Showing papers on "Traffic wave published in 2019"

Cooperative Shock Waves Mitigation in Mixed Traffic Flow Environment

Abstract: Human driver behavior strongly influences traffic flow by increasing the spread of shock waves in a downstream direction. This paper addresses the problem of traffic congestion mitigation in a mixed scenario composed of connected human-driven and autonomous vehicles. The control protocol, driving the longitudinal motion of the autonomous vehicles, is designed for damping down traffic waves. The effectiveness of the strategy, and ability to cope with multiple and time-varying delays originated by the non-ideal wireless communication among connected vehicles, is both analytically and numerically analyzed. The asymptotic stability of the algorithm is mathematically proved by leveraging a Lyapunov–Krasovskii functional, while the head-to-tail stability tool is exploited for the tuning of the control gains. The performance of the control strategy is disclosed by using hardware-in-the-loop real-time simulation for an exemplary pattern of three vehicles. The effectiveness of the proposed cooperative strategy in longer queues of vehicles is, instead, investigated through PLEXE, an inter-vehicular communication and mobility simulator that includes features for autonomous vehicles as well as for the realistic emulation of the IEEE 802.11p standard. The results confirm the robustness of the approach and its ability in damping disturbances and mitigating stop-and-go effects according to the theoretical derivation.

Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic

Abstract: It is anticipated that in the near future, the penetration rate of vehicles with some autonomous capabilities (e.g., adaptive cruise control, lane following, full automation, etc.) will increase on roadways. This work investigates the potential reduction of vehicular emissions caused by the whole traffic stream, when a small number of autonomous vehicles (e.g., 5% of the vehicle fleet) are designed to stabilize the traffic flow and dampen stop-and-go waves. To demonstrate this, vehicle velocity and acceleration data are collected from a series of field experiments that use a single autonomous-capable vehicle to dampen traffic waves on a circular ring road with 20 to 21 human-piloted vehicles. From the experimental data, vehicle emissions (hydrocarbons, carbon monoxide, carbon dioxide, and nitrogen oxides) are estimated using the MOVES emissions model. This work finds that vehicle emissions of the entire fleet may be reduced by between 15% (for carbon dioxide) and 73% (for nitrogen oxides) when stop-and-go waves are reduced or eliminated by the dampening action of the autonomous vehicle in the flow of human drivers. This is possible if a small fraction (∼5%) of vehicles are autonomous and designed to actively dampen traffic waves. However, these reductions in emissions apply to driving conditions under which stop-and-go waves are present. Less significant reductions in emissions may be realized from a deployment of AVs in a broader range of traffic conditions.

Tracking vehicle trajectories and fuel rates in phantom traffic jams: Methodology and data

Abstract: High-fidelity vehicle trajectory data is becoming increasingly important in traffic modeling, especially to capture dynamic features such as stop-and-go waves. This article presents data collected in a series of eight experiments on a circular track with human drivers. The data contains smooth flowing and stop-and-go traffic conditions. The vehicle trajectories presented in this article are collected using a panoramic 360-degree camera, and fuel rate data is recorded via an on-board diagnostics scanner installed in each vehicle. The video data from the 360-degree camera is processed with an offline unsupervised algorithm to extract vehicle trajectories from experimental data. The trajectories are highly accurate, with a mean positional bias of less than 0.01 m and a standard deviation of 0.11 m. The velocities are also validated to be highly accurate with a bias of 0.02 m/s and standard deviation of 0.09 m/s. The source code and data used in this article are published with this work.

Feedback Control Algorithms for the Dissipation of Traffic Waves with Autonomous Vehicles

Abstract: This article considers the problem of traffic control in which an autonomous vehicle is used to regulate human-piloted traffic to dissipate stop-and-go traffic waves. We first investigated the controllability of well-known microscopic traffic flow models, namely, (i) the Bando model (also known as the optimal velocity model), (ii) the follow-the-leader model, and (iii) a combined optimal velocity follow-the-leader model. Based on the controllability results, we proposed three control strategies for an autonomous vehicle to stabilize the other, human-piloted traffics. We subsequently simulate the control effects on the microscopic models of human drivers in numerical experiments to quantify the potential benefits of the controllers. Based on the simulations, finally, we conduct a field experiment with 22 human drivers and a fully autonomous-capable vehicle, to assess the feasibility of autonomous vehicle-based traffic control on real human-piloted traffic. We show that both in simulation and in the field test that an autonomous vehicle is able to dampen waves generated by 22 cars, and that as a consequence, the total fuel consumption of all vehicles is reduced by up to 20%.

Constructing spatiotemporal speed contour diagrams: using rectangular or non-rectangular parallelogram cells?

Abstract: A spatiotemporal speed contour (SSC, or time-space traffic) diagram that exhibits traffic dynamics in time and space is of importance in transportation research and applications. This paper empiric...

Real-time distance estimation and filtering of vehicle headways for smoothing of traffic waves

Abstract: In this paper we describe an experience report and field deployment of real-time filtering algorithms used with a robotic vehicle to smooth emergent traffic waves. When smoothing these waves in simulation, a common approach is to implement controllers that utilize space gap, relative velocity and even acceleration from smooth ground truth information, rather than from realistic data. As a result, many results may be limited in their impact when considering the dynamics of the vehicle under control and the discretized nature of the laser data as well as its periodic arrival. Our approach discusses trade-offs in estimation accuracy to provide both distance and velocity estimates, with ground-truth hardware-in-the-loop tests with a robotic car. The contribution of the work enabled an experiment with 21 vehicles, including the robotic car closing the loop at up to 8.0 m/s with the filtered estimates, stressing the importance of an algorithm that can deliver real-time results with acceptable accuracy for the safety of the drivers in the experiment.

Design method of length from left turn U-turn intersection to stop line based on traffic wave theory

Abstract: The invention relates to a design method of length from a left turn U-turn intersection to a stop line based on a traffic wave theory. The design method comprises the following steps: acquiring related traffic flow data through a manual counting method, calculating the wave velocity of a concentrated wave at the intersection with intersection left turn traffic volume and left turn traffic densityby utilizing a traffic flow fluctuation theory, finding the maximum queue length of upstream left-turn vehicles according to the distance concentrated and swept by the concentrated wave at the upstream of the intersection and taking the length as the distance from a U-turn lane to the stop line. The design method of the length from the left turn U-turn intersection to the stop line based on the traffic wave theory, provided by the invention, has the benefits that the blank in the design aspect of the length from the left turn U-turn intersection in the U-turn inside the intersection to the stop line is made up, the influence of T-turn vehicles on the left turn vehicles is effectively reduced, the intersection congestion can be reduced, the diversion conflict between left turn U-turn and left turn on a same lane can be reduced as much as possible, the influence of pedestrians on a crosswalk on the left turn U-turn vehicles is reduced, the operation efficiency and the safety of the intersection are improved, and the intersection traffic capacity is improved.

Back to the Future: Predicting Traffic Shockwave Formation and Propagation Using a Convolutional Encoder-Decoder Network

Abstract: This study proposes a deep learning methodology to predict the propagation of traffic shockwaves. The input to the deep neural network is time-space diagram of the study segment, and the output of the network is the predicted (future) propagation of the shockwave on the study segment in the form of time-space diagram. The main feature of the proposed methodology is the ability to extract the features embedded in the time-space diagram to predict the propagation of traffic shockwaves.

Coordinated guidance control method for highway ramps under traffic events

Abstract: The invention discloses a coordinated guidance control method for highway ramps under traffic events, and belongs to the technical field of traffic control. The method includes: (1) obtaining an influence range of a traffic wave during a traffic event time period by using a queuing detector in a VISSIM; (2) determining the number of ramps used for coordinated control according to a ramp number ofa highway and the influence range of the traffic wave; and (3) obtaining the optimal ramp regulation rate by using the combination of a single point and a coordination level and providing path guidance, wherein the density is selected as a control variable at the coordination level, the coordination regulation rate is calculated through a PID control method, and vehicles are diverted to respectiveramps upstream of a congested point according to the weights of reducing inflows. The method uses the combination of an improved Bottleneck control method and a path guidance method based on journeyevents and shows that the vehicle delay at a trunk road can be greatly reduced and the adjustment efficiency is accelerated based on a VISSIM simulation result.

Laboratory Emulator Using Connected Scaled Cars to Study Traffic Waves

Abstract: Traffic density has become one of the substantial problems in urban areas. Saturated roads increase the likelihood of vehicular collisions, mostly since the distance between the cars is decreased significantly. The emerging technology of communication between cars is suggested as an enabling technology to optimize traffic flow control. One solution to improve traffic flow on dense roads is to share kinematic properties among near cars. This could enable drivers or an automated system to get better decisions with respect to following the preceding cars. Control algorithms for cars driving in heavy traffic that considers the velocities, acceleration and spacing of the neighboring vehicles ahead, could eliminate traffic waves and reduce tail to head collisions. The purpose of this work is to design and construct a lab testbed based on scaled electric cars, which are remotely controlled by a PC, and to implement driving algorithms for these cars assuming the kinematic properties of the adjacent cars are known.

Arterial coordination control method based on traffic wave under road section construction area background

Abstract: The invention discloses an arterial coordination control method based on the traffic wave under the road section construction area background. The method includes the following steps of firstly, establishing a traffic wave model capable of reflecting features of a construction area; secondly, calculating parking delay of each crossing under the road section construction area background; thirdly, establishing a dual-target arterial coordination model with the main target of the minimum coordination phase parking delay and the auxiliary target of the minimum crossing parking delay under the constraint condition of no overflow of coordination phase queueing vehicles. Compared with the prior art, the method has the advantages that the influences on the vehicle speed probability distribution, arrival rate and queueing vehicle length and time in the presence of the construction area are sufficiently considered, and the arterial coordination model based on the traffic wave under the road section construction area background is established. By means of the method, the more accurate arterial coordination result is obtained, the traffic delay caused by the construction area is reduced as much as possible, and the traffic capacity of a construction area road section is effectively improved.

Research on Signal Control Method of Isolated Intersection Based on the Queuing Length Reliability

Abstract: Considering the stochastic characteristics of traffic flow at the approach of intersection, a signal control method based on the queuing length reliability is proposed. Firstly, the formula of queuing length is obtained according to the traffic wave theory, and then the signal timing method which satisfies a predetermined queuing length reliability is constructed with the assumption that the traffic flow of intersection approach follows a normal or a lognormal distribution. Finally, some numerical studies are presented to verify the proposed signal timing model.

Method for determining traffic state of urban intersection

Abstract: The invention provides a method for determining a traffic state of an urban intersection. Starting from a traffic wave theory, the method refinedly redefines the boundary of traffic states at an intersection by introducing the concepts of a passing rate, a traffic jam rate, and comprehensive action results, and solves the roughness of the current traffic state discriminant indicators of various intersections. In addition, the method provides a systematic, complete and implementable technical solution from concept description, theoretical characterization and method proposal.

Method for predicting vehicle delay through lane division in real time based on IQA

Abstract: The invention relates to a method for predicting vehicle delay through lane division in real time based on IQA, and belongs to the technical field of intelligent transportation. The invention constructs an IQA delay polygon based on a method for predicting the queue length through lane division in real time and the traffic wave theory, and predicts the vehicle delay through the lane division in real time. By predicting IQA in advance, the defect that the real-time data is difficult to obtain when IQA is used for delay calculation in the past is made up, and the accuracy of the delay calculation is improved. According to the method for predicting vehicle delay through lane division in real time based on IQA, vehicle delay information can be obtained in advance by lane division, and passivedelay estimation is changed into active delay prediction, thereby facilitating the signal optimization design for relevant intersections or crowded roads in advance, so that the purpose of alleviatingthe traffic congestion and improving the travel environment can be achieved.

Factors for enhancing inherent resilience in traffic network

Abstract: The study of the inherent resilience of traffic networks has not received due research attention. The ability of a link or a corridor can be enhanced with design factors. Traffic control means such as adaptive systems can be applied as well and these have been studied in the past and are in use in many cities around the world. However, there has been a general lack of attention to improving inherent resilience with geometric design factors. The paper will consist of five parts. The first part serves as a background. The second part defines a model of traffic service capability and its inputs. The intent is to investigate link and corridor-level means to enhance the inherent resilience in terms of sustained service flow. Specifically, the developed predictive model incorporates geometric factors, volume-delay functions, and operating speed. This model can be used to study service volume changes in relation to selected variables. The third part defines a microsimulation methodology, which enables testing of factors for enhancing inherent resilience. The simulation-based methodology will be described, and the process followed to prepare inputs will be explained. The U.S. Bureau of Public Roads (BPR) equation was used in simulation studies. The fourth part will cover an analysis of simulation outputs. Finally, conclusions are presented. The findings of this research are intended for use by traffic engineers so that traffic networks can be designed and operated with the improved ability of links and corridors to withstand traffic shocks better as compared to the conventional approaches.

Traffic Wave Damping: A Shared Control Approach

Abstract: Traffic waves, also known as “phantom jams”, are caused by the instability of the system describing the dynamics of traffic flow on highways: slight disturbances in the distribution of vehicles on highways are amplified when the density of the traffic is higher than a certain critical value and eventually generate traffic waves and “stop-and-go” phenomena. We propose a solution to the traffic wave damping problem via shared-control on vehicles and show that the effectiveness of the proposed controller does not depend on human drivers' actions. In other terms, with the developed shared-controller the amplitude of the traffic wave is reduced regardless of the action of the drivers. Simulation results on a traffic control benchmark demonstrating the effectiveness of the controller are also provided.

Hybrid bicycle traffic wave calculation method based on spatial awareness

Abstract: The invention relates to a hybrid bicycle traffic wave calculation method based on spatial awareness, and belongs to the technical field of transportation. According to the hybrid bicycle traffic wavecalculation method provided by the invention, by means of a hybrid traffic flow model based on spatial awareness, spatial ratios under different hybrid bicycle traffic states are analyzed, and hybridbicycle density and flow rate are determined, so that a hybrid bicycle traffic wave velocity is calculated through a cellular transmission model. By adoption of the hybrid bicycle traffic wave calculation method provided by the invention, the limitation that the assumption is too ideal when the operation of multi-strand bicycle flow is simulated by the previous methods, such that the isotropic traffic flow phenomenon cannot be better simulated, is overcome, and the hybrid bicycle traffic wave calculation precision is improved.

Back to the Future: Predicting Traffic Shockwave Formation and Propagation Using a Convolutional Encoder-Decoder Network

Abstract: This study proposes a deep learning methodology to predict the propagation of traffic shockwaves. The input to the deep neural network is time-space diagram of the study segment, and the output of the network is the predicted (future) propagation of the shockwave on the study segment in the form of time-space diagram. The main feature of the proposed methodology is the ability to extract the features embedded in the time-space diagram to predict the propagation of traffic shockwaves.