Mean Velocity Feedback Research Articles

Freeway traffic flow cellular automata model based on mean velocity feedback

Making full use of real-time feedback traffic information to guide road traffic is one of the hot spots in the field of intelligent transportation system, which has practical significance for improving travel efficiency and reducing congestion. This paper proposes a new average speed feedback strategy based on real-time information, and uses it to improve the MCD model. The fundamental diagram, space–time diagram and flow interruption effect diagram obtained by simulation show that the results are consistent with the three-phase flow theory. It is found that in the free flow phase, the mean velocity feedback enables vehicles to adjust the velocity, accelerate the dissipation of the deceleration wave and maintain the stability of the traffic flow. In contrast, in the synchronized flow phase, the mean velocity feedback strategy keeps the traffic flow constant, reduces the velocity disturbance caused by the drivers’ own factors and improves the road operation efficiency.

Impacts of bounded rationality on trip cost in a two-route traffic network

The driver’s bounded rationality (BR) widely exists and has significant impacts on traffic system, but little effort has been made to explore the impacts of BR on each vehicle’s trip cost in a two-route traffic network. In this paper, we incorporate BR into the mean velocity feedback strategy (MVFS) and the number of vehicles feedback strategy (NVFS) to study each vehicle’s trip cost in a two-route traffic network. The numerical results indicate that BR has some effects on each vehicle’s trip cost and that the effects are related to the initial time headway at the origin. The results can help us to better understand the impacts of BR on each vehicle’s route choice behavior in a traffic network.

Feedback strategy with delay in a two-route traffic network

Most feedback strategies (FSs) have feedback delay, but little effort has been made to study this topic. In this paper, we incorporate the feedback delay into the mean velocity feedback strategy (MVFS) and vehicle number feedback strategy (VNFS), then propose two FSs to study the impacts of delay on each vehicle’s trip cost and the total cost in a two-route network. The numerical results indicate that the delay has some impacts on each vehicle’s trip cost and the system’s total cost and that the impacts are related to each vehicle’s initial time headway at the origin. The results can guide each driver to adjust his/her route choice at the origin when the initial time headway is very high.

Analysis of the traffic running cost in a two-route system with feedback strategy

Abstract In this paper, we apply the FVD (full velocity difference) model to study the influences of MVFS (mean velocity feedback strategy) and NVFS (the number of vehicles feedback strategy) on each vehicle’s running cost and each route’s total cost in a two-route system from the numerical perspective. The numerical results illustrate that MFVS and NVFS have significant effects on each vehicle’s running cost and each route’s total cost, and that the impacts, each vehicle’s running cost and each route’s total cost are related to the gap of each vehicle’s departure time at the origin.

Route guidance strategies revisited: Comparison and evaluation in an asymmetric two-route traffic network

To alleviate traffic congestion, a variety of route guidance strategies have been proposed for intelligent transportation systems. A number of strategies are introduced and investigated on a symmetric two-route traffic network over the past decade. To evaluate the strategies in a more general scenario, this paper conducts eight prevalent strategies on an asymmetric two-route traffic network with different slowdown behaviors on alternative routes. The results show that only mean velocity feedback strategy (MVFS) is able to equalize travel time, i.e. approximate user optimality (UO); while the others fail due to incapability of establishing relations between the feedback parameters and travel time. The paper helps better understand these strategies, and suggests MVFS if the authority intends to achieve user optimality.

A weighted mean velocity feedback strategy in intelligent two-route traffic systems

Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly. Based on the more practical symmetrical two-route scenario with one entrance and one exit, an improved weighted mean velocity feedback strategy (WMVFS) is proposed, which is not sensitive to the precision of global position system (GPS) devices. The applicability of WMVFS to different weight factors, aggressive probabilities, densities of dynamic vehicles, and different two-route scenarios (symmetrical scenario and asymmetrical scenario with a speed limit bottleneck) is analyzed. Results show that WMVFS achieves the best performance compared with three other information feedback strategies when considering the traffic flux and stability.

Application of adaptive weights to intelligent information systems: An intelligent transportation system as a case study

Optimization of information feedback technologies is very important for many socioeconomic systems such as stock markets and traffic systems aiming to make full use of resources. In this paper, we propose an adaptive weight method, which has potential value for a variety of information processing contexts. We apply this adaptive weight method to an intelligent transportation system (ITS) as a case study. A feedback strategy named Improved Congestion Coefficient Feedback Strategy (ICCFS) is introduced based on a two-route scenario in which dynamic information can be generated and displayed on the roadside in order to enable drivers to make an informed route decision. Our model incorporates the effects of adaptability into the cellular automaton models of traffic flow. Simulations demonstrate that adopting this optimal information feedback strategy provides a high efficiency in controlling spatial distribution of traffic patterns when compared with the three other information feedback strategies, i.e., Travel Time Feedback Strategy (TTFS), Mean Velocity Feedback Strategy (MVFS) and Congestion Coefficient Feedback Strategy (CCFS).

EFFECTS OF VEHICLE NUMBER FEEDBACK IN MULTI-ROUTE INTELLIGENT TRAFFIC SYSTEMS

We first study dynamics of traffic flow with real-time information and the influence of a new feedback strategy named Vehicle Number Feedback Strategy (VNFS) in a multi-route scenario in which dynamic information can be generated and displayed on the board (the board refers to a variable message sign where information on the routes is displayed) to guide road users to make a choice. In a multi-route scenario, our model incorporates the effects of adaptability into the cellular automaton models of traffic flow and simulation results adopting vehicle number feedback strategy have demonstrated high efficiency in controlling spatial distribution of traffic patterns compared with the other three information feedback strategies, i.e. Travel Time Feedback Strategy (TTFS), Mean Velocity Feedback Strategy (MVFS) and Congestion Coefficient Feedback Strategy (CCFS). We also discuss the influence of expected arrival rate (Vp) at the entrance on the average flux of each route, and we find that the flux adopting VNFS is always the largest at each Vp value among these four feedback strategies.

Day-To-Day Route Choice Decision Simulation Based on Dynamic Feedback Information

In reality, the individual's day-to-day route choice behavior is a long-time evolution process, and travelers choose their traveling routes according to the combination of historical experience and real-time traffic information. Considering two classes of users, one equipped with advanced traveler information systems (ATIS) and the other without, this paper investigates the travel efficiency under two different information feedback strategies, namely, travel time feedback strategy and mean velocity feedback strategy. The simulation results given by the cellular automaton model show that the more users rely on historical experience, the quicker the system evolves to the equilibrium. To all users, the travel efficiency decreases with travel demand and firstly increases then decreases with the dependent degree to historical experience. However, as far as the ATIS market penetration rate is concerned, the users' travel efficiency under two feedback strategies exhibits different trends. The equipped travelers have shorter travel time, particularly under mean velocity feedback strategy. In addition, the difference of travel efficiencies between two classes of users decreases as days evolve.

Microscopic simulation of multi-lane traffic under dynamic tolling and information feedback

To investigate drivers’ lane-changing behavior under different information feedback strategies, a microscopic traffic simulation based on the cellular automaton model was made on the typical freeway with a regular lane and a high-occupancy one. A new dynamic tolling scheme in terms of the real-time traffic condition on the high-occupancy lane was further designed to enhance the whole freeway’s flow throughput. The results show that the mean velocity feedback strategy is generally more efficient than the travel time feedback strategy in correctly guiding drivers’ lane choice behavior. Specifically, the toll level, lane-changing rate and freeway’s throughput and congestion coefficient induced by the travel time feedback strategy oscillate with larger amplitude and longer period. In addition, the dynamic tolling scheme can make the high-occupancy lane less congested and maximize the freeway’s throughput when the regular-lane inflow rate is larger than 0.45.

Effects of information feedback on an asymmetrical two-route scenario

In traffic system, a reasonable information feedback can improve road capacity. In this paper, we investigate an asymmetrical two-route scenario in which dynamic information can be generated and displayed on the board to guide drivers. Two improved feedbacks (i.e. improved mean velocity feedback and improved congestion coefficient feedback) are introduced. Simulations show that the average cost is dependent on the vehicle arrival rate and there exists a critical the dynamic vehicles ratio corresponding to the maximum flux. We find that improved con-gestion coefficient can better enhance the system capacity than that of improved mean velocity feedback.

Information Feedback Strategies in a Signal Controlled Network with Overlapped Routes

We investigate the effects of four different information feedback strategies on the dynamics of traffic, travelers' route choice and the resultant system performance in a signal controlled network with overlapped routes. Simulation results given by the cellular automaton model show that the system purpose-based mean velocity feedback strategy and the congestion coefficient feedback strategy have more advantages in improving network utilization efficiency and reducing travelers' travel times. The travel time feedback strategy and the individual purposed-based mean velocity feedback strategy behave slightly better to ensure user equity.

Comparative studies on information feedback strategies in traffic networks with overlaping routes

Intelligent traffic systems can help road users make reasonable route choice by providing them real-time traffic information，thus alleviate congestion. Considering the existence of overlapping between routes， this paper applies the cellular automaton model to simulate and investigate the route choice behavior under two information service strategies， namely travel time feedback strategy and mean velocity feedback strategy. Our simulation results indicate that the mean velocity feedback strategy can reduce the route travel time more efficiently than the time feedback strategy， particularly in longer networks with very short or very long overlapping segments. Its advantage in improving the network utilization efficiency decreases with the route length and drops first and rises afterwards with the length of overlapping part.

Broadband Active Vibration Control of a Rectangular Flexible Wall of an Empty and a Water-filled Tank

Broadband active vibration control of a rectangular plate representing a flexible wall of a thick Plexiglas container is experimentally investigated, for both empty and water-filled tanks, using five piezoelectric patches as control actuators. Preliminary dynamical analyses are carried out on the system in order to verify the influence of different water levels and different environment conditions (in particular, temperatures) on the system dynamics. Active vibration control is then experimentally applied to the plate with a single input—single output approach in the presence of broadband primary disturbance between 0 and 400 Hz, testing both filtered-x least mean square adaptive feedforward control and direct velocity feedback control. The time delay through the disturbance and control paths is measured.

On The Numerical Modeling Of Buoyancy-dominated Turbulent Fires By Using Large Eddy Simulation

This study concerns the modeling of three characteristic buoyancy-dominated turbulent diffusion flames such as pool-like, vertical and interaction between pool-like and vertical wall fires. Controlling mechanisms of three dimensional flow, combustion, soot production and radiation are coupled with a Large Eddy Simulation (LES). An EddyBreak-Up concept which accounts for the interaction between combustion and turbulence, is implemented in LES. The numerical models have been validated using experimental data from three turbulent diffusion flames. The predicted mean temperature, velocity and total heat feedback from the high temperature gases in the flame to the wall surface follow closely to the experimental data. Moreover, it is found that LES successfully predicted the important features of highly oscillating buoyancy-controlled pool-like fire (recirculation zone, narrowing and broadening of the flame). While, the standard Smagorinsky sub-grid scale model should be improved to predict the variation of the fluctuating velocity and temperature for the vertical wall fires.