scholarly journals Cooperative Adaptive Driving for Platooning Autonomous Self Driving Based on Edge Computing

2019 ◽  
Vol 29 (2) ◽  
pp. 213-225 ◽  
Author(s):  
Ben-Jye Chang ◽  
Ren-Hung Hwang ◽  
Yueh-Lin Tsai ◽  
Bo-Han Yu ◽  
Ying-Hsin Liang
Keyword(s):  
Shock Waves ◽  
Traffic Flow ◽  
Road Traffic ◽  
Edge Computing ◽  
Traffic Information ◽  
Velocity Variation ◽  
Traffic Density ◽  
Cruise Control ◽  
Safe Driving ◽  
Butterfly Effect

Abstract Cooperative adaptive cruise control (CACC) for human and autonomous self-driving aims to achieve active safe driving that avoids vehicle accidents or traffic jam by exchanging the road traffic information (e.g., traffic flow, traffic density, velocity variation, etc.) among neighbor vehicles. However, in CACC, the butterfly effect is encountered while exhibiting asynchronous brakes that easily lead to backward shock-waves and are difficult to remove. Several critical issues should be addressed in CACC, including (i) difficulties with adaptive steering of the inter-vehicle distances among neighbor vehicles and the vehicle speed, (ii) the butterfly effect, (iii) unstable vehicle traffic flow, etc. To address the above issues in CACC, this paper proposes the mobile edge computing-based vehicular cloud of the cooperative adaptive driving (CAD) approach to avoid shock-waves efficiently in platoon driving. Numerical results demonstrate that the CAD approach outperforms the compared techniques in the number of shock-waves, average vehicle velocity, average travel time and time to collision (TTC). Additionally, the adaptive platoon length is determined according to the traffic information gathered from the global and local clouds.

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

scholarly journals DEVELOPMENT OF WEBGIS BASED REAL TIME ROAD TRAFFIC INFORMATION SYSTEM

2018 ◽  
Vol IV-5 ◽  
pp. 37-45
Author(s):  
H. Shankar ◽  
M. Sharma ◽  
K. Oberai ◽  
S. Saran
Keyword(s):  
Information System ◽  
Real Time ◽  
Traffic Congestion ◽  
Road Traffic ◽  
Transportation Cost ◽  
Traffic Information ◽  
Traffic Density ◽  
Vehicle To Vehicle ◽  
Decision Making Processes ◽  
Inductive Loop Detector

<p><strong>Abstract.</strong> Rapid increase in road traffic density results into a serious problem of Traffic Congestion (TC) in cities. During peaks hours TC is very high and hence public search least congested path for their journeys in order to minimize ravel time and hence transportation cost. In this study, a new empirical model was developed to estimate congestion levels using real time road Traffic Parameters (TPs) such as vehicle density, speed, class and vehicle-to-vehicle (V2V) gap. These real time road TPs were collected using latest generation Inductive Loop Detector (ILD) technology. Further, a WebGIS based Road Traffic Information System (RTIS) for Dehradun city was developed for real time TD analyses and visualisation. This RTIS is very useful for public and user departments for planning and decision making processes. No other such system is available in India, which handles multiple traffic parameters simultaneously to provide solution of day-to-day problems.</p>

Intelligent Cruise Control Systems and Traffic Flow Behavior

1999 ◽  
Author(s):  
Darbha Swaroop ◽  
K. R. Rajagopal
Keyword(s):  
Control Systems ◽  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Flow Behavior ◽  
Flow Stability ◽  
Traffic Density ◽  
Cruise Control ◽  
String Stability ◽  
Control Laws ◽  
Traffic Flow Stability

Abstract In analogy to the flow of fluids, it is expected that the aggregate density and the velocity of vehicles in a section of a freeway adequately describe the traffic flow dynamics. The conservation of mass equation together with the aggregation of the vehicle following dynamics of controlled vehicles describes the evolution of the traffic density and the aggregate speed of a traffic flow. There are two kinds of stability associated with traffic flow problems — string stability (or car-following stability) and traffic flow stability. We make a clear distinction between traffic flow stability and string stability, and such a distinction has not been recognized in the literature, thus far. String stability is stability with respect to intervehicular spacing; intuitively, it ensures the knowledge of the position and velocity of every vehicle in the traffic, within reasonable bounds of error, from the knowledge of the position and velocity of a vehicle in the traffic. String stability is analyzed without adding vehicles to or removing vehicles from the traffic. On the other hand, traffic flow stability deals with the evolution of traffic velocity and density in response to the addition and/or removal of vehicles from the flow. Traffic flow stability can be guaranteed only if the velocity and density solutions of the coupled set of equations is stable, i.e., only if stability with respect to automatic vehicle following and stability with respect to density evolution is guaranteed. Therefore, the flow stability and critical capacity of any section of a highway is dependent not only on the vehicle following control laws and the information used in their synthesis, but also on the spacing policy employed by the control system. Such a dependence has practical consequences in the choice of a spacing policy for adaptive cruise control laws and on the stability of the traffic flow consisting of vehicles equipped with adaptive cruise control features on the existing and future highways. This critical dependence is the subject of investigation in this paper. This problem is analyzed in two steps: The first step is to understand the effect of spacing policy employed by the Intelligent Cruise Control (ICC) systems on traffic flow stability. The second step is to understand how the dynamics of ICC system affects traffic flow stability. Using such an analysis, it is shown that cruise control systems that employ a constant time headway policy lead to unacceptable characteristics for the traffic flows.

scholarly journals Analysis of a Novel Two-Dimensional Lattice Hydrodynamic Model Considering Predictive Effect

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2464
Author(s):  
Huimin Liu ◽  
Rongjun Cheng ◽  
Tingliu Xu
Keyword(s):  
Traffic Flow ◽  
Hydrodynamic Model ◽  
Traffic Information ◽  
Traffic Density ◽  
Two Dimensional ◽  
Lattice Hydrodynamic Model ◽  
Traffic Condition ◽  
Dimensional Lattice ◽  
The Stability ◽  
Predictive Effect

In actual driving, the driver can estimate the traffic condition ahead at the next moment in terms of the current traffic information, which describes the driver’s predictive effect. Due to this factor, a novel two-dimensional lattice hydrodynamic model considering a driver’s predictive effect is proposed in this paper. The stability condition of the novel model is obtained by performing the linear stability analysis method, and the phase diagram between the driver’s sensitivity coefficient and traffic density is drawn. The nonlinear analysis of the model is conducted and the kink-antikink of modified Korteweg-de Vries (mKdV) equation is derived, which describes the propagation characteristics of the traffic density flow waves near the critical point. The numerical simulation is executed to explore how the driver’s predictive effect affects the traffic flow stability. Numerical results coincide well with theoretical analysis results, which indicates that the predictive effect of drivers can effectively avoid traffic congestion and the fraction of eastbound cars can also improve the stability of traffic flow to a certain extent.

A MODIFIED CELLULAR AUTOMATON MODEL FOR RING ROAD TRAFFIC WITH VELOCITY GUIDANCE

2009 ◽  
Vol 20 (05) ◽  
pp. 711-719 ◽  
Author(s):  
C. Q. MEI ◽  
H. J. HUANG ◽  
T. Q. TANG
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Road Traffic ◽  
Red Light ◽  
Cellular Automaton Model ◽  
Traffic Density ◽  
Traffic Light ◽  
Ring Road ◽  
Detector Position ◽  
Simulation Results

We present a modified cellular automaton model to study the traffic flow on a signal controlled ring road with velocity guidance. The velocity guidance is such a strategy that when vehicles approach the traffic light, suggested velocities are provided for avoiding the vehicles' sharp brakes in front of red light. Simulation results show that this strategy may significantly reduce the vehicles' stopping rate and the effect size is dependent upon the traffic density, the detector position, the signal's cycle time and the obedience rate of vehicles to the guidance.

scholarly journals Speed-Density Model of Interrupted Traffic Flow Based on Coil Data

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Chen Yu ◽  
Jiajie Zhang ◽  
Dezhong Yao ◽  
Ruiguo Zhang ◽  
Hai Jin
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Road Traffic ◽  
Flow Analysis ◽  
Density Model ◽  
Upper And Lower Bounds ◽  
Traffic Density ◽  
Density Relationship ◽  
Speed Fluctuation ◽  
The Impact

As a fundamental traffic diagram, the speed-density relationship can provide a solid foundation for traffic flow analysis and efficient traffic management. Because of the change in modern travel modes, the dramatic increase in the number of vehicles and traffic density, and the impact of traffic signals and other factors, vehicles change velocity frequently, which means that a speed-density model based on uninterrupted traffic flow is not suitable for interrupted traffic flow. Based on the coil data of urban roads in Wuhan, China, a new method which can accurately describe the speed-density relation of interrupted traffic flow is proposed for speed fluctuation characteristics. The model of upper and lower bounds of critical values obtained by fitting the data of the coils on urban roads can accurately and intuitively describe the state of urban road traffic, and the physical meaning of each parameter plays an important role in the prediction and analysis of such traffic.

LWR Model for Traffic Flow Mixed with CACC Vehicles

2021 ◽  
Author(s):  
Yanyan Qin ◽  
Hao Wang ◽  
Daiheng Ni
Keyword(s):  
Shock Waves ◽  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Small Perturbations ◽  
Car Following ◽  
Lwr Model ◽  
And Shock Waves ◽  
Generalized Framework ◽  
The Impact

In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.

scholarly journals An Analysis of the Catastrophe Model and Catastrophe Characteristics of Traffic Flow Based on Cusp Catastrophe Theory

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Yanguo Huang ◽  
Huiming Zhang ◽  
Hongjun Liu ◽  
Shengsheng Zhang
Keyword(s):  
Traffic Flow ◽  
Catastrophe Theory ◽  
Wave Speed ◽  
Road Traffic ◽  
Traffic Density ◽  
Cusp Catastrophe ◽  
Flow State ◽  
Analysis Method ◽  
Urban Road ◽  
Catastrophe Model

—The state of urban road traffic flow shows discontinuity and jumping phenomenon in the process of running. There was a data gap in the collected traffic flow data. Through the data analysis, it was found that the traffic flow state had the characteristics of multimode, mutation, inaccessibility, divergence and hysteresis, which were similar to the mutation characteristics of the basic model of catastrophe theory when the system state changed. The cusp catastrophe model of traffic flow based on traffic wave theory was established by analyzing the movement process of traffic flow. In this model, the traffic density was taken as the state variable, and traffic flow and wave speed were taken as the control variable. Referring to the basic idea of catastrophe theory, the solution method of the model was given, and the structural stability of the traffic flow state was analyzed. Through the critical equilibrium surface equation, the stability of the extreme value of the system potential function can be analyzed, and the bifurcation set equation when the traffic flow state changed can be obtained, which can be used to determine the critical range of the structural stability of the system. This paper discussed and analyzed the changing trend and constraint relationship among the wave speed, traffic density and traffic flow when the traffic flow state changed suddenly in different running environments. The analysis results were consistent with the actual road traffic flow state. A case was given, and the results showed that the cusp catastrophe model could describe the relationship among the three parameters of traffic flow from three-dimensional space, and could effectively analyze the internal relationship of the parameters when the traffic flow state changed. The validity of the model and analysis method was verified. The goal of this paper is to provide an analysis method for the judgment of urban road traffic state.

scholarly journals Characteristic Analysis of Mixed Traffic Flow of Regular and Autonomous Vehicles Using Cellular Automata

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Yangzexi Liu ◽  
Jingqiu Guo ◽  
John Taplin ◽  
Yibing Wang
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Road Traffic ◽  
Penetration Rate ◽  
Heterogeneous Traffic ◽  
Transport Systems ◽  
Traffic Density ◽  
Characteristic Analysis ◽  
Lane Changing ◽  
Car Following

The technology of autonomous vehicles is expected to revolutionize the operation of road transport systems. The penetration rate of autonomous vehicles will be low at the early stage of their deployment. It is a challenge to explore the effects of autonomous vehicles and their penetration on heterogeneous traffic flow dynamics. This paper aims to investigate this issue. An improved cellular automaton was employed as the modeling platform for our study. In particular, two sets of rules for lane changing were designed to address mild and aggressive lane changing behavior. With extensive simulation studies, we obtained some promising results. First, the introduction of autonomous vehicles to road traffic could considerably improve traffic flow, particularly the road capacity and free-flow speed. And the level of improvement increases with the penetration rate. Second, the lane-changing frequency between neighboring lanes evolves with traffic density along a fundamental-diagram-like curve. Third, the impacts of autonomous vehicles on the collective traffic flow characteristics are mainly related to their smart maneuvers in lane changing and car following, and it seems that the car-following impact is more pronounced.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

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