Dynamic Headway Research Articles

Maximin headway control of automated vehicles for system optimal dynamic traffic assignment in general networks

This study develops the headway control framework in a fully automated road network, as we believe headway of Automated Vehicles (AVs) is another influencing factor to traffic dynamics in addition to conventional vehicle behaviors (e.g. route and departure time choices). Specifically, we aim to search for the optimal time headway between AVs on each link that achieves the network-wide system optimal dynamic traffic assignment (SO-DTA). To this end, the headway-dependent fundamental diagram (HFD) and headway-dependent double queue model (HDQ) are developed to model the effect of dynamic headway on roads, and a dynamic network model is built. It is rigorously proved that the minimum headway could always achieve SO-DTA, yet the optimal headway is non-unique. Motivated by these two findings, this study defines a novel concept of maximin headway, which is the largest headway that still achieves SO-DTA in the network. Mathematical properties regarding maximin headway are analyzed and an efficient solution algorithm is developed. Numerical experiments on both a small and large network verify the effectiveness of the maximin headway control framework as well as the properties of maximin headway. This study sheds light on deriving the desired solution among the non-unique solutions in SO-DTA and provides implications regarding the safety margin of AVs under SO-DTA.

Data-Driven Event-Triggered Cooperative Control for Multiple Subway Trains With Switching Topologies

In this paper, a data-driven event-triggered cooperative control (DD-ETCC) scheme is proposed for the multiple subway trains to realize speed tracking and dynamic headway adjustment under switching topologies. Firstly, a nonlinear subway train system is transformed into a linearization data model, and the complex nonlinear terms caused by mechanical and aerodynamic resistance and operating environment conditions are estimated by projection algorithm. Then, the DD-ETCC scheme based on the linearization data model and the asynchronous event-triggered condition for multiple subway trains with switching topologies is designed. Theoretical analysis shows that the speed tracking errors of multiple subway trains are bounded, and the headway distances of consecutive trains are stabilized in a safe range with the proposed scheme. Finally, the effectiveness of the proposed DD-ETCC scheme of multiple trains is illustrated by subway train simulations.

Communication-Based Train Control with Dynamic Headway Based on Trajectory Prediction

Rail transit plays a significant role in the operation of an efficient and effective urban public transportation system. Safety and capacity are some of the most crucial objectives in railway operations. The communication-based train control (CBTC) system is a continuous and automatic train control system that realizes constant and high-capacity train ground two-way communication. In this study, a dynamic headway model of the ‘softwall’ moving-block approach is proposed for CBTC to increase the track capacity and improve dispatching efficiency based on the train trajectory prediction. For this precise trajectory prediction task, we introduce a hybrid trajectory prediction model to combine Long Short-term memory (LSTM) and Kalman Filter (KF) to extract the train’s local data features and learn the long-term dependencies, respectively. Then we present a dynamic headway model to maximize the train headway and reduce the track distance. The leading trains’ information is used to construct the iterative learning control strategy, and the predicted trajectory is input into the algorithm of the headway model. We use a simulation model of the rail network in Chengdu to demonstrate the effectiveness of our proposed approach. The results show the Mean Absolute Error (MAE) of the predicted trajectory retreated to 93.97 cm and reductions in operation headway of at least 64.33% under the dynamic headway model versus the traditional moving-block model.

Research on Adaptive Cruise Control Car-following Model Based on Dynamic Spacing in V2X Scenario

In the adaptive cruise control (ACC) car-following model, the constant spacing strategy cannot adapt to complex and variable deceleration and acceleration situations. When the preceding car decelerates or accelerates suddenly, considering the safety and adaptability, the desire spacing should be larger or smaller, so the desire spacing is not only related to the speed of the two cars, but also to the speed change of the preceding car. For this problem of the deficiency, which the desire spacing existed, an adaptive cruise control car-following model based on dynamic headway strategy is proposed in this paper. In order to achieve more realtime and more accurate information transmission, this paper uses the v2v communication in v2x environment to obtain the preceding car information. MATLAB/Simulink is used to simulation modelling for verification and analysis. The experimental results show that, under the same simulation conditions, the dynamic spacing strategy proposed in this paper have a larger desire spacing for safety when preceding car decelerates, and a smaller desire spacing for comfort and road dynamic utilization when preceding car accelerates. So, the dynamic spacing strategy proposed in this paper shows different improvement effects for different acceleration and deceleration conditions.

Influences of dynamic safe headway on car-following behavior

In car following states, the reaction of drivers is closely related to the space headway at given speed difference. Unlike the constant velocity difference reaction coefficient in traditional traffic model, this work designed a dynamic function, which can realize the switch between models according to the dynamic headway between vehicles, and developed a new car-following model to investigate the influences of dynamic safe headway (DSH) on car-following behavior. First, the following behavior of vehicle with DSH under urgent situation is simulated to demonstrate that DSH has the ability to prevent the occurrence of collision. Then, the prediction of delay time of car motion and the kinematic wave speed is reasonable and the evolution from free flow to congested flow is well reproduced. In addition, the result of excitation simulation shows that DSH can absorb the disturbance and suppress the propagation of traffic oscillations effectively, which is hard to achieve for traditional traffic model. Finally, the numerical experiment under period condition demonstrate that the new model is conducive to improving driving performance and further to smooth traffic flow. In addition, calibration and validation results show that the empirical data can be modeled with a quantitative agreement.

Modeling and Simulating Urban Traffic Flow Mixed With Regular and Connected Vehicles

In the upcoming decades, connected vehicles will join regular vehicles on the road, and the characteristics of traffic flows will change accordingly. To better understand mixed traffic flow (regular vehicles and connected vehicles) characteristics, a generic car-following modeling framework for this new mixed traffic flow on an urban road under a connected vehicle environment is proposed in this paper. Considering a vehicle’s speed, which is affected by the speed of the preceding vehicle, an improved intelligent driver model (IDM) is used as the car-following model for regular vehicles. An extended cooperative adaptive cruise control (CACC) based on the nonlinear dynamic headway strategy was established as the car-following model for connected vehicles. The fundamental diagram model of mixed traffic flow under different market penetration rates of CACC vehicles is investigated, and the traffic flow operation mechanism of connected vehicles is analyzed to improve the capacity. In addition, simulation experiments on urban roads are designed to evaluate the queue time and length of vehicles passing through congested sections under different market penetration rates of CACC vehicles. The results demonstrate that the proposed model can effectively describe the current situation of traffic flow on urban roads under different market penetration rates of CACC vehicles. The increase in the market penetration rates of CACC vehicles can significantly improve the traffic flow efficiency. When CACC vehicles reach 100% of all vehicles, the queue length on congested roads can be shortened by 64.6%, and the total travel time on congested roads can be reduced by 48.3%.

Feature Analysis on Mixed Traffic Flow of Manually Driven and Autonomous Vehicles Based on Cellular Automata

This paper attempts to disclose the features of the mixed traffic flow of manually driven vehicles (MVs) and autonomous vehicles (AVs). Considering dynamic headway, the mixed traffic flow was modelled based on the improved single-land cellular automata (CA) traffic flow model (DHD) proposed by Zhang Ningxi. The established CA model was adopted to obtain the maximum flow of the mixed traffic flow and was analyzed under different proportions of AVs. On this basis, the features of the mixed traffic flow were summarized. The main results are as follows: the proportion of AVs has a significant impact on the mixed traffic flow; when the proportion reached 0.6, the flow of the whole lane was twice that of the MV traffic flow. At a low density, the AV proportion has an obvious influence on mixed traffic flow. At a high density, the mixed traffic flow changed very little, as the AV proportion increased from 0 to 5. The reason is that the flow of the whole lane is constrained by the fact that MVs cannot move faster. However, when the AV proportion reached 0.8, the flow of the whole lane became three times that at the proportion of 0.6. At the speed of 126 km/h, the flow rate was 2.5 times the speed limit of 54 km/h. The findings lay a theoretical basis for the modelling of multilane mixed traffic flow.

동적 운전 시격 방식 열차제어의 효율 향상을 위한 전송 시간 요건 분석

동적 운전 시격 방식 열차제어의 효율 향상을 위한 전송 시간 요건 분석

Numerical study of traffic flow considering the probability density distribution of the traffic density

The probability density distribution of the traffic density is analyzed based on the empirical data. It is found that the beta distribution can fit the result obtained from the measured traffic density perfectly. Then a modified traffic model is proposed to simulate the microscopic traffic flow, in which the probability density distribution of the traffic density is taken into account. The model also contains the behavior of drivers’ speed adaptation by taking into account the driving behavior difference and the dynamic headway. Accompanied by presenting the flux-density diagrams, the velocity evolution diagrams and the spatial-temporal profiles of vehicles are also given. The synchronized flow phase and the wide moving jam phase are indicated, which is the challenge for the cellular automata traffic model. Furthermore the phenomenon of the high speed car-following is exhibited, which has been observed in the measured data previously. The results set demonstrate the effectiveness of the proposed model in detecting the complicated dynamic phenomena of the traffic flow.

Models and algorithms for dynamic headway control

We consider the dynamic headway control problem under no-deadlock and no-collision constraints. Different speed limits are applied to different railway segments and junctions according to local geographic conditions. A mathematical programming formulation is given under the consideration of the trains’ dynamics. Then a heuristic rule for train movement is proposed to reduce delay and guarantees a safety distance between trains. Simulation experiments are also conducted to show the efficiency of the dynamic headway model together with the proposed heuristics.

Positive Train Control With Dynamic Headway Based on an Active Communication System

Safety, capacity, and timely schedules are some of the most crucial objectives in railway operations. Positive train control (PTC) is a concept whose goal is to improve the safety and efficiency of railway operations by using advanced information technologies. Information technologies such as active communications enable the use of a dynamic headway policy, which can increase the track capacity and improve dispatching efficiency in addition to improving safety. In this paper, we propose a dynamic headway system for PTC based on active communications, which we integrate with a dynamic dispatching model in order to improve track capacity and safety in railway operations. We use a simulation model of a rail network in southern California to demonstrate the effectiveness of our proposed approach. The simulation results of different scenarios show reductions in train delays of at least 55% and reductions in travel time of at least 35% when using the dynamic headway versus using a fixed headway.

A modified two-lane traffic model considering drivers’ personality

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.

One-dimensional cellular automaton model of traffic flow considering dynamic headway

Based on the NaSch cellular automaton traffic model, a modified single lane traffic model is proposed by considering the dynamic headway of successive vehicles, in which the complex characteristic and driving behavior difference between drivers are taken into account. The relationship between the flow rate and the traffic density is obtained by the numerical simulation, and it shows a two-dimensional region in the flow density plane. The three traffic phases, i.e., free flow, synchronized flow, and wide moving jams, are exhibited. It indicates that the synchronized flow and traffic jams can appear even if there is no traffic bottleneck. Besides, the high speed car-following phenomenon is indicated when the traffic is in the synchronized flow. The rate of the high speed car-following is in good agreement with the measured result.