scholarly journals Regional Boundary Control of Traffic Network Based on MFD and FR-PID

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xin Yang ◽  
Juncheng Chen ◽  
Mantun Yan ◽  
Zhao He ◽  
Ziyan Qin ◽  
...  
Keyword(s):  
Boundary Control ◽  
Traffic Safety ◽  
Pid Control ◽  
Traffic Congestion ◽  
Road Network ◽  
Traffic Accidents ◽  
Urban Traffic ◽  
Traffic Network ◽  
The Road ◽  
Regional Boundary

In recent years, urban traffic congestion has become more serious and the capacity of roads has declined, resulting in frequent traffic accidents. In order to effectively alleviate the traffic congestion of the regional road network, aiming at the problem of lack of accurate OD data of the road network, a regional boundary control method of the traffic network based on fuzzy RBF neural network PID (FR-PID) is proposed by combining the theory of macroscopic fundamental diagram (MFD). Firstly, based on the traffic survey, the simulation model of the study area is built, and the basic data such as the traffic flow and the time occupation rate of each road section are obtained. Secondly, the simulation data are used to test the existence of MFD in the road network, and the controlled area is defined. Then, the vehicle change model of the road network area is established. Then, in view of the problem of poor adaptive ability of traditional PID control, the FR-PID control structure is designed. Finally, an example is verified by VISSIM software. In the simulation, different control methods are used for comparison and verification, and the simulation results are analyzed. The results show that the control effect of the proposed method is better than that of the traditional method, and the regional average accumulative vehicle number, regional average completed volume, regional accumulative delays, and total vehicle travel time are optimized by 28.21%, 41.19%, 27.06%, and 32.73%, respectively. The research results can provide reference for the management of urban congestion, thereby reducing the number of traffic accidents and improving urban traffic safety.

Taxi Global Positioning System Data in Urban Road Network: A Methodology to Identify Key Road Clusters Based on Travel Speed–Traffic Volume Correlation

2021 ◽  
pp. 036119812110366
Author(s):  
Yi Li ◽  
Weifeng Li ◽  
Qing Yu ◽  
Han Yang
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Travel Speed ◽  
Detection Algorithm ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Mitigation Strategies ◽  
Operating Characteristics ◽  
The Road ◽  
Road Segments

Urban traffic congestion is one of the urban diseases that needs to be solved urgently. Research has already found that a few road segments can significantly influence the overall operation of the road network. Traditional congestion mitigation strategies mainly focus on the topological structure and the transport performance of each single key road segment. However, the propagation characteristics of congestion indicate that the interaction between road segments and the correlation between travel speed and traffic volume should also be considered. The definition is proposed for “key road cluster” as a group of road segments with strong correlation and spatial compactness. A methodology is proposed to identify key road clusters in the network and understand the operating characteristics of key road clusters. Considering the correlation between travel speed and traffic volume, a unidirectional-weighted correlation network is constructed. The community detection algorithm is applied to partition road segments into key road clusters. Three indexes are used to evaluate and describe the characteristic of these road clusters, including sensitivity, importance, and IS. A case study is carried out using taxi GPS data of Shanghai, China, from May 1 to 17, 2019. A total of 44 key road clusters are identified in the road network. According to their spatial distribution patterns, these key road clusters can be classified into three types—along with network skeletons, around transportation hubs, and near bridges. The methodology unveils the mechanism of congestion formation and propagation, which can offer significant support for traffic management.

scholarly journals Road Traffic Safety Analysis Of Different Junction Types On The State Roads

2021 ◽  
Vol 1202 (1) ◽  
pp. 012034
Author(s):  
Valentina Amare ◽  
Juris Smirnovs
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Accidents ◽  
The Road ◽  
Road Traffic Safety ◽  
Road Capacity ◽  
On The Road ◽  
The Impact

Abstract The highest number of road accidents occurs at junctions. One of the aims of traffic organisation is to improve traffic safety in these areas. Based on a variety of indices – road capacity, points of conflict, number, and severity of road traffic accidents – different alternatives for junctions are evaluated. However, the road network has many junctions and roads serve to travel from point "A" to point "B" at a given time. Therefore, one of the most important tasks when addressing the issue of road safety is to find a rational way of improving the safety without losing the importance of the road. The aim of this paper is to analyse the impact of different junctions on the road network and basing on actual data develop a method for the evaluation of different types of junctions with respect to road class.

scholarly journals Road Network Pre-partitioning Method with Priority for Congestion Control

2019 ◽  
pp. 1-13
Author(s):  
Hao She ◽  
Xingsheng Xie
Keyword(s):  
Congestion Control ◽  
Traffic Congestion ◽  
Spectral Clustering ◽  
Road Network ◽  
Control Area ◽  
Urban Traffic ◽  
The Road ◽  
Traffic Efficiency ◽  
Svm Model ◽  
Partition Method

Urban traffic congestion seriously affects the traffic efficiency, causing travel delays and resources wasted directly. In this paper, a road network pre-partitioning method with priority for congestion control is proposed to reduce traffic congestion. Traffic flow feature is extracted based on CNN, and the estimated accuracy of intersection reach 95.32% through CNN-SVM model. Subarea congestion coefficient and intersection merger coefficient are defined to expand the control area of congestion coordination. The association and similarity of intersections are considered using spectral clustering for non-congested intersection partitioning. The results show that the congestion priority control partition method reduces a congestion intersection compared to directly using spectral clustering for subarea partition, and reduces the road network congestion coefficient by 0.05 after 30 minutes than directly using spectral clustering, which is an effective subarea partition method.  

Understanding structure of urban traffic network based on spatial-temporal correlation analysis

2017 ◽  
Vol 31 (22) ◽  
pp. 1750230 ◽  
Author(s):  
Yanfang Yang ◽  
Limin Jia ◽  
Yong Qin ◽  
Shixiu Han ◽  
Honghui Dong
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Structural Characteristics ◽  
Small World ◽  
Temporal Correlation ◽  
Urban Traffic ◽  
Utilization Rate ◽  
Traffic Network ◽  
Pagerank Algorithm ◽  
Urban Traffic Network

Understanding the structural characteristics of urban traffic network comprehensively can provide references for improving road utilization rate and alleviating traffic congestion. This paper focuses on the spatial-temporal correlations between different pairs of traffic series and proposes a complex network-based method of constructing the urban traffic network. In the network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding spatial-temporal correlation. Further, a modified PageRank algorithm, named the geographical weight-based PageRank algorithm (GWPA), is proposed to analyze the spatial distribution of important segments in the road network. Finally, experiments are conducted by using three kinds of traffic series collected from the urban road network in Beijing. Experimental results show that the urban traffic networks constructed by three traffic variables all indicate both small-world and scale-free characteristics. Compared with the results of PageRank algorithm, GWPA is proved to be valid in evaluating the importance of segments and identifying the important segments with small degree.

scholarly journals ESTABLISHMENT OF CAUSE AND EFFECT RELATIONSHIP BETWEEN IMPROPER ARRANGEMENT OF TRAFFIC MANAGEMENT FACILITIES AND TRAFFIC ACCIDENTS OCCURRENCE

2020 ◽  
Vol 21 (1) ◽  
pp. 432-440
Author(s):  
V. Olkhov
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Traffic Accidents ◽  
Road Accident ◽  
Road Accidents ◽  
Forensic Investigation ◽  
Criminal Proceedings ◽  
Effect Relationship ◽  
Cause And Effect ◽  
The Road

The daunting issues arising at experts and forensic bodies when appointing and conducting comprehensive road and pavement forensic investigation and road accident analysis (forensic expert examination) are considered. Types of traffic accidents provided by the statistics of the Department of Patrol Police of Ukraine are analyzed. A number of road accidents with victims committed in conditions of the road and settlements streets unsatisfactory state is defined.   More and more judicial and investigative bodies turn to forensic science institutes, in particular to KhRIFE, in order to determine whether the improper design of the road network affected the occurrence of an accident. In other words, the questions not only on the establishment of improper design of the road section where the accident occurred, but also on the existence of cause and effect relationship between the identified discrepancies and the accident are advanced for examination. The study of the above issues belongs to the forensic specialty 10.16 Road and Pavement Forensic Investigation. The demand for forensic research of improper design of the road network and the causes of accidents are constantly growing. At the same time, the practice of conducting road and pavement forensic investigation, namely the analysis of the materials provided for the study, shows that most criminal proceedings are investigated both while pre-trial investigation and in court for violation of traffic safety rules or transport operation by persons who drive vehicles. In the statistical report of the Department of Patrol Police of Ukraine, the data of road accidents are not classified as those that arose due to improper condition of roads and streets of settlements, and when conducting road and pavement forensic investigation it is established that improper design of the road network is in cause and effect relationship with the occurrence of an accident from a technical point of view.

SOME TRAFFIC SAFETY ISSUES AT UNREGULATED PEDESTRIAN CROSSINGS IN THE CITY

2021 ◽  
Vol 5 (12(81)) ◽  
pp. 26-32
Author(s):  
V. Volkov ◽  
E. Nabatnikova ◽  
E. Lebedev
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Hourly Interval ◽  
Safety Issues ◽  
The Road ◽  
Probability Estimates ◽  
Mode Of Transport ◽  
Speed Mode

The groups of participants of the pedestrian and automobile flows, whose actions cause the greatest danger to the occurrence of conflict situations in the zone of unregulated transition, are identified. The factors determining the likelihood of a traffic accident at an unregulated transition are systematized, for which probability estimates of the occurrence of road traffic accidents are calculated. As an estimated parameter, the hazard coefficient of a conflict point of an unregulated transition is proposed, which is determined by the ratio of the probability of a traffic accident in the real-time hourly interval to the average annual probability of a traffic accident reduced to the hourly interval. The dependences of the hazard ratio of an unregulated transition are established on the most significant factors: the speed mode of transport in the area before the transition and the state of the road surface.

Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network

2022 ◽  
Vol 13 (2) ◽  
pp. 1-25
Author(s):  
Bin Lu ◽  
Xiaoying Gan ◽  
Haiming Jin ◽  
Luoyi Fu ◽  
Xinbing Wang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Large Scale ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Propagation Mechanism ◽  
Urban Road ◽  
The Road ◽  
Traffic Flow Forecasting ◽  
Gating Mechanism

Urban traffic flow forecasting is a critical issue in intelligent transportation systems. Due to the complexity and uncertainty of urban road conditions, how to capture the dynamic spatiotemporal correlation and make accurate predictions is very challenging. In most of existing works, urban road network is often modeled as a fixed graph based on local proximity. However, such modeling is not sufficient to describe the dynamics of the road network and capture the global contextual information. In this paper, we consider constructing the road network as a dynamic weighted graph through attention mechanism. Furthermore, we propose to seek both spatial neighbors and semantic neighbors to make more connections between road nodes. We propose a novel Spatiotemporal Adaptive Gated Graph Convolution Network ( STAG-GCN ) to predict traffic conditions for several time steps ahead. STAG-GCN mainly consists of two major components: (1) multivariate self-attention Temporal Convolution Network ( TCN ) is utilized to capture local and long-range temporal dependencies across recent, daily-periodic and weekly-periodic observations; (2) mix-hop AG-GCN extracts selective spatial and semantic dependencies within multi-layer stacking through adaptive graph gating mechanism and mix-hop propagation mechanism. The output of different components are weighted fused to generate the final prediction results. Extensive experiments on two real-world large scale urban traffic dataset have verified the effectiveness, and the multi-step forecasting performance of our proposed models outperforms the state-of-the-art baselines.

scholarly journals Macroscopic dynamics and the collapse of urban traffic

2018 ◽  
Vol 115 (50) ◽  
pp. 12654-12661 ◽  
Author(s):  
Luis E. Olmos ◽  
Serdar Çolak ◽  
Sajjad Shafiei ◽  
Meead Saberi ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Spatial Dynamics ◽  
Urban Traffic ◽  
Nonequilibrium Phase Transition ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Road Capacity ◽  
Total Vehicle ◽  
The Individual

Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the individual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ, defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.

Regression Analysis of Rural Road Traffic Accidents Causes

2011 ◽  
Vol 97-98 ◽  
pp. 1042-1045 ◽  
Author(s):  
Chuan Jiao Sun ◽  
Ru Yue Bai ◽  
Yuan Yuan Yu
Keyword(s):  
Regression Analysis ◽  
Traffic Safety ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Lower Grade ◽  
The Road ◽  
Rural Road ◽  
Safety Awareness

9238 traffic accidents data are collected in rural road of China. Through the data analysis, the main causes of rural road traffic accident are presented. The external environment, the participant features, road features and accident characteristics are involved. The regression analysis in SPSS is applied to find the relationship between the accident features. Overall, the rural road traffic accident was mainly due to in the rural area there are mass travel mode, lower grade roads, poorer safety awareness of traveler and the road is lack of traffic safety facilities and so on.

scholarly journals The Effects of Picking Up Primary School Pupils on Surrounding Street’s Traffic: A Case Study in Hanoi

2020 ◽  
Vol 14 (1) ◽  
pp. 237-250
Author(s):  
Dinh Hiep ◽  
Vu V. Huy ◽  
Teppei Kato ◽  
Aya Kojima ◽  
Hisashi Kubota
Keyword(s):  
Primary School ◽  
Traffic Safety ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Primary Schools ◽  
Traffic Accidents ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Almost All

Introduction: One of the significant characteristics of schools in Vietnam is that almost all parents send their children to school and/or pick up their children from school using private vehicles (motorcycles). The parents usually stop and park their vehicle on streets outside the school gates, which can lead to serious congestion and increases the likelihood of traffic accidents. Methods: The objective of this study is to find out factors affecting the picking up of pupils at primary school by evaluating the typical primary schools in Hanoi city. A binary logistic regression model was used to determine factors that influence the decision of picking up pupils and the waiting duration of parents. The behavior of motorcyclists during the process of picking up pupils at the primary school gate has been identified and analyzed in detail by the Kinovea software. Results and Discussion: The study showed that, on the way back home, almost all parents use motorbikes (89.15%) to pick up their children. During their waiting time (8.48 minutes in average), they made a lot of illegal parking actions on the street there by, causing a lot of “cognitive” errors and “crash” points surrounding in front of the primary school entrance gate. Risky picking-up behaviors were significantly observed, i.e. picking-up on opposite side of the school, making a U-turn, backing-up dangerously, parking on the middle of street, and parking on the street next to sidewalk). Conclusion: Based on the analyzed results, several traffic management measures have been suggested to enhance traffic safety and reduce traffic congestion in front of school gates. In addition, the results of the study will provide a useful reference for policymakers and authorities.

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