class of control problem and greatly improve the traffic response. Next, the iterative learning control is combined with error feedback in a complementary modular manner to achieve the output tracking and system robustness. The effectiveness of the new approach is further verified through case studies with intensive simulations. [Copyright &y& Elsevier]

Abstract: We study the congestion on a homogeneous roadway with open boundaries. Three different phases are identified. Both numerical and analytical results are presented. For stationary boundaries, three different flow can be associated with a single density on the fundamental diagram. When the congestion is characterized by numerous jams, the system is homogeneous and the traffic flow is low. When the system is dominate by a single jam, the time trajectory traces out finite cycles and a higher traffic flow can be supported. If the cycles fill up a two-dimensional area, the traffic flow remains constant as the density changes; if the cycles collapse into a one-dimensional loop, a much higher traffic flow can be achieved. We also discuss the effects of dynamical boundaries. [Copyright &y& Elsevier]

Abstract: Two-dimensional cellular automaton model has been broadly researched for traffic flow, as it reveals the main characteristics of the traffic networks in cities. Based on the BML models, a first-order phase transition occurs between the low-density moving phase in which all cars move at maximal speed and the high-density jammed phase in which all cars are stopped. However, it is not a physical result of a realistic system. We propose a new traffic rule in a two-dimensional traffic flow model containing road sections, which reflects that a car cannot enter into a road crossing if the road section in front of the crossing is occupied by another car. The simulation results reveal a second-order phase transition that separates the free flow phase from the jammed phase. In this way the system will not be entirely jammed (“don’t block the box” as in New York City). [Copyright &y& Elsevier]

Abstract: This paper describes and discusses the possibilities of steering the transportation planning process in the face of bounded rationality and unbounded uncertainty: (a) through the introduction of the concept of ‘systemicity’; (b) by expanding the spectrum of the existing planning paradigm currently in use; (c) by reducing complexity through the application of tests of adequacy, dependency, suitability, and adaptability; (d) through the introduction of soft systems thinking; and (e) by using ‘abductive’ in addition to deductive and inductive inferencing. It is concluded that the application of these strategies, adjustments, and tests to the existing planning procedure will hopefully enrich and strengthen our planning effort and make it more robust. [Copyright &y& Elsevier]

Abstract: This paper deals with the construction of fuzzy costs and more particularly with their meaning in traffic assignment models based on fuzzy logic tools. The idea is to separate different possible semantics, namely imprecision, uncertainty and grade of preference. The classically encountered approach is based on the gathering of those different meanings into a single fuzzy cost. It is demonstrated in this paper that it may sometimes lead to inconsistencies. We propose another approach, based on decision theory with possibility measurement of uncertainty. [Copyright &y& Elsevier]

Abstract: The fuzzy version of group model of traffic flow in street networks is presented. At first definitions of vehicles groups and its elementary transformations are introduced. Then the generic transformer of vehicle groups at an entrance of intersection is derived and network evaluation performed. The introduction of the fuzzy group definition as fuzzy set of similar vehicle groups made possible to extend results have obtained for crisp model to fuzzy one. Vehicle group transformations were generalized to fuzzy environment by law of extension and new formulas for delay were derived. Remarks concerning delay defuzzyfication and advantages of fuzzy group model over crisp one ended the paper. [Copyright &y& Elsevier]

Urban road noise has always been an important environmental problem for man from ancient history. But despite the fact proven by measurements and calculations that road traffic is the main source of noise in urban areas, citizens have the tendency to accept the situation as part of modern way of life and as a "necessary evil". This paper compares the results of noise measurements and the noise related complaints of the citizens from Timisoara. [ABSTRACT FROM AUTHOR]

The author comments on the traffic problem in different countries and offers solutions to such problem. He considers innovative and updated traffic planning as one of the solutions to enhance traffic flow. He stresses the importance of better driver education before licenses are given and much stricter enforcement of traffic laws. He also mentions the traffic he experienced in Bangkok, Thailand, Manila, Philippines, and Sydney, New South Wales.