A two-Fluid Model (TFM) of urban traffic provides the macroscopic description of traffic state. The TFMs parameters are hard to calibrate, particularly for the dynamic traffic conditions. This leads to the TFM often being used to compare the quality of service through the plot of stopping time versus trip time of the vehicles in the network. Recently, the taxi GPS data has been applied to predict the traffic condition at the network level. Despite the network-wide coverage of the taxi GPS probe data, the penetration rate of taxis in the network traffic is still a vital and challenging issue for traffic estimation purpose. It is necessary to estimate penetration rate of taxis by combining with other data sources. Here, we propose a novel approach to fill two gaps: TFM parameter calibration and the taxis penetration rate. This method stretches the description of TFM to a zone size. The method is applied to real Changsha city GPS data, calibrating the parameters. The macroscopic fundamental diagram of the large-scale city is derived. For the Changsha case, running speed is the super-linear power law of the fraction of running cars; the fraction of stopping time is nearly linear power law of density, which can be an alternative of the density. The proposed method enables the calibration of TFM parameters and macroscopic traffic monitoring at urban scale using only GPS data.@en

Freeways forman important part of the road network. Yet, driving behavior on freeways, in particular lane changes and the relation with the choice of speed, is not well understood. To overcome this, an online survey has been carried out. Drivers were shown video clips, and after each clip they had to indicate what they would do after the moment the video stopped. A total of 1258 Dutch respondents completed the survey. The results show thatmost people have a strategy to choose a speed first and stick to that, which is the first strategy. A second, less often chosen, strategy is to choose a desired lane and adapt the speed based on the chosen lane. A third strategy, slightly less frequently chosen, is that drivers have a desired speed, but contrary to the first strategy, they increase this speed when they are in a different lane overtaking another driver. A small fraction have neither a desired speed nor a desired lane. Of the respondents 80% use the right lane if possible, and 80% avoid overtaking at the right. Also 80% give way to merging traffic.The survey was validated by 25 survey respondents also driving an instrumented vehicle. The strategies in this drive were similar to those in the survey. The findings of this work can be implemented in traffic simulation models, e.g., to determine road capacity and constraints in geometric design.@en

Freeways form an important part of the road network. Drivers’ behavior can be split in longitudinal (acceleration and deceleration) and lateral behavior (lane changing). The combination of these two behaviors on freeways play a key role in traffic operations. This paper tries to describe the driving behavior, emphasizing the relation between the lateral and longitudinal behavior. To this end, an experimental study based on a test-drive and on-line questionnaire has been carried out. For the test-drive, 34 participants drove a vehicle equipped with monitoring systems. Based on the test drives a survey was developed regarding driving behavior in specific situations. This survey was answered by 1258 drivers who were questioned using videos for specific and relevant situations. The results show that most people choose a speed first, and stick to that. Fewer people adapt a strategy of having a desired speed which might change when they are in a different lane to overtake, or a strategy to choose a desired lane, and tries to adapt speed. A small fraction of the respondents mentioned that they have neither a desired speed or a desired lane. Most people (80%) use the right lane if possible, and 80% will not overtake at the right. 70% may have a courtesy behavior when needed. The outcome of this study has shed some light on the naturalistic driving behavior on freeways under different situations. The findings of this work can be implemented in traffic simulation programs, which are able to delay with this scale of traffic behavior. Repeating this survey in international context will reveal differences between drivers in various countries.@en

Many network-wide traffic management strategies based on the Macroscopic or Network Fundamental Diagram (NFD) have been developed in recent years. In this paper we investigate one of these strategies, namely feedback NFD-based perimeter control, which limits the rate at which vehicles are allowed to enter an urban region. The inflow limitation is imposed at selected main entry links (gated links) and results in queuing of vehicles at the boundaries of the network. Most of the works on this subject neglected the effect of the queued vehicles on the traffic conditions upstream of the gated links. In this paper we analyze in microsimulation the queuing at the gated links and its effect on network performance for a realistic network model. Moreover, a queue management strategy based on a continuous quadratic knapsack problem aiming at balancing relative queues at the gated links is proposed. Simulation results suggest that queues under perimeter control are shorter in space and time than with no perimeter control. Additionally, managing the queues at the gated links not only improves the overall network performance but also reduces the possibility of queue propagation to the upstream junctions. This improves traffic flow outside the protected network.

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Understanding the influence of lane changing manoeuvres on the capacity, stability, and breakdown of traffic flows is a crucial issue. In a recent study, four distinct lane change strategies on freeways have been found: (1) Speed Leading; (2) Speed Leading with Overtaking; (3) Lane Leading; (4) Traffic Leading. To the best of our knowledge, combining speed choice and lane preference is not currently considered in most driving behaviour models. The principal aim of this paper is to investigate the impact of the forenamed lane change strategies on freeway traffic operations. The developed strategy-based lane change model has been implemented in a microscopic simulation environment. The study revealed that different lane change strategies may have various impact on the lane flow distribution and consequently on the freeway capacity. It has been seen that an unbalanced distribution of flow on a multi-lane freeway may lead to reduction of capacity. In addition, it has been found that the lane change rate variates under different lane change strategies. The highest traffic stability has been observed under speed leading and speed leading with overtaking strategies. @en

Traditionally, urban traffic is controlled by traffic lights. Recent findings of the Macroscopic or Network Fundamental Diagram (MFD or NFD) have led to the development of novel traffic control strategies that can be applied at a networkwide level. One pertinent example is perimeter flow control (also known as gating or metering), which limits the rate at which vehicles are allowed to enter an urban region. This paper studies to which extent a combination of adaptive traffic control and gating improves the traffic flow. To this end, combinations of gating and traffic signal timing tested implemented in a microsimulation. It is found that gating is much more effective than adaptive signal timing for high traffic loads. Adaptive signal timing can improve the network performance by increasing the maximum flow and increasing the critical accumulation, i.e. the number of vehicles inside a protected network for which the performance is maximized. The latter helps to reduce queuing outside the protected network. @en

Traffic operations for new road layouts are often simulated using microscopic traffic simulation packages. These traffic simulation packages usually simulate traffic on freeways by a combination of a car-following model and a lane change model. The car-following models have gained attention of researchers and are well calibrated versus data. The proposed lane change models are often representations of assumed reasonable behavior, not necessarily corresponding to reality. The current simulation packages apply solely one specific type of model for car-following or lane changing for all vehicles during the simulation. This paper investigates the decision process of lane changing maneuvers for a variety of drivers based on a two-stage test-drive. Participants are asked to take a drive on a freeway in the Netherlands in a camera-equipped vehicle. Afterwards, the drivers are asked to comment on their choices related to lane and speed choice, while watching the video. This paper reveals that different drivers have completely different strategies to choose lanes, and the choices to change lane are related to their speed choice. Four distinct strategies are empirically found. These strategies differ not only in parameter values, as is currently being modeled in most simulation packages, but also in their reasoning. Most remarkably, all drivers perceive their strategy as an obvious behavior and expect all other drivers to drive in a similar way. In addition to the interviews of the participants in the test-drive, 11 people who did not take part in the experiment were interviewed and questioned on lane change decisions. Moreover, the findings of this study have been presented to various groups of audience with different backgrounds (about 150 people). Their comments and feedback on the derived driving strategies have added some value to this study. The findings in this paper form a starting point for developing a novel lane change model which considers four different driving strategies among the drivers on freeway. This is a significant contribution in the area of driving behavior modeling, since the existing microscopic simulators consider only one type of lane change models for all drivers during the simulation. This could lead to significant changes in the way lane changes on freeways are modeled@en