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Showing papers on "Traffic wave published in 2015"


Journal ArticleDOI
TL;DR: This paper first uses a dynamic traffic simulator to generate flows in all links using available traffic information, estimated demand, and historical traffic data available from links equipped with sensors, and implements an optimization methodology to adjust the origin-to-destination matrices driving the simulator.
Abstract: Obtaining accurate information about current and near-term future traffic flows of all links in a traffic network has a wide range of applications, including traffic forecasting, vehicle navigation devices, vehicle routing, and congestion management. A major problem in getting traffic flow information in real time is that the vast majority of links is not equipped with traffic sensors. Another problem is that factors affecting traffic flows, such as accidents, public events, and road closures, are often unforeseen, suggesting that traffic flow forecasting is a challenging task. In this paper, we first use a dynamic traffic simulator to generate flows in all links using available traffic information, estimated demand, and historical traffic data available from links equipped with sensors. We implement an optimization methodology to adjust the origin-to-destination matrices driving the simulator. We then use the real-time and estimated traffic data to predict the traffic flows on each link up to 30 min ahead. The prediction algorithm is based on an autoregressive model that adapts itself to unpredictable events. As a case study, we predict the flows of a traffic network in San Francisco, CA, USA, using a macroscopic traffic flow simulator. We use Monte Carlo simulations to evaluate our methodology. Our simulations demonstrate the accuracy of the proposed approach. The traffic flow prediction errors vary from an average of 2% for 5-min prediction windows to 12% for 30-min windows even in the presence of unpredictable events.

261 citations


Journal ArticleDOI
TL;DR: It is revealed that the platoon length might be significantly different even if the average velocity of the platoon is essentially the same, and it is demonstrated that the traffic states span a 2D region in the speed-spacing plane.
Abstract: We have carried out car-following experiments with a 25-car-platoon on an open road section to study the relation between a car’s speed and its spacing under various traffic conditions, in the hope to resolve a controversy surrounding this fundamental relation of vehicular traffic. In this paper we extend our previous analysis of these experiments, and report new experimental findings. In particular, we reveal that the platoon length (hence the average spacing within a platoon) might be significantly different even if the average velocity of the platoon is essentially the same. The findings further demonstrate that the traffic states span a 2D region in the speed-spacing (or density) plane. The common practice of using a single speed-spacing curve to model vehicular traffic ignores the variability and imprecision of human driving and is therefore inadequate. We have proposed a car-following model based on a mechanism that in certain ranges of speed and spacing, drivers are insensitive to the changes in spacing when the velocity differences between cars are small. It was shown that the model can reproduce the experimental results well.

164 citations


Journal ArticleDOI
TL;DR: A method to estimate queue profiles that are traffic shockwave polygons in the time-space plane describing the spatiotemporal formation and dissipation of queues is proposed, applicable in oversaturated conditions and includes queue spillover identification.
Abstract: Queues at signalized intersections are the main cause of traffic delays and travel time variability in urban networks. In this article, we propose a method to estimate queue profiles that are traffic shockwave polygons in the time-space plane describing the spatiotemporal formation and dissipation of queues. The method integrates the collective effect of dispersed probe vehicle data with traffic flow shockwave analysis and data mining techniques. The proposed queue profile estimation method requires position and velocity data of probe vehicles; however, any explicit information of signal settings and arrival distribution is indispensable. Moreover, the method captures interdependencies in queue evolutions of successive intersections. The significance of the proposed method is that it is applicable in oversaturated conditions and includes queue spillover identification. Numerical results of simulation experiments and tests on NGSIM field data, with various penetration rates and sampling intervals, reveal the promising and robust performance of the proposed method compared with a uniform arrival queue estimation procedure. The method provides a thorough understanding of urban traffic flow dynamics and has direct applications for delay analysis, queue length estimation, signal settings estimation, and vehicle trajectory reconstruction.

131 citations


Journal ArticleDOI
TL;DR: The proposed nonparametric car-following model exhibits traffic dynamics in a simple and parsimonious manner and is able to well replicate periodic traffic oscillations from the precursor stage to the decay stage.
Abstract: Car-following models are always of great interest of traffic engineers and researchers. In the age of mass data, this paper proposes a nonparametric car-following model driven by field data. Different from most of the existing car-following models, neither driver’s behaviour parameters nor fundamental diagrams are assumed in the data-driven model. The model is proposed based on the simple k-nearest neighbour, which outputs the average of the most similar cases, i.e., the most likely driving behaviour under the current circumstance. The inputs and outputs are selected, and the determination of the only parameter k is introduced. Three simulation scenarios are conducted to test the model. The first scenario is to simulate platoons following real leaders, where traffic waves with constant speed and the detailed trajectories are observed to be consistent with the empirical data. Driver’s rubbernecking behaviour and driving errors are simulated in the second and third scenarios, respectively. The time–space diagrams of the simulated trajectories are presented and explicitly analysed. It is demonstrated that the model is able to well replicate periodic traffic oscillations from the precursor stage to the decay stage. Without making any assumption, the fundamental diagrams for the simulated scenario coincide with the empirical fundamental diagrams. These all validate that the model can well reproduce the traffic characteristics contained by the field data. The nonparametric car-following model exhibits traffic dynamics in a simple and parsimonious manner.

118 citations


Journal ArticleDOI
TL;DR: This paper investigates at an aggregated (macroscopic) scale the effects of route patterns on a road network and proposes a new modelling framework to account for multiple macroscopic routes within reservoirs (spatial aggregates of road network) in the context of MFD simulation.
Abstract: This paper investigates at an aggregated (macroscopic) scale the effects of route patterns on a road network. Four main variables are considered: the production, the mean speed, the outflow and the mean travel distance. First, a simple network with heterogeneous travel distances between origins and destinations is studied by simulation. It appears that the mean travel distance is not only very sensitive to the changes in the origin-destination (OD) matrix but also to the internal traffic conditions within the network. When this distance is assumed constant as usual in the literature, significant errors may appear when estimating the outflow at the network perimeter. The OD matrix also modifies the shape of the macroscopic fundamental diagram (MFD) to a lesser extend. Second, a new modelling framework is proposed to account for multiple macroscopic routes within reservoirs (spatial aggregates of road network) in the context of MFD simulation. In contrast to existing works, partial accumulations are defined per route and traffic waves are tracked at this level. This leads to a better representation of wave propagation between the reservoir frontiers. A Godunov scheme is combined to a HLL Riemann approximate solver in order to derive the model numerical solutions. The accuracy of the resulting scheme is assessed for several simple cases. The new framework is similar to some multiclass models that have been elaborated in the context of link traffic dynamics.

88 citations


Journal ArticleDOI
TL;DR: A marine traffic complexity model is introduced to evaluate the status of traffic situation, use the complexity to investigate the degree of crowding and risk of collision, and support mariners and traffic controllers to get the traffic situation awareness.

74 citations


Journal ArticleDOI
Jin Cao1, Monica Menendez1
TL;DR: In this article, the authors proposed a methodology to model macroscopically such interactions and evaluate their effects on urban congestion, based on a matrix describing how, over time, vehicles in an urban area transition from one parking-related state to another.
Abstract: The urban parking and the urban traffic systems are essential components of the overall urban transportation structure. The short-term interactions between these two systems can be highly significant and influential to their individual performance. The urban parking system, for example, can affect the searching-for-parking traffic, influencing not only overall travel speeds in the network (traffic performance), but also total driven distance (environmental conditions). In turn, the traffic performance can also affect the time drivers spend searching for parking, and ultimately, parking usage. In this study, we propose a methodology to model macroscopically such interactions and evaluate their effects on urban congestion. The model is built on a matrix describing how, over time, vehicles in an urban area transition from one parking-related state to another. With this model it is possible to estimate, based on the traffic and parking demand as well as the parking supply, the amount of vehicles searching for parking, the amount of vehicles driving on the network but not searching for parking, and the amount of vehicles parked at any given time. More importantly, it is also possible to estimate the total (or average) time spent and distance driven within each of these states. Based on that, the model can be used to design and evaluate different parking policies, to improve (or optimize) the performance of both systems. A simple numerical example is provided to show possible applications of this type. Parking policies such as increasing parking supply or shortening the maximum parking duration allowed (i.e., time controls) are tested, and their effects on traffic are estimated. The preliminary results show that time control policies can alleviate the parking-caused traffic issues without the need for providing additional parking facilities. Results also show that parking policies that intend to reduce traffic delay may, at the same time, increase the driven distance and cause negative externalities. Hence, caution must be exercised and multiple traffic metrics should be evaluated before selecting these policies. Overall, this paper shows how the system dynamics of urban traffic, based on its parking-related-states, can be used to efficiently evaluate the urban traffic and parking systems macroscopically. The proposed model can be used to estimate both, how parking availability can affect traffic performance (e.g., average time searching for parking, number of cars searching for parking); and how different traffic conditions (e.g., travel speed, density in the system) can affect drivers ability to find parking. Moreover, the proposed model can be used to study multiple strategies or scenarios for traffic operations and control, transportation planning, land use planning, or parking management and operations.

67 citations


Journal ArticleDOI
TL;DR: A space discretization–based simulation framework is proposed to address critical issues of heterogeneous traffic, including discrete lane changes in the case of lane-based traffic and modeling of continuous lateral movements.
Abstract: Vehicles in homogeneous traffic follow lane-based movement and can be conveniently modeled using car-following and lane-changing models. The former deals with longitudinal movement behavior, while the latter deals with lateral movement behavior. However, typical heterogeneous traffic is characterized by the presence of multiple vehicle types and non-lane-based movement. Because of the off-centered positions of the vehicles, the following driver is not necessarily influenced by a single leader. Additionally, the following behavior of the subject vehicle depends on the type of the front vehicle. Unlike discrete lane changes in the case of lane-based traffic, heterogeneous traffic streams require modeling of continuous lateral movements. Hence, the existing driver behavioral models may not be able to represent the heterogeneous traffic behavior accurately enough. To address these critical issues of heterogeneous traffic, a space discretization–based simulation framework is proposed. The lane is divid...

56 citations


Journal ArticleDOI
01 Jan 2015
TL;DR: Methods of queuing theory helped to obtain explicit solutions of the problem of minimizing delays at signal-controlled road intersection and the concept of the effective number of lanes is used which indicates the maximum flow of cars with different modes of traffic lights.
Abstract: The paper describes the methods of queuing theory to solve the problem of optimizing traffic light phases on signal-controlled road intersections. The flow of vehicles on multi-lane roads is described by Poisson processes. In this paper the concept of the effective number of lanes is used which indicates the maximum flow of cars with different modes of traffic lights. Methods of queuing theory helped to obtain explicit solutions of the problem of minimizing delays at signal-controlled road intersection.

50 citations


Journal ArticleDOI
TL;DR: In this article, the authors developed a methodology to measure relationships of density and vehicle spacing on freeways and verified the results against the NGSIM data set, finding that many of the critical parameters of the macroscopic flow-density and microscopic speed-spacing relationships depend on vehicle length.
Abstract: Traffic flow theory has come to a point where conventional, fixed time averaged data are limiting our insight into critical behavior both at the macroscopic and microscopic scales. This paper develops a methodology to measure relationships of density and vehicle spacing on freeways. These relationships are central to most traffic flow theories but have historically been difficult to measure empirically. The work leads to macroscopic flow-density and microscopic speed-spacing relationships in the congested regime derived entirely from dual loop detector data and then verified against the NGSIM data set. The methodology eliminates the need to seek out stationary conditions and yields clean relationships that do not depend on prior assumptions of the curve shape before fitting the data. Upon review of the clean empirical relationships a key finding of this work is the fact that many of the critical parameters of the macroscopic flow-density and microscopic speed-spacing relationships depend on vehicle length, e.g., upstream moving waves should travel through long vehicles faster than through short vehicles. Thus, the commonly used assumption of a homogeneous vehicle fleet likely obscures these important phenomena. More broadly, if waves travel faster or slower depending on the length of the vehicles through which the waves pass, then the way traffic is modeled should be updated to explicitly account for inhomogeneous vehicle lengths.

44 citations


Journal ArticleDOI
TL;DR: There are differences in the resulted noise levels when the intersection is detailed and these differences may affect the measures that can be undertaken by the local authorities for noise abatement.

Journal ArticleDOI
TL;DR: The numerical results show that the proposed model can describe oscillation in traffic and stop-and-go traffic, where the speed–density relationship is qualitatively accordant with the empirical data of the Weizikeng segment of the Badaling freeway in Beijing.
Abstract: In this paper, we propose a traffic flow model to study the effects of the real-time traffic state on traffic flow. The numerical results show that the proposed model can describe oscillation in traffic and stop-and-go traffic, where the speed–density relationship is qualitatively accordant with the empirical data of the Weizikeng segment of the Badaling freeway in Beijing, which means that the proposed model can qualitatively reproduce some complex traffic phenomena associated with real-time traffic state.

Journal ArticleDOI
Simon Oh1, Hwasoo Yeo1
TL;DR: In this article, the authors analyzed individual vehicle trajectories at a microscopic level and documented the findings based on an investigation of traffic flow involving diverse traffic situations, identifying a driver tendency to take a significant headway after passing stop-and-go waves was identified as one of the influencing factors for discharge rate reduction.
Abstract: In an effort to uncover traffic conditions that trigger discharge rate reductions near active bottlenecks, this paper analyzed individual vehicle trajectories at a microscopic level and documented the findings. Based on an investigation of traffic flow involving diverse traffic situations, a driver’s tendency to take a significant headway after passing stop-and-go waves was identified as one of the influencing factors for discharge rate reduction. Conversely, the pattern of lane changers caused a transient increase in the discharge rate until the situation was relaxed after completing the lane-changing event. Although we observed a high flow from the incoming lane changers, the events ultimately caused adverse impacts on the traffic such that the disturbances generated stop-and-go waves. Based on this observation, we regard upstream lane changes and stop-and-go waves as the responsible factors for the decreased capacity at downstream of active bottlenecks. This empirical investigation also supports the resignation effect, the regressive effect, and the asymmetric behavioral models in differentiating acceleration and deceleration behaviors.

Journal ArticleDOI
TL;DR: A continuum traffic flow model is put forward that incorporates the bi-directional information impact macroscopically but can still preserve the anisotropic characteristics of traffic flow and avoid non-physical phenomenon such as wrong-way travels.
Abstract: In traffic flow with naturalistic driving only, stimulus information pre-dominantly comes from the preceding vehicles with drivers occasionally responding to the following vehicles through the inspection of rear-view mirrors. Such one-sided information propagation may potentially be altered in future connected vehicle environment. This brings new motivations of modeling vehicle dynamics under bi-directional information propagation. In this study, stemming from microscopic bi-directional car-following models, a continuum traffic flow model is put forward that incorporates the bi-directional information impact macroscopically but can still preserve the anisotropic characteristics of traffic flow and avoid non-physical phenomenon such as wrong-way travels. We then analyze the properties of the continuum model and respectively illustrate the condition that guarantees the anisotropy, eradicates the negative travel speed, preserves the traveling waves and keeps the linear stability. Through a series of numerical experiments, it is concluded that (1) under the bi-directional looking context only when the backward weight ratio belongs to an appropriate range then the anisotropic property can be maintained; (2) forward-propagating traffic density waves and standing waves emerge with the increasing consideration ratio for backward information; (3) the more aggressive driving behaviors for the forward direction can delay the backward-propagating and speed up the forward-propagating of traffic density waves; (4) positive holding effect and negative pushing effect of backward looking can also be observed under different backward weight ratios; and (5) traffic flow stability varies with different proportion of backward traffic information contribution and such stability impact is sensitive to the initial traffic density condition. This proposed continuum model may contribute to future development of traffic control and coordination in future connected vehicle environment.

Journal ArticleDOI
TL;DR: Based on the stochastic traffic flow simulation, two new analytical frameworks, one using mode superposition and the other using the finite element (FE) formulation, were proposed recently for the bridge-stochastic traffic system.

Journal ArticleDOI
TL;DR: In this paper, an acknowledged traffic micro-simulation model is used for generating congested traffic on a single-lane roadway encompassing two bridges (200 and 1000m long), and different congestion patterns are analyzed in relation to their traffic features and effects on bridge loading.

Proceedings ArticleDOI
01 Oct 2015
TL;DR: An intelligent traffic cooperative routing application called SCORPION is proposed, which improves the overall spatial utilization of a road network and also reduces the average vehicletravel costs by avoiding vehicles from getting stuck in traffic.
Abstract: Most large cities suffer with congestion problem, one of the main causes of congestion is the sudden increase of vehicle traffic during peak hours, mainly in areas with bottlenecks. Current solutions in the literature are based on perceiving road traffic conditions and re-routing vehicles to avoid the congested area. However, they do not consider the impact of thesechanges on near future traffic patterns. Hence, these approachesare unable to provide a long-term solution to the congestion problem, since when suggesting alternative routes, they create new bottlenecks at roads closer to the congested one, thus just transferring the problem from one point to another one. With this issue in mind, we propose an intelligent traffic cooperative routing application called SCORPION, which improves the overall spatial utilization of a road network and also reduces the average vehicletravel costs by avoiding vehicles from getting stuck in traffic. Simulation results show that our proposal is able to forecasting congestion and re-route vehicles properly, performing a load balance of vehicular traffic.

Journal ArticleDOI
TL;DR: Based on real field traffic data measured in 1996-2014 through road detectors installed on German freeways, the authors reveal physical features of empirical nuclei for spontaneous traffic breakdown in free flow at highway bottlenecks.
Abstract: Based on an empirical study of real field traffic data measured in 1996–2014 through road detectors installed on German freeways, we reveal physical features of empirical nuclei for spontaneous traffic breakdown in free flow at highway bottlenecks. A microscopic stochastic three-phase traffic model of the nucleation of spontaneous traffic breakdown presented in the article explains the empirical findings. It turns out that in the most cases a nucleus for the breakdown occurs through an interaction of one of waves in free flow with an empirical permanent speed disturbance localized at a highway bottleneck. The wave is a localized structure in free flow, in which the total flow rate is larger and the speed averaged across the highway is smaller than outside the wave. The waves in free flow appear due to oscillations in the percentage of slow vehicles; these waves propagate with the average speed of slow vehicles in free flow. Any of the empirical waves exhibits a two-dimensional asymmetric spatiotemporal structure: Wave’s characteristics are different in different highway lanes.

Journal ArticleDOI
TL;DR: It is found that traffic states inside hypercongestion are not homogeneous, which contradicts the existence of a “Homogeneous Congested Traffic” state claimed in two-phase traffic theory.
Abstract: We study in this paper the structure of traffic under hypercongestion, which is a controversial issue between traditional two-phase traffic theory and Kerner’s three-phase theory. By analyzing video traffic data from a section of the Nanjing Airport Highway, it is found that traffic states inside hypercongestion are not homogeneous, which contradicts the existence of a “Homogeneous Congested Traffic” state claimed in two-phase traffic theory. Analysis of vehicle trajectories and velocities obtained from an experimental car-following study with a platoon of 25 vehicles also confirms the above findings. Furthermore, it is also found from the video traffic data that the structure of hypercongested traffic varies only slightly with location, which might be due to small jams inside hypercongested traffic merging into larger ones slowly and/or larger jams sometimes breaking into small ones. Finally, the implications of our observations on traffic modeling have been discussed.

Journal ArticleDOI
TL;DR: In this article, the authors present a model of the equilibrium for cars and transit, recognizing that hypercongestion often arises when modes are not priced and show that hyper-congested traffic can be part of a stable, steady equilibrium state when cars and high-capacity transit are used simultaneously.

Journal ArticleDOI
TL;DR: Results show that the proposed LaNPro traffic device may ensure the non-stop crossing of intersections having an expected traffic volume equal or less than λ = 0.10 vehicles per second.
Abstract: This work presents a novel traffic device (LaNPro) that avoids the stop of vehicles at junctions under low traffic conditions. To the best of our knowledge, this is the first smart traffic light designed for low traffic conditions. LaNPro is a security solution to preserve the physical integrity of drivers in countries with high social discrepancy. The server-side of the solution is deployed as a module of a smart traffic light, and it senses the presence of vehicles along the road through input devices (radars, cameras, road sensors, wireless communication) to assign the right of way. While any smart traffic light is able to manage low traffic intersections, we argue that they are not specialized devices to perform such task, and thus they may lack important optimizations. The main aggregated value of our approach is the ability to handle low traffic conditions, and that involves several challenges. Results show that our proposal may ensure the non-stop crossing of intersections having an expected traffic volume equal or less than ? = 0.10 vehicles per second, assuming intersections composed of 2, 3, or 4 lanes, road segments 200 m long, intersections 10 m wide, and vehicles 5 m long traveling at an average speed of μ = 40 km/h with standard deviation ? = 4 km/h.

Journal ArticleDOI
TL;DR: It is mathematically proved that the set of earliest arrival flows EAFs not constrained by the traffic wave propagation equations obtained on the node-arc network without cell division is a subset of the SO-DTA, which can theoretically be solved with a run time at the link level depending polynomially on log T.
Abstract: This paper investigates the cell-transmission model CTM-based single destination system optimum dynamic traffic assignment SO-DTA problem, focusing attention on a case where the cell properties are time-invariant. We show the backward propagation of congestion in CTM does not affect the optimal arrival flow pattern of SO-DTA, if the fundamental diagram is of triangular/trapezoidal shape as in the CTM. We mathematically prove that the set of earliest arrival flows EAFs not constrained by the traffic wave propagation equations obtained on the node-arc network without cell division is a subset of the SO-DTA. This finding leads to a new approach to the SO-DTA that solves the EAF. Such an EAF can be obtained by merely applying static flow techniques and turning the static flows into dynamic flows over time. Therefore, SO-DTA can theoretically be solved with a run time at the link level depending polynomially on log T. We use numerical examples to verify the results and report the computational benefits of the proposed method by solving SO-DTA on a real-world network.

Journal ArticleDOI
TL;DR: A new lattice model of two-lane traffic flow considering the effects of traffic interruption probability is proposed and the modified Korteweg–de Vries equation is obtained to describe the traffic phase transition resulted from traffic disruption probability through nonlinear analysis in two- lane system.
Abstract: In this paper, we proposed a new lattice model of two-lane traffic flow considering the effects of traffic interruption probability. The stability condition is deduced from the linear stability analysis for two-lane freeways. Also, the modified Korteweg–de Vries equation is obtained to describe the traffic phase transition resulted from traffic interruption probability through nonlinear analysis in two-lane system. The numerical simulation results validate that the traffic interruption probability further improves the stability of traffic flow on two-lane freeways.

Journal ArticleDOI
TL;DR: The author investigates and characterizes the time-headway distributions of vehicles traveling on an urban expressway in Bangkok, Thailand and finds that the GEV distribution is most effective in modeling time headways.
Abstract: Traffic flow modeling is one of the fundamental keys to solving a traffic engineering problem. Among many parameters, time headway is frequently used to model traffic flow characteristics. A statistical analysis of time headways is immensely important to both theoretical traffic modeling and simulation-based traffic modeling. Basically, it allows researchers to describe an inherently random pattern of traffic flows. Past studies have mainly focused on the time headways of vehicles on highways, freeways, and arterials. However, studies of time headways on urban expressways are rather limited and still need further investigation. In this paper, the author investigates and characterizes the time-headway distributions of vehicles traveling on an urban expressway in Bangkok, Thailand. Particularly, the exponential distribution, the lognormal distribution, and the generalized extreme value (GEV) distribution are used to model the time headways. It is found that the GEV distribution is most effective in modeling time headways. In fact, the GEV distribution can describe more than 90% of the empirical distributions on most lanes and sections of the expressway. On the other hand, the exponential distribution is the least effective distribution. It can only describe the empirical distributions during the periods when the traffic is extremely light.

Journal ArticleDOI
TL;DR: The Network Transmission Model (NTM), a model based on areas, exploiting the Macroscopic or Network Fundamental Diagram, is proposed which can be implemented in a network divided into multiple subnetworks, and the physical properties of spillback of traffic jams for subnetwork to subnetwork is ensured.
Abstract: Microscopic and macroscopic dynamic traffic models not fast enough to run in an optimization loop to coordinate traffic measures over areas of twice a trip length (50x50 km). Moreover, in strategic planning there are models with a spatial high level of detail, but lacking the features of traffic dynamics. This paper introduces the Network Transmission Model (NTM), a model based on areas, exploiting the Macroscopic or Network Fundamental Diagram (NFD). For the first time, a full operational model is proposed which can be implemented in a network divided into multiple subnetworks, and the physical properties of spillback of traffic jams for subnetwork to subnetwork is ensured. The proposed model calculates the traffic flow between to cell as the minimum of the demand in the origin cell and the supply in the destination cell. The demand first increasing and then decreasing as function of the accumulation in the cell; the supply is first constant and then decreasing as function of the accumulation. Moreover, demand over the boundaries of two cells is restricted by a capacity. This system ensures that traffic characteristics move forward in free flow, congestion moves backward and the NFD is conserved. Adding the capacity gives qualitatively reasonable effects of inhomogeneity. The model applied on a test case with multiple destinations, and re-routing and perimeter control are tested as control measures.

Journal ArticleDOI
TL;DR: A modified traffic model (R-STCA model, for short) is presented, in which the new symmetric lane changing rules are introduced by considering driving behavioral difference and dynamic headway and results indicate that the presented model is reasonable and more realistic.
Abstract: Based on the two-lane traffic model proposed by Chowdhury et al., a modified traffic model (R-STCA model, for short) is presented, in which the new symmetric lane changing rules are introduced by considering driving behavioral difference and dynamic headway. After the numerical simulation, a broad scattering of simulated points is exhibited in the moderate density region on the flow-density plane. The synchronized flow phase accompanied with the wide moving jam phase is reproduced. The spatial–temporal profiles indicate that the vehicles move according to the R-STCA model can change lane more easily and more realistically. Then vehicles are convenient to get rid of the slow vehicles that turn into plugs ahead, and hence the capacity increases. Furthermore the phenomenon of the high speed car-following is discovered by using the R-STCA model, which has been already observed in the traffic measured data. All these results indicate that the presented model is reasonable and more realistic.

Journal ArticleDOI
TL;DR: In this paper, a field investigation was conducted on four bicycle-only paths in the vicinity of bottlenecks in the city of Nanjing, China; two were one-lane paths and two were twolane paths.
Abstract: This study investigated the operational features in bicycle traffic flow on bicycle-only paths. A field investigation was conducted on four bicycle-only paths in the vicinity of bottlenecks in the city of Nanjing, China; two were one-lane paths and two were two-lane paths. The cumulative curve method was used to extract from videos traffic flow information, such as bicycle speeds, flow, and density. The fundamental diagram with free-flow and congested traffic state was constructed with the use of actual traffic data. Data analysis showed that the capacity of bicycle traffic flow on the one-lane and two-lane paths was 3,960 bicycles per hour and 8,100 bicycles per hour, respectively. The critical density was approximately 100 bicycles per kilometer per lane. Average bicycle speed and speed variation decreased as bicycle density increased. The probability of overtaking was highest when bicycle traffic was slightly congested. The observational study showed that even when average speed was quite low, bicycle ...

Journal ArticleDOI
TL;DR: The proposed DTA model can be used to estimate the stochastic link flow pattern and route travel time distribution for examining the impacts of a traffic incident on the on-time arrival probability with and without dynamic speed limit (SL) control.
Abstract: A traffic incident is one of the major sources for degrading network capacity, inducing traffic congestion, and decreasing network reliability. The impacts of a traffic incident on network reliability have been extensively studied with the use of static network equilibrium or dynamic simulation models. In this paper, an analytical reliability-based dynamic traffic assignment (DTA) model is proposed for assessing the temporal and spatial impacts of a traffic incident on network reliability. The proposed DTA model can be used to estimate the stochastic link flow pattern and route travel time distribution for examining the impacts of a traffic incident on the on-time arrival probability with and without dynamic speed limit (SL) control. It is shown that a traffic incident on a congested road during peak period will greatly decrease the on-time arrival probability, particularly when the incident has greater effects on link capacity degradation with longer duration. Under certain circumstances, SL control can ...

Journal ArticleDOI
TL;DR: The results indicate that incoming flow control and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume’s enhancing.
Abstract: The aim of this work is to investigate the traffic impact of low visibility weather on a freeway including the fraction of real vehicle rear-end accidents and road traffic capacity. Based on symmetric two-lane Nagel–Schreckenberg (STNS) model, a cellular automaton model of three-lane freeway mainline with the real occurrence of rear-end accidents in low visibility weather, which considers delayed reaction time and deceleration restriction, was established with access to real-time traffic information of intelligent transportation system (ITS). The characteristics of traffic flow in different visibility weather were discussed via the simulation experiments. The results indicate that incoming flow control (decreasing upstream traffic volume) and inputting variable speed limits (VSL) signal are effective in accident reducing and road actual traffic volume’s enhancing. According to different visibility and traffic demand the appropriate control strategies should be adopted in order to not only decrease the probability of vehicle accidents but also avoid congestion.

Journal ArticleDOI
10 Apr 2015
TL;DR: An analytic model is presented to estimate the speed report rate from cellular network signaling in steady traffic conditions, that is, the traffic speed and flow are assumed constant, and demonstrates that the lack of speed reports from consecutive handover events during rush hours indicates severe traffic congestion.
Abstract: The control signals of cellular networks have been used to infer the traffic conditions of the road network. In particular, consecutive handover events are being used to estimate the traffic speed. During traffic congestion, consecutive handover events may be rare because vehicles move slowly, and thus very few or no speed reports would be generated from the congested area.However, the traffic speed report rate during traffic congestion has not been investigated in the literature. In this paper, we present an analytic model to estimate the speed report rate from cellular network signaling in steady traffic conditions, that is, the traffic speed and flow are assumed constant. Real field trial data were used to validate our analytic model. In addition, computer simulations were conducted to study how speed reports are generated in dynamic traffic conditions when traffic speed and flow change rapidly. Our study indicates that in a typical cell of length 1.5km with a typical expected call holding time of 1min, no speed report was generated from a congested three-lane highway. Our study demonstrates that the lack of speed reports from consecutive handover events during rush hours indicates severe traffic congestion, and new methods that can estimate traffic speed from cellular network data during severe traffic congestion need to be developed. Copyright © 2013 John Wiley & Sons, Ltd.