Traffic Status Prediction and Analysis Based on Mining Frequent Subgraph Patterns

2012 ◽  
Vol 605-607 ◽  
pp. 2543-2548
Author(s):  
Gang Xu ◽  
Hai He Jin ◽  
Jing Liu

With the development of the city, the traffic congestion and traffic accidents on the urban road increase frequently. Using traffic modeling and analysis to improve the traffic conditions become more important. Now, using the traffic flow model to study the traffic problems has made many achievements. However, traffic flow model cannot be a good choice for describing the relations of the traffic element at a specific moment, but these relations are indeed significant for forecasting traffic status from that moment on. In this paper, a graph model for the static traffic was studied, and then analyzed the feature of a graph substructure for traffic congestion at one moment. We propose an effective frequent subgraph mining algorithm to find the frequent substructure that represent traffic congestion status in a graph. Our mining algorithm can enhance the efficiency of finding the congestion subgraph. Analyzing the proportion of the congestion subgraph in a graph for traffic to forecast the traffic status at that moment later, thus to find ways to improve traffic conditions.

2003 ◽  
Vol 1852 (1) ◽  
pp. 183-192
Author(s):  
W. L. Jin ◽  
H. M. Zhang

Results are presented from a recent study on a variation of a new non-equilibrium continuum traffic flow model in which traffic sound speed is constant. Hence this model is called the frozen-wave model. This model resembles the Payne–Whitham model but avoids the “back-traveling” of the latter. For this frozen-wave model, the Riemann problem is analyzed for its homogeneous system, two numerical solution methods are developed to solve it, and numerical simulations are carried out under both stable and unstable traffic conditions. These results show that under stable conditions, the model behaves similarly to the Payne–Whitham model. However, under unstable traffic conditions, it has nonphysical solutions or no solutions when a vacuum problem occurs. This study, on the one hand, provides a more complete picture of the properties of this frozen-wave model and reduces the risk of improper applications of it. On the other hand, it also highlights the need to adopt a density-dependent sound speed.


2018 ◽  
Vol 10 (12) ◽  
pp. 4694 ◽  
Author(s):  
Xiang Wang ◽  
Po Zhao ◽  
Yanyun Tao

Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management strategies. We propose a multi-class traffic flow model based on Smulders fundamental diagram to analyze the influence of overloaded HVs on traffic conditions. The relationship between the overloading ratio and maximum speed is established by freeway toll collection data for different types of HVs. Dynamic passenger car equivalent factors are introduced to represent the various impacts of overloaded HVs in different traffic flow patterns. The model is solved analytically and discussed in detail in the appendices. The model validation results show that the proposed model can represent traffic conditions more accurately with consideration for overloaded HVs. The scenario tests indicate that the increase of overloaded HVs leads to both a higher congestion level and longer duration.


Author(s):  
Delina Mshai Mwalimo ◽  
Mary Wainaina ◽  
Winnie Kaluki

This study outlines the Kerner’s 3 phase traffic flow theory, which states that traffic flow occurs in three phases and these are free flow, synchronized flow and wide moving jam phase. A macroscopic traffic model that is factoring road inclination is developed and its features discussed. By construction of the solution to the Rienmann problem, the model is written in conservative form and solved numerically. Using the Lax-Friedrichs method and going ahead to simulate traffic flow on an inclined multi lane road. The dynamics of traffic flow involving cars(fast moving) and trucks(slow moving) on a multi-lane inclined road is studied. Generally, trucks move slower than cars and their speed is significantly reduced when they are moving uphill on an in- clined road, which leads to emergence of a moving bottleneck. If the inclined road is multi-lane then the cars will tend to change lanes with the aim of overtaking the slow moving bottleneck to achieve free flow. The moving bottleneck and lanechange ma- noeuvres affect the dynamics of flow of traffic on the multi-lane road, leading to traffic phase transitions between free flow (F) and synchronised flow(S). Therefore, in order to adequately describe this kind of traffic flow, a model should incorporate the effect of road inclination. This study proposes to account for the road inclination through the fundamental diagram, which relates traffic flow rate to traffic density and ultimately through the anticipation term in the velocity dynamics equation of macroscopic traffic flow model. The features of this model shows how the moving bottleneck and an incline multilane road affects traffic transistions from Free flow(F) to Synchronised flow(S). For a better traffic management and control, proper understanding of traffic congestion is needed. This will help road designers and traffic engineers to verify whether traffic properties and characteristics such as speed(velocity), density and flow among others determines the effectiveness of traffic flow.


Author(s):  
Anargiros I. Delis ◽  
Ioannis K. Nikolos ◽  
Markos Papageorgiou

An extended second-order macroscopic traffic flow model is presented that describes multi-lane traffic dynamics and also incorporates the effects of adaptive cruise control (ACC) or cooperative ACC (CACC). The extended model equations stem from a recently proposed multi-lane gas-kinetic traffic flow (GKT) model that can simulate lane changes due to vehicle interactions as well as spontaneous ones. The proposed extension that models the effects of ACC/CACC satisfies the time-gap principle of such systems on each lane and allows for consideration of mixed traffic comprising both manual and ACC/CACC vehicles. Numerical simulations are performed for a particular three-lane motorway stretch in the United Kingdom, where recurrent traffic congestion is observed during the morning peak hours, so as to compare the effects of ACC/CACC in the traffic flow conditions with those resulting from manual driving.


CICTP 2020 ◽  
2020 ◽  
Author(s):  
Lidong Zhang ◽  
Wenxing Zhu ◽  
Mengmeng Zhang ◽  
Cuijiao Chen

Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi

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.


Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3425
Author(s):  
Huanping Li ◽  
Jian Wang ◽  
Guopeng Bai ◽  
Xiaowei Hu

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.


2021 ◽  
Vol 94 ◽  
pp. 369-387
Author(s):  
Weilin Ren ◽  
Rongjun Cheng ◽  
Hongxia Ge

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Yingdong Liu

A one-dimensional cellular automaton traffic flow model, which considers the deceleration in advance, is addressed in this paper. The model reflects the situation in the real traffic that drivers usually adjust the current velocity by forecasting its velocities in a short time of future, in order to avoid the sharp deceleration. The fundamental diagram obtained by simulation shows the ability of this model to capture the essential features of traffic flow, for example, synchronized flow, meta-stable state, and phase separation at the high density. Contrasting with the simulation results of the VE model, this model shows a higher maximum flux closer to the measured data, more stability, more efficient dissolving blockage, lower vehicle deceleration, and more reasonable distribution of vehicles. The results indicate that advanced deceleration has an important impact on traffic flow, and this model has some practical significance as the result matching to the actual situation.


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