Traffic Flow Behavior Research Articles

Simulation study of traffic car accidents in single-lane highway

In this paper we numerically study the probability Pac of the occurrence of car accidents in the extended Nagel–Schreckenberg (NS) model in the case of mixture of fast (Vmax1=5) and slow vehicles (Vmax2=1) by taking also to the risky overtaking of fast vehicles. In comparison with previous existing models, we find that accidents can occur in the free traffic phase and/or congested one depending on the overtaking rate of fast vehicles. The effect of evacuation of damaged vehicles from the road with probabilities Pevf and Pevs of fast and slow vehicles respectively on the traffic flow behavior is also computed.

Cellular automata traffic flow behavior at the intersection of two roads

The control of vehicles in urban traffic is a requirement to maximize the flow and to ensure the safety of traffic. Using the cellular automata Nagel–Schreckenberg (NaSch) model within a parallel dynamic update, we studied the effect of the intersection of two symmetrical roads, with typical periodic boundary conditions. It is found that the fundamental diagram depends strongly on the probability P of priority and the probability P1 of changing the road at the intersection. Beside the free flow, the platoon and the jamming phases, the fundamental diagram exhibits a fourth new phase occurring for any value of P ≠ 0.5, which disappears gradually as one increases the probability P, and disappears completely for P = 0.5. The effects of the braking probability Pb on the fundamental diagram and space time structures are also computed for different values of maximal velocities.

Traffic matrix estimation: Advanced‐Tomogravity method based on a precise gravity model

SummaryTraffic matrix (TM) is extremely important in many networking operations. This paper proposes a novel approach of TM estimation in large‐scale IP networks, termed as Advanced‐Tomogravity method, which is based on a precise gravity model and the tomography method. First, the precise gravity model is proposed on the basis of the existing generalized gravity model by introducing a relativity factor vector parameter, which defines the relativity between the solution of the existing generalized gravity model and its real TM. The solution obtained from this precise gravity model is then refined by the basic model of the tomography method. By mathematical analysis, we give the explicit expression of the relativity factor vector parameter in the proposed precise gravity model by the Moore–Penrose inverse and the minimum‐norm least‐square solution. The vector parameter is subsequently determined with the aid of small amount of historical real data of TM. A general algorithm of the proposed approach is therefore designed. Finally, our approach is validated by simulation using the real data of the Abilene Network. The simulation results indicate that it reduces the relative errors to less than one‐half, better tracks not only the dynamic fluctuations but also the overall mean behavior of traffic flow. Copyright © 2014 John Wiley & Sons, Ltd.

A control method applied to mixed traffic flow for the coupled-map car-following model

In light of previous work [Phys. Rev. E 60 4000 (1999)], a modified coupled-map car-following model is proposed by considering the headways of two successive vehicles in front of a considered vehicle described by the optimal velocity function. The non-jam conditions are given on the basis of control theory. Through simulation, we find that our model can exhibit a better effect as p = 0.65, which is a parameter in the optimal velocity function. The control scheme, which was proposed by Zhao and Gao, is introduced into the modified model and the feedback gain range is determined. In addition, a modified control method is applied to a mixed traffic system that consists of two types of vehicle. The range of gains is also obtained by theoretical analysis. Comparisons between our method and that of Zhao and Gao are carried out, and the corresponding numerical simulation results demonstrate that the temporal behavior of traffic flow obtained using our method is better than that proposed by Zhao and Gao in mixed traffic systems.

Automated Driving, Traffic Flow Efficiency, and Human Factors

Automation may be assumed to have a beneficial impact on traffic flow efficiency. However, the relationship between automation and traffic flow efficiency is complex because behavior of road users influences this efficiency as well. This paper reviews what is known about the influence of automation on traffic flow efficiency and behavior of road users, formulates a theoretical framework, and identifies future research needs. It is concluded that automation can be assumed to have an influence on traffic flow efficiency and on the behavior of road users. The research has shortcomings, and in this context directions are formulated for future scientific research on automation in relation to traffic flow efficiency and human behavior.

On traffic flow model with weighted look-ahead potential

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rule of traffic system. On the basis of cellular automata model and traffic flow model with look-ahead potential, in this paper, a novel traffic flow model with weighted look-ahead potential is presented. By introducing the weighting coefficient into the look-ahead potential and endowing the potential of vehicle closer to itself with a greater weight, the modeling process is more suitable for the driver's random decision-making process which is based on the vehicle and enviroment situation in front of him in actual traffic. Complex high-density traffic behavior is reproduced by numerical simulations. The simulation results show that the weighting coefficient has an obvious effect on high-density traffic flux, and the weighted model is more conducive to keeping high traffic flux and road capacity while maintaining a high traffic density.

Fractal behavior in the headway fluctuation simulated by the NaSch model

The fractal behavior of traffic flow is studied by the adaptive fractal analysis method on the basis of the vehicle headway time series, which are obtained from the numerical simulation of the NaSch model. We find that the vehicle headway time series has a fractal behavior that is similar to the standard Brownian motion (BM) over a wide range of scales when the density is low. As the density increases well-defined sharp spectral peaks, corresponding to the stop-and-go waves, appear while the scale range showing BM-like behavior rapidly shrinks. In the high density regime, a new type of fractal behavior with long-range correlations appears, accompanying the worsening of traffic congestions. The underlying dynamics of traffic flow is analyzed, and some meaningful results are obtained.

Traffic Incident Detection Based on the Grid Model

Highway accidents significantly impact normal traffic flow. Consequently, automatic detection of abnormal traffic events has gradually attracted the attention of researchers interested in intelligent transportation system. This work presents a vision-based approach for automatic traffic congestion and incident detection. The proposed approach involves extracting entropy-based features to create a grid model that simulates dynamic traffic flow behavior. When an unusual event occurs in the lane of the vehicle employing the system, the system can immediately detect it and issue signals to approaching vehicles to prevent accidents. Experiments conducted using various simulation results clearly demonstrate the validity and effectiveness of the proposed approach for managing traffic congestion and detecting incidents.

Passenger Car Units at Different Levels of Service for Capacity Analysis of Multilane Interurban Highways in India

Passenger car units (PCU) of different types of vehicles are required to convert a mixed traffic stream into a homogeneous equivalent, and thereby to express the mixed traffic flow in terms of equivalent number of passenger cars. Earlier studies have reported that PCU for a vehicle is dynamic in nature and changes with traffic volume and proportional share of a vehicle type in the traffic stream. The present study provides PCU values for different types of vehicles typically found on interurban multilane highways in India at different levels of service (LOS). Traffic simulation model VISSIM is used to generate the traffic flow and speed data for conditions that are difficult to obtain from field observations. Important VISSIM parameters are first calibrated to reflect mixed traffic flow behavior and then the software is used to draw the speed-volume relationships for cars and one of the remaining four categories of vehicles in the traffic stream. The proportion of second category of the vehicle was also varied to observe its effects on PCU values. Finally, PCU values are suggested for different type of vehicles at different LOS and for different traffic composition on four-lane and six-lane divided highways.

Simulation Research on On-ramp Traffic Flow Based on Cellular Automata

In order to analyze characteristic of on-ramp traffic flow, a new traffic model of on-ramp system based on the cellular automaton traffic model have been built according to the behavior of changing lane form point of safe distance, and on that basis, four different lane changing rules were put forward, and Affection of four kinds of lane changing rules on-ramp system were analyzed, in the meanwhile, the complex behavior of traffic flow of on-ramp system were discuss. Finally, characteristic of on-ramp traffic flow based on the cellular automaton traffic have been carried out to simulate in order to testify validity, objectivity and applicability by using calculating and comparing analysis. The simulation results show that the lane-changing behavior has a huge effect on the flow of ramp model, and the behavior without considering safe-distance could make the flow of on-ramp section reach the highest point, while the flow of upstream and downstream sections of main road could be obviously suppressed.

A Neural Network Model for Driver’s Lane-Changing Trajectory Prediction in Urban Traffic Flow

The neural network may learn and incorporate the uncertainties to predict the driver’s lane-changing behavior more accurately. In this paper, we will discuss in detail the effectiveness of Back-Propagation (BP) neural network for prediction of lane-changing trajectory based on the past vehicle data and compare the results between BP neural network model and Elman Network model in terms of the training time and accuracy. Driving simulator data and NGSIM data were processed by a smooth method and then used to validate the availability of the model. The test results indicate that BP neural network might be an accurate prediction of driver’s lane-changing behavior in urban traffic flow. The objective of this paper is to show the usefulness of BP neural network in prediction of lane-changing process and confirm that the vehicle trajectory is influenced previously by the collected data.

Traffic Management Effects of Variable Speed Limit System on a German Autobahn

An empirical study of the traffic flow effects of a variable speed limit (VSL) system on a three-lane German autobahn is presented. The study integrated loop detector data and VSL and driver information provided by overhead dynamic message signs along a 16.3-km section of Autobahn A99 near Munich, Germany. Unlike most VSL deployments, the data sources allowed for a with-and-without analysis to reflect traffic flow and driver behavior in the presence and in the absence of the VSL system. In addition to speed, the primary features of interest were the spatial–temporal extent of the queue (congestion), flow changes caused by identified bottlenecks, the distribution of flow across lanes, the percentage of trucks per lane, and the flow homogeneity between lanes. The analysis recorded bottleneck flow reductions that were balanced across all lanes with an active VSL system. With an inactive VSL system, the flow reductions were slightly lower and occurred primarily in the center and shoulder lanes; there was a small flow increase in the median lane. Further examination indicated that the gain in homogeneity and safety with the system in place was at the cost of capacity. Possible reasons that might explain the differences between the scenarios with and without the VSL system had their basis in the ban against passing by trucks, which was in effect when the driver information system was active.

Analytical Prediction of Self-Organized Traffic Jams as a Function of Increasing ACC Penetration

Self-organizing traffic jams are known to occur in medium-to-high density traffic flows, and it is suspected that adaptive cruise control (ACC) may affect their onset in mixed human-ACC traffic. Unfortunately, closed-form solutions that predict the occurrence of these jams in mixed human-ACC traffic do not exist. In this paper, both human and ACC driving behaviors are modeled using the General Motors fourth car-following model and are distinguished by using different model parameter values. A closed-form solution that explains the impact of ACC on congestion due to the formation of self-organized traffic jams (or “phantom” jams) is presented. The solution approach utilizes the master equation for modeling the self-organizing behavior of traffic flow at a mesoscopic scale and the General Motors fourth car-following model for describing the driver behavior at the microscopic scale. It is found that, although the introduction of ACC-enabled vehicles into the traffic stream may produce higher traffic flows, it also results in disproportionately higher susceptibility of the traffic flow to congestion.

Stochastic Modeling of Traffic Flow Breakdown Phenomenon: Application to Predicting Travel Time Reliability

This paper presents a modeling approach in generating random flow breakdowns on congested freeways and capturing subsequent wave propagation among heterogeneous drivers. The approach is intended for predicting travel time variability caused by such stochastic phenomena. It is assumed that breakdown may occur at different flow levels with some probability and would sustain for a random duration. This is modeled at the microscopic level by considering speed changes that are initiated by a leading vehicle and propagated by the following vehicles with correlated-distributed behavioral parameters. Numerical results from a Monte Carlo simulation demonstrate that the proposed stochastic modeling approach produces a realistic macroscopic traffic flow behavior and can be used to generate travel time distributions.

A microscopic lane changing process model for multilane traffic

In previous simulations lane-changing behavior is usually assumed as an instantaneous action. However, in real traffic, lane changing is a continuing process which can seriously affect the following cars. In this paper, a microscopic lane-changing process (LCP) model is clearly described. A new idea of simplifying the lane-changing process to the car-following framework is presented by controlling fictitious cars. To verify the model, the results of flow, lane-changing frequency, and single-car velocity are extracted from experimental observations and are compared with corresponding simulation. It is found that the LCP model agrees well with actual traffic flow and lane-changing behaviors may induce a 12%–18% reduction of traffic flow. The results also reflect that most of the drivers on the two roads in a city are conservative but not aggressive to change lanes. Investigation of lane-changing frequency shows that the largest lane-changing frequency occurs at a medium density range from 15vehskm−1lane−1 to 35vehskm−1lane−1. It also implies that the lane-changing process might strengthen velocity variation at medium density and weaken velocity variation at high density. It is hoped that the idea of this study may be helpful to promote the modeling and simulation study of traffic flow.

A Realistic Approach to the Traffic Flow Behaviors by Cellular Automata Models

A Realistic Approach to the Traffic Flow Behaviors by Cellular Automata Models

Vehicular motion in counter traffic flow through a series of signals controlled by a phase shift

We study the dynamical behavior of counter traffic flow through a sequence of signals (traffic lights) controlled by a phase shift. There are two lanes for the counter traffic flow: the first lane is for east-bound vehicles and the second lane is for west-bound vehicles. The green-wave strategy is studied in the counter traffic flow where the phase shift of signals in the second lane has opposite sign to that in the first lane. A nonlinear dynamic model of the vehicular motion is presented by nonlinear maps at a low density. There is a distinct difference between the traffic flow in the first lane and that in the second lane. The counter traffic flow exhibits very complex behavior on varying the cycle time, the phase difference, and the split. Also, the fundamental diagram is derived by the use of the cellular automaton (CA) model. The dependence of east-bound and west-bound vehicles on cycle time, phase difference, and density is clarified.

Operational Performance and Speed–Flow Relationships for Basic Managed Lane Segments

Managed lane facilities, including high-occupancy vehicle (HOV) lanes, high-occupancy toll lanes, and express lanes, have become attractive tools for managing today's transportation system. Although managed lanes, specifically, HOV lanes, have existed for several decades, there has been little documentation of their traffic flow behaviors. Because these facilities tend to take on a variety of configurations, including different numbers of managed lanes and separation types from abutting general purpose lanes, transportation engineers should understand the traffic flow differences among facility types. An understanding of the interaction between managed lanes and parallel general purpose lanes is also needed for assessing the performance of managed lanes. A study was done to investigate the performance and traffic flow behavior of managed lane facilities at sites across the country. Traffic flow behavior for five facility types, based on separation type and number of lanes, was analyzed. Factors such as frictional impact on the managed lane—caused by poor performance of the general purpose lanes and slow vehicle effects on managed lane facilities where passing is prohibited—were considered in development of a set of speed–flow curves for each of the five basic facility types. These speed–flow relationships are expressed similarly to basic freeway segments in the Highway Capacity Manual and can be readily incorporated into the manual for predicting the performance of combined general purpose and managed lane facilities.

The changes of group behavior in mixed traffic flow

Mixed traffic flow is the popular problem now, not only in Vietnam but also in almost developing countries. With the mix traffic flow, we have to consider many problems in traffic control and traffic safety, especially in the cases of some countries that private vehicle ownership increase very quickly. This study was conducted to analyze the change in motorcycle driver behaviors with the progress of urbanization and motorization, the observations is inside intersections between left-turn groups and straight-go groups. From the analysis in this study, the results show the changes of driver behavior in case of one popular city in developing countries - Hanoi. This study also conducted the analysis about the relations between group behaviors and conflict situation inside intersection, from that propose some suggestion in traffic control measures and policies for mixed traffic flow.

Pedestrian Level of Service Model Incorporating Pedestrian Perception for Sidewalk with Vendor Activities

This paper presents an alternative model for evaluating pedestrian level of service at the sidewalk with street vendor activities. Variables in the model include pedestrian perceptions of walking condition based on interview surveys as well as the pedestrian traffic flow and pedestrian behavior as the impact of street vendor activities. The presence of street vendors along the sidewalk is considered important in the proposed model. Data collections, which are conducted in Bangkok and Jakarta, include pedestrian interviews and pedestrian traffic surveys. Factor analysis is used to summarize pedestrian perceptions into several important variables. Then, along with pedestrian traffic data, regression models are estimated to find level of service as a function of the pedestrian perceptions of comfort and problem caused by vendor activities, pedestrian volume, and the number of pedestrian who interact with street vendors.