scholarly journals A macroscopic and hierarchical location model of regional road traffic disaster relief material repository

2019 ◽  
Vol 11 (1) ◽  
pp. 168781401882176 ◽  
Author(s):  
Jianfeng Xi ◽  
Kai Mu ◽  
Tongqiang Ding ◽  
Chengyuan Zhang ◽  
Hongyu Guo
Keyword(s):  
Ant Colony Algorithm ◽  
Road Traffic ◽  
Disaster Relief ◽  
Location Model ◽  
Large Area ◽  
Coverage Area ◽  
Location Selection ◽  
The Road ◽  
Hierarchical Location

Since the disaster point of road traffic emergency and the emergency demand were uncertain, the demand weighting model and the hierarchical location model are suitable for the characteristics of road traffic emergency. According to the requirements for coverage area of the macroscopic-location of the large area of disaster relief material repository, the demand weighting model and the hierarchical location model were established in this article. Among them, the demand weight model was solved by modeling, and the demand weight of each disaster point was obtained; the location model was combined with immune algorithm and ant colony algorithm to get the hierarchical location scheme. Finally, Jing-jin-ji that represented China’s “capital circle” was taken as an example, the model was solved using MATLAB, the mathematical software, and provided scientific and reasonable decision-making support for location selection. Moreover, it also provided a basis for the classification of the road traffic disaster relief material repository.

scholarly journals Improper Driver Action as a Cause of Road Accidents / Niewłaściwe Działania Kierowców Jako Przyczyna Powstawania Zdarzeń Drogowych

2012 ◽  
Vol 21 (1) ◽  
pp. 87-98
Author(s):  
Łukasz Muślewski
Keyword(s):  
Motor Vehicle ◽  
Road Traffic ◽  
Road Accident ◽  
Process Safety ◽  
Driving Experience ◽  
The Road ◽  
Human Driver ◽  
Proper Estimation ◽  
The Impact

Abstract Road traffic is inseparably connected with road accident. This is the human-driver whose role in the transportation process safety is of key importance. Driving a motor vehicle requires from the driver not only knowledge but also physical and psychical fitness. They need to have the ability of quick reaction, proper estimation of the road situation and doing maneuvers adequate to it. In this study, an assessment of the impact of improper behaviors of drivers on occurrence of road collisions and accidents, has been analyzed on the basis of literature analysis and the authors’ own research. In effect of the carried out tests there has been made a classification of the road events with a division into: cause, place, date, and time of their occurrence as well as drivers’ age and their driving experience. The whole study has been performed on the basis of a real transportation company, operating on the territory of an urban agglomeration with the population of 500 inhabitants.

scholarly journals Research on the classification for road traffic visibility based on the characteristics of driving behaviour – a driving simulator experiment

2020 ◽  
Vol 3 (1) ◽  
pp. 30-36
Author(s):  
Kun Wang ◽  
Weihua Zhang ◽  
Zhongxiang Feng ◽  
Cheng Wang
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Road Traffic ◽  
Driving Behavior ◽  
Control Measures ◽  
Content Type ◽  
The Road ◽  
Road Traffic Safety ◽  
Fine Classification

Purpose The purpose of this paper is to perform fine classification of road traffic visibility based on the characteristics of driving behavior under different visibility conditions. Design/methodology/approach A driving simulator experiment was conducted to collect data of speed and lane position. ANOVA was used to explore the difference in driving behavior under different visibility conditions. Findings The results show that only average speed is significantly different under different visibility conditions. With the visibility reducing, the average vehicle speed decreases. The road visibility conditions in a straight segment can be divided into five levels: less than 20, 20-30, 35-60, 60-140 and more than 140 m. The road visibility conditions in a curve segment can be also divided into four levels: less than 20, 20-30, 35-60 and more than 60 m. Originality/value A fine classification of road traffic visibility has been performed, and these classifications help to establish more accurate control measures to ensure road traffic safety under low-visibility conditions.

scholarly journals Hierarchical Classification of Environmental Noise Sources Considering the Acoustic Signature of Vehicle Pass-Bys

2012 ◽  
Vol 37 (4) ◽  
pp. 423-434 ◽  
Author(s):  
Xavier Valero ◽  
Francesc Alías
Keyword(s):  
Classification Accuracy ◽  
Classification Scheme ◽  
Road Traffic ◽  
Hierarchical Classification ◽  
Environmental Noise ◽  
Noise Sources ◽  
Daily Lives ◽  
The Road ◽  
Acoustic Signature

Abstract This work is focused on the automatic recognition of environmental noise sources that affect humans’ health and quality of life, namely industrial, aircraft, railway and road traffic. However, the recognition of the latter, which have the largest influence on citizens’ daily lives, is still an open issue. Therefore, although considering all the aforementioned noise sources, this paper especially focuses on improving the recognition of road noise events by taking advantage of the perceived noise differences along the road vehicle pass-by (which may be divided into different phases: approaching, passing and receding). To that effect, a hierarchical classification scheme that considers these phases independently has been implemented. The proposed classification scheme yields an averaged classification accuracy of 92.5%, which is, in absolute terms, 3% higher than the baseline (a traditional flat classification scheme without hierarchical structure). In particular, it outperforms the baseline in the classification of light and heavy vehicles, yielding a classification accuracy 7% and 4% higher, respectively. Finally, listening tests are performed to compare the system performance with human recognition ability. The results reveal that, although an expert human listener can achieve higher recognition accuracy than the proposed system, the latter outperforms the non-trained listener in 10% in average.

scholarly journals REAL-TIME TRACKING IN SATELLITE VIDEOS VIA JOINT DISCRIMINATION AND POSE ESTIMATION

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 23-29
Author(s):  
X. Chen ◽  
H. Sui
Keyword(s):  
Kalman Filter ◽  
Pose Estimation ◽  
Road Traffic ◽  
State Of The Art ◽  
Spatial Distance ◽  
Large Area ◽  
Background Region ◽  
Long Distance ◽  
The Road ◽  
Art Methods

<p><strong>Abstract.</strong> Object tracking has gained much attention in the field of computer vision and intelligent traffic analysis. Satellite videos are more suitable for long-distance tracking comparing to the road traffic videos. However, most of the state-of-the-art methods produce poor results when applied to satellite videos, due to low resolution of the small target and interference from similar background in satellite videos. In this paper, we present an improved Discriminative Correlation Filter based approach specifically tailored for small objects tracking in satellite videos through applying spatial weight in the filter and estimating the pose by Kalman filter. First, a spatial mask is introduced to encourage the final filter to give different contributions depending on the spatial distance. Furthermore, Kalman filter is incorporated into the approach with the aim of predicting the position when the target run into the large area similar background region. Finally, an efficient strategy for combining the improved DCF tracker and pose estimation is proposed. Experimental results on three satellite videos describing the traffic conditions of three cities demonstrate that the proposed approach can effectively track the targets even though the targets are similar to the background region in a period of time. Compare with other state-of-the-art methods, the final accuracies and speeds of our method achieve the best.</p>

scholarly journals Investigating Car Users’ Driving Behaviour through Speed Analysis

2017 ◽  
Vol 29 (2) ◽  
pp. 193-202 ◽  
Author(s):  
Laura Eboli ◽  
Giuseppe Guido ◽  
Gabriella Mazzulla ◽  
Giuseppe Pungillo ◽  
Riccardo Pungillo
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Road Segment ◽  
Accident Risk ◽  
The Road ◽  
Driving Behaviour ◽  
Long Time ◽  
Recorded Data ◽  
On The Road

Speed has been identified for a long time as a key risk factor in road traffic: inappropriate speeds contribute to a relevant part of traffic accidents. Many literature studies have focused on the relationship between speed and accident risk. Starting from this consideration this paper investigates traffic accident risk by analysing the travelling speeds recorded by real tests on the road. A survey was conducted to collect experimental speed values in a real context. A specific road segment, belonging to an Italian rural two-lane road, was repeatedly run by 27 drivers in order to collect the instantaneous speed values for each trajectory. Smartphone-equipped vehicles were used to record continuous speed data. The recorded data were used to calculate: the average speed, 50th and 85th percentile speed for each geometric element of the analysed road segment. The main result of the research is the classification of car users’ driving behaviour based on the speed values. By using the above mentioned ranges of speed, the classification provides three types of driving behaviour: safe, unsafe, and safe but potentially dangerous. It was found that only four drivers feature “safe” behaviour, driving in a safe manner on most of the road elements. However, the major part of drivers, even if they feature safe behaviour, could be dangerous for other drivers because they drive at very low speeds.

A Groundwork Based Novel Routing Protocol for Vehicular Ad hoc Networks

2017 ◽  
Vol 7 (11) ◽  
pp. 121
Author(s):  
Amolkirat Singh ◽  
Guneet Saini
Keyword(s):  
Routing Protocol ◽  
Packet Loss ◽  
Secure Communication ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Road Traffic ◽  
Traditional Approach ◽  
Unexpected Events ◽  
The Road ◽  
On The Road

Many people lose their life and/or are injured due to accidents or unexpected events taking place on road networks. Besides traffic jams, these accidents generate a tremendous waste of time and fuel. Undoubtedly, if the vehicles are provided with timely and dynamic information related to road traffic conditions, any unexpected events or accidents, the safety and efficiency of the transportation system with respect to time, distance, fuel consumption and environmentally destructive emissions can be improved. In the field of computer and information science, Vehicular Ad hoc Network (VANET) have recently emerged as an effective tool for improving road safety through propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. VANET is a research area which is in more demand among the researchers, the automobile industries and scientists to discover about the loopholes and advantages of the vehicular networks so that efficient routing algorithms can be developed which can provide reliable and secure communication among the mobile nodes.In this paper, we propose a Groundwork Based Ad hoc On Demand Distance Vector Routing Protocol (GAODV) focus on how the Road Side Units (RSU’s) utilized in the architecture plays an important role for making the communication reliable. In the interval of finding the suitable path from source to destination the packet loss may occur and the delay also is counted if the required packet does not reach the specified destination on time. So to overcome delay, packet loss and to increase throughput GAODV approach is followed. The performance parameters in the GAODV comes out to be much better than computed in the traditional approach.

Analysis of Vehicle–Pedestrian Interactive Behaviors near Unsignalized Crosswalk

2021 ◽  
pp. 036119812199906
Author(s):  
Byeongjoon Noh ◽  
Dongho Ka ◽  
David Lee ◽  
Hwasoo Yeo
Keyword(s):  
South Korea ◽  
Traffic Accidents ◽  
Road Traffic ◽  
The Road ◽  
Video Footage ◽  
Premature Deaths ◽  
Vehicle Velocity ◽  
Behavioral Features ◽  
Velocity Changes ◽  
On The Road

Road traffic accidents are a leading cause of premature deaths and globally pose a severe threat to human lives. In particular, pedestrians crossing the road present a major cause of vehicle–pedestrian accidents in South Korea, but we lack dense behavioral data to understand the risk they face. This paper proposes a new analytical system for potential pedestrian risk scenes based on video footage obtained by road security cameras already deployed at unsignalized crosswalks. The system can automatically extract the behavioral features of vehicles and pedestrians, affecting the likelihood of potentially dangerous situations after detecting them in individual objects. With these features, we can analyze the movement patterns of vehicles and pedestrians at individual sites, and understand where potential traffic risk scenes occur frequently. Experiments were conducted on four selected behavioral features: vehicle velocity, pedestrian position, vehicle–pedestrian distance, and vehicle–crosswalk distance. Then, to show how they can be useful for monitoring the traffic behaviors on the road, the features are visualized and interpreted to show how they may or may not contribute to potential pedestrian risks at these crosswalks: (i) by analyzing vehicle velocity changes near the crosswalk when there are no pedestrians present; and (ii) analyzing vehicle velocities by vehicle–pedestrian distances when pedestrians are on the crosswalk. The feasibility of the proposed system is validated by applying the system to multiple unsignalized crosswalks in Osan city, South Korea.

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