scholarly journals AN INTEGRATED NETWORK-CONSTRAINED SPATIAL ANALYSIS FOR CAR ACCIDENTS: A CASE STUDY OF TEHRAN CITY, IRAN

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 335-342
Author(s):  
S. A. EslamiNezhad ◽  
M. R. Delavar
Keyword(s):  
Road Network ◽  
Statistical Parameter ◽  
Kernel Functions ◽  
Urban Traffic ◽  
Point Pattern ◽  
One Dimensional ◽  
The Road ◽  
Car Accidents ◽  
The One ◽  
Car Accident

Abstract. Research on determination of spatial patterns in urban car accidents plays an important role in improving urban traffic safety. While traditional methods of spatial clustering of car accidents mostly rely on the two dimensional assumption, many spatial events defy this assumption. For instance, car accidents are constrained by the road network and rely on the one dimensional assumption of street network. The aim of this study is to detect and statistically prioritize the car accident-prone segments of an urban road network by a network-based point pattern analysis. The first step involves estimating the density of car accidents in the one dimensional space of the road network using the network kernel density estimation (NKDE) method with equal-split continuous and discontinuous kernel functions. In the second step, due to the lack of statistical prioritization of the accident-prone segments with NKDE method, the output of the NKDE method is integrated with network-constrained Getis-Ord Gi* statistics to measure and compare the accident-prone segments based on the statistical parameter of Z-Score. The integration of these two methods can improve identification of accident-prone segments which is effective in the enhancing of urban safety and sustainability. These methods were tested using the data of damage car accidents in Tehran District 3 during 2013–2017. We also performed the Network K-Function to display the significant clustering of damage car accident points in the network space at different scales. The results have demonstrated that the damage car accidents are significantly clustered.

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.

scholarly journals Determination of Reserves for Reducing Delays and Increasing the Capacity of the Street-Road Network in Gomel as a Factor of Reducing Losses in Traffic

2021 ◽  
pp. 65-72
Author(s):  
D. P. Khodoskin
Keyword(s):  
Road Network ◽  
Urban Traffic ◽  
Economic Losses ◽  
Value Assessment ◽  
Large Cities ◽  
The Road ◽  
Car Traffic ◽  
Traffic Capacity ◽  
Real Objects ◽  
Time Expenditures

Purpose. Often, the existing level of traffic capacity of road network facilities in large cities is insufficient. This is often due to the fact that urban growth is significantly ahead of the reconstruction and renovation of the corresponding infrastructure. As a result, traffic delays of various kinds occur on city roads, accompanied, first of all, by economic losses. Therefore, the search for reserves to reduce various types of losses associated with insufficient traffic capacity of the road network when organizing urban traffic is the purpose of this work. Methodology To determine the reserves for increasing the traffic capacity of the road network and reducing various kinds of delays, the method of deterministic analysis was used, the method for calculating the cycle according to F. Webster, based on the use of phase coefficients and time lost in the cycle (as the sum of transient intervals), the method for measuring the intensity of car traffic in the traffic flow, as well as the methodology for calculating economic losses arising from delays in the movement of vehicles. Findings. A study of delays and time expenditures and the corresponding economic losses that occur at typical objects of the city's street-road network (regulated intersections) has been carried out. The reserves of their reduction, and as a consequence, the increase in the capacity of both individual sections and the city's road network as a whole, have been determined. Originality. The use of this method on real objects of the road network allows developing the scientific interpretation of the methods used and expanding the scope of their application. Practical value. Assessment of emerging problems of traffic capacity and associated losses (including economic ones) makes it possible to determine the most promising ways to determine the traffic capacity reserves and, as a result, reduce economic losses.

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 Studi Simulasi Model Kecelakaan Pengendara Mobil untuk Meningkatkan Keselamatan Lalu Lintas di Daerah Perkotaan

2020 ◽  
Vol 32 (2) ◽  
Author(s):  
Imma Widyawati Agustin ◽  
Christia Meidiana ◽  
Sri Muljaningsih
Keyword(s):  
Linear Model ◽  
Traffic Safety ◽  
Generalized Linear Model ◽  
Probability Model ◽  
Seat Belt ◽  
Traffic Density ◽  
The Road ◽  
Car Accidents ◽  
Road Width ◽  
Car Accident

AbstrakBerbagai permasalahan transportasi yang sering dialami dengan kepadatan lalu lintas yang tinggi salah satunya adalah kecelakaan lalu lintas. Kecelakaan lalu lintas di Kota Surabaya pada tahun 2017 tercatat sebanyak 1.338 kejadian kecelakaan. Jumlah kejadian kecelakaan ini didominasi oleh kendaraan pribadi seperti sepeda motor dan mobil. Penelitian ini bertujuan membuat model peluang kecelakaan mobil di Kota Surabaya yang didasarkan pada data karakteristik jalan dan karakteristik pengendara untuk mengetahui tindakan yang tepat dalam menurunkan angka kecelakaan mobil. Metode yang digunakan dalam penelitian ini adalah analisis generalized linear model (GLM) untuk melihat model peluang kecelakaan mobil berdasarkan karakteristik jalan dan regresi logistik biner untuk melihat model peluang kecelakaan mobil berdasarkan karakteristik pengendara mobil. Penelitian ini difokuskan pada six ruas jalan yang memiliki tingkat kecelakaan tertinggi dan sedang, serta diwakilkan dengan 348 responden pengendara mobil. Dari hasil analisis GLM didapatkan model peluang kecelakaan McA = 𝑒𝑒4,5 − 0,707 Lebar badan jalan yang menunjukkan bahwa hanya lebar badan jalan yang mempengaruhi peluang kecelakaan mobil. Hal ini dapat diintepretasikan bahwa jika lebar badan jalan memiliki peningkatan 10% dari lebar badan jalan sebelumnya, maka model pendekatan dengan GLM memprediksi akan terjadi peningkatan jumlah kecelakaan mobil sebanyak 84 korban. Dari hasil analisis regresi logistik biner didapatkan model peluang kecelakaan di mana perilaku pengendara yang mempengaruhi peluang kecelakaan mobil adalah membawa surat berkendara seperti SIM dan STNK (X3.6), mematuhi lampu lalu lintas (X3.10), memberi tanda berbelok/darurat (X3.11), menggunakan sabuk pengaman (X3.12), dan mengantuk saat mengendarai (X3.13).Kata kunci: Model kecelakaan, pengendara mobil, generalized-linear-model, Kota Surabaya.AbstractSimulation Study of Car Accident Model to Improve Traffic Safety in the Urban Area: Various transportation problems that are often experienced with high traffic density, one of which is a traffic accident. The number of accidents is dominated by private vehicles such as motorbikes and cars. This study aimed to make a car accident model in Surabaya Ciy based on the road and the driver characteristics to find out the right actions in reducing the number of car accidents. The study used the analysis of generalized linear model (GLM) and binary logistic regression. It focused on six road segments that have the highest and moderate accident rates, and it was represented by 348 respondents of car drivers. The results of the GLM analysis obtained a probability model of McA = 𝒆𝒆𝟒𝟒,𝟓𝟓 − 𝟎𝟎,𝟕𝟕𝟕 𝟕𝟕 𝑹𝑹𝑹𝑹𝑹𝑹𝑹𝑹 𝑾𝑾𝑾𝑾𝑾 𝑾𝑾𝑾𝑾 which shows only the width of the road body that affects the chances of a car accident. It can be interpreted that if the road width has increased by 10% from the previous road width, the GLM approach model predicts an increase in the number of car accidents by 84 victims. Furthermore, the driver’s behavior that affects the chances of a car accident include carrying a driver license and vehicle registration (X3.6), obeying a traffic light (X3.10), giving a turning/emergency sign (X3.11), using a seat belt (X3.12), and being drowsy when driving (X3.13).Keywords: Accident model, car driver, generalized-linear-model, Surabaya City.

scholarly journals A Study on the Coordination of Urban Traffic Control and Traffic Assignment

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
ZhaoWei Qu ◽  
Yan Xing ◽  
XianMin Song ◽  
YuZhou Duan ◽  
Fulu Wei
Keyword(s):  
Traffic Control ◽  
Network Flow ◽  
Road Network ◽  
Traffic Assignment ◽  
Route Choice ◽  
Flow Distribution ◽  
Urban Traffic ◽  
Network Efficiency ◽  
The Road ◽  
Value Model

The interactions between signal setting and traffic assignment can directly affect the urban road network efficiency. In order to improve the coordination of signal setting with traffic assignment, this paper created a traffic control algorithm considering traffic assignment; meanwhile, the link impedance function and the route choice function were introduced into this paper to study the user's route choice and the road network flow distribution. Then based on the above research, we created a system utility value model. Finally through the VISSIM software to simulate the test network, we verified the superiority of the coordination algorithm and the model and gave the optimal flow of the road network.

scholarly journals Comparing Road User Charging Acceptability in the City of Tunis and Damascus

2019 ◽  
Vol 296 ◽  
pp. 02002
Author(s):  
Mohamad Shatanawi ◽  
Souhir Boudhrioua ◽  
Ferenc Mészáros
Keyword(s):  
Road Network ◽  
Road Pricing ◽  
Urban Traffic ◽  
Road User ◽  
The Political ◽  
The Public ◽  
The Road ◽  
Pricing Scheme ◽  
Two Cities ◽  
The City

Worldwide, multiple studies have been trying to reduce traffic issues without physically changing the road network, this is when the congestion fees strategy has been considered as a favorable solution for the urban traffic issues. A fundamental condition that needs to be checked before the implementation of the road-pricing scheme is the acceptability of both the political and the public parties. The acceptability is so variable and depends on many features and differs from one individual to another, thus, a survey with a set of variant questions might help to understand the expectations and the worries of the citizens and aim to improve them for better effectiveness of the road-pricing project. This report aims, through analyzing the responses of a distributed survey, to evaluate the acceptability of the citizens of Tunis, Tunisia and Damascus, Syria in order to draw a comparison between the two cities. Moreover, it assesses the degree of acceptability and the variable expectations of the implementation of the congestion fees of the two societies.

scholarly journals Modeling and optimizing a road de-icing device by a nonlinear heating

2019 ◽  
Vol 53 (3) ◽  
pp. 775-803 ◽  
Author(s):  
Frederic Bernardin ◽  
Arnaud Munch
Keyword(s):  
Optimal Control ◽  
Control Problem ◽  
Real Data ◽  
Road Surface ◽  
Winter Period ◽  
One Dimensional ◽  
The Road ◽  
Dimensional Modeling ◽  
Nonlinear Heating ◽  
The One

In order to design a road de-icing device by heating, we consider in the one dimensional setting the optimal control of a parabolic equation with a nonlinear boundary condition of the Stefan–Boltzmann type. Both the punctual control and the corresponding state are subjected to a unilateral constraint. This control problem models the heating of a road during a winter period to keep the road surface temperature above a given threshold. The one-dimensional modeling used in this work is a first step of the modeling of a road heating device through the circulation of a coolant in a porous layer of the road. We first prove, under realistic physical assumptions, the well-posedness of the direct problem and the optimal control problem. We then perform some numerical experiments using real data obtained from experimental measurements. This model and the corresponding numerical results allow to quantify the minimal energy to be provided to keep the road surface without frost or snow.

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