Optimization of Emergency Transportation Organization of Holiday Tourism Traffic

The purpose of the optimization of holiday traffic emergency traffic organization is to solve the problem of serious traffic jams in holiday scenic spots. Based on the prediction of traffic volume and traffic mode division in the future years of the scenic spot, the traffic accident route is analyzed to provide theoretical support for the emergency traffic organization and planning of the scenic spot. This article takes the Shijiazhuang Jinta Bay scenic area as the research object, based on the traffic volume of the Jinta Bay tourist scenic area from 2009 to 2016, analyzes the traffic environment of the scenic area, predicts the traffic demand, and builds a one-way traffic organization double-layer optimization model. The simulated annealing algorithm is used to solve the model, an emergency transportation organization optimization plan is formulated, and the feasibility of the plan is verified through VISSIM simulation. The results of the study show that the one-way traffic organization method reduces the average vehicle delay by 32.2% and the average queue length by 14.5%. The one-way traffic organization based on branch diversion can more effectively solve the main road jamming and congestion caused by traffic accidents, prevent the occurrence of secondary accidents, and reduce the economic losses of scenic area managers. At the same time, the purpose of ensuring the tourist quality of tourists and the economic interests of scenic spot management departments is ensured.

Download Full-text

Development of an early warning system for loose automobile tires

Science Progress ◽

10.1177/0036850420940880 ◽

2020 ◽

Vol 103 (3) ◽

pp. 003685042094088

Author(s):

Huibo Wu ◽

Fei Song ◽

Kainan Wu ◽

Cheng Chen ◽

Xiaohua Wang

Keyword(s):

Early Warning ◽

Early Warning System ◽

Traffic Accidents ◽

Warning System ◽

Working Environment ◽

Vehicle Body ◽

Economic Losses ◽

Control Module ◽

Alarm Signal ◽

Monitoring Module

The looseness of tires or even falling off from cars will lead to serious traffic accidents. Once it occurs, it will bring casualties and huge economic losses to society, seriously affecting the traffic safety. To mitigate such possible safety concerns, an early loosening warning system is developed in this article. The system consists of the tire monitoring module and the working control module. The tire monitoring module is installed on the tire and is designed with no power supply. The control module is installed in the vehicle body. Signal transmission between the two modules is achieved through wireless radio frequency. In the driving, once the tire is loosened, the monitoring device will send out the alarm signal automatically and wirelessly. After the driver gets the alarm signal, he can immediately perform the emergency processing, parking, and inspection, which can avoid traffic accidents caused by it. This article introduces the detailed structure, working principle, and operation process of the system. This early warning system has simple structure, high reliability, and is easy to use. It can be used in the common working environment of automobiles. Meanwhile, it is also the foundation of intelligent connected vehicle.

Download Full-text

Analysis of Driver's Characteristics Based on Internet of Vehicles

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.505-506.1148 ◽

2014 ◽

Vol 505-506 ◽

pp. 1148-1152

Author(s):

Jian Qun Wang ◽

Xiao Qing Xue ◽

Ning Cao

Keyword(s):

Traffic Accidents ◽

Road Traffic ◽

Classification Model ◽

Economic Losses ◽

Lane Changing ◽

Internet Of Vehicles ◽

Factors Affecting ◽

The Road ◽

The University ◽

Driver’S Characteristics

The road traffic accidents caused huge economic losses and casualties, so it had been focused by the researchers. Lane changing characteristic is the most relevant characteristic with safety. The intent of lane changing was discussed. Firstly, the factors affecting the intent were analyzed, the speed satisfaction value and the space satisfaction value were proposed; then the data from the University of California, Berkeley was extracted and the number of vehicles changed lane more often and the vehicle ID were obtained; the BP neural network classification model was established, it was trained and testified by actual data. The results shown the method could predict the intent accurately.

Download Full-text

Epidemiology of Road Traffic Accidents and Injuries in Nigeria: A Protocol for Systematic Review and Meta-analysis

10.21203/rs.3.rs-215120/v1 ◽

2021 ◽

Author(s):

Samuel Osobuchi Ngene ◽

Olatoun Adefunke Adeola ◽

Chi-kadibia T Ukoma ◽

Augustine Nwakuche Duru ◽

Kayode Olaoluwa Olaniyan ◽

...

Keyword(s):

Systematic Review ◽

Standard Error ◽

Traffic Accidents ◽

Road Traffic ◽

Cochrane Library ◽

Economic Losses ◽

Road Traffic Accidents ◽

Road Traffic Injuries ◽

Pooled Prevalence ◽

Registration Number

Abstract Background: About 1.35 million people die annually worldwide due to road traffic accidents. Road traffic injuries cause considerable economic losses to individuals, their families, and to nations as a whole. About 93% of the world's fatalities on the roads occur in low-and middle-income countries, even though these countries have approximately 60% of the world's vehicles. Road Traffic Accidents constitute the third leading cause of trauma related deaths in Nigeria. It is a substantial public health problem that deserves a systematic review.Methods and Analysis: We developed a search strategy using MeSH, text words and entry terms. Nine databases will be searched, including PubMed, African Journal Online, Embase, Google Scholar, Scopus, Cochrane Library, CINAHL, Web of Science and ResearchGate. Only observational studies, retrievable in the English language will be included. The primary outcome is prevalence of road traffic injuries in Nigeria. The secondary outcomes include proportion of road traffic accidents in Nigeria, patterns, predictors and consequences of road traffic accidents in Nigeria. Identified studies will be screened and selected based on inclusion criteria using Rayyan QCRI screening tool, by independent reviewers with dual blinding. Data items will be extracted into predefined forms in Microsoft Excel before exporting to CMA version 3 for analysis. Every selected study will have their NIH quality scores and Cochrane risk of bias reported. Studies will be assessed for methodological and statistical heterogeneity. Publication bias will be assessed using Funnel Plots and test of asymmetry. Results will include forest plots, pooled prevalence with standard error, variance, relative weights assigned to studies and heterogeneity test. Further analysis will include subgroup analysis and meta-regression using both categorical and quantitative variables.Discussion: This protocol will enable a transparent, accurate and reliable method for determining pooled prevalence, standard error and 95% CI of road traffic injuries in Nigeria. Patterns and outcomes of RTA in Nigeria will also be assessed. Evidence generated by this protocol will likely inform policy on prevention of RTA in NigeriaTrial Registration Number: This protocol is registered with PROSPERO, with registration number CRD42021226956.

Download Full-text

Optimal Staffing for Vessel Traffic Service Operators: A Case Study of Yeosu VTS

Sensors ◽

10.3390/s21238004 ◽

2021 ◽

Vol 21 (23) ◽

pp. 8004

Author(s):

Sang-Lok Yoo ◽

Kwang-Il Kim

Keyword(s):

Statistical Data ◽

Optimal Number ◽

Traffic Volume ◽

Near Miss ◽

Trajectory Data ◽

Staffing Level ◽

Microscopic Approach ◽

Marine Accidents ◽

Traffic Organization

Vessel traffic volume and vessel traffic service (VTS) operator workloads are increasing with the expansion of global maritime trade, contributing to marine accidents by causing difficulties in providing timely services. Therefore, it is essential to have sufficient VTS operators considering the vessel traffic volume and near-miss cases. However, no quantitative method for determining the optimal number of workstations, which is necessary for calculating the VTS operator staffing level, has yet been proposed. This paper proposes a new, microscopic approach for calculating the number of workstations from vessel trajectories and voice recording communication data between VTS operators and navigators. The vessel trajectory data are preprocessed to interpolate different intervals. The proposed method consists of three modules: Information services, navigational assistance services, and traffic organization service. The developed model was applied to the Yeosu VTS in Korea. Another workstation should be added to the current workstation based on the proposed method. The results showed that even without annual statistical data, a reasonable VTS operator staffing level could be calculated. The proposed approach helps prevent vessel accidents by providing timely services even if the vessel traffic is congested if VTS operators are deployed to a sufficient number of workstations.

Download Full-text

Real-Time V2V Communication With a Machine Learning-Based System for Detecting Drowsiness of Drivers

International Journal of Interdisciplinary Telecommunications and Networking ◽

10.4018/ijitn.2021100104 ◽

2021 ◽

Vol 13 (4) ◽

pp. 35-50

Author(s):

Ahmed Y. Awad ◽

Seshadri Mohan

Keyword(s):

Machine Learning ◽

Traffic Accidents ◽

Ad Hoc ◽

Economic Losses ◽

Drowsy Driving ◽

The Road ◽

V2v Communication ◽

Physical Injuries ◽

On The Road ◽

The U.S

This article applies machine learning to detect whether a driver is drowsy and alert the driver. The drowsiness of a driver can lead to accidents resulting in severe physical injuries, including deaths, and significant economic losses. Driver fatigue resulting from sleep deprivation causes major accidents on today's roads. In 2010, nearly 24 million vehicles were involved in traffic accidents in the U.S., which resulted in more than 33,000 deaths and over 3.9 million injuries, according to the U.S. NHTSA. A significant percentage of traffic accidents can be attributed to drowsy driving. It is therefore imperative that an efficient technique is designed and implemented to detect drowsiness as soon as the driver feels drowsy and to alert and wake up the driver and thereby preventing accidents. The authors apply machine learning to detect eye closures along with yawning of a driver to optimize the system. This paper also implements DSRC to connect vehicles and create an ad hoc vehicular network on the road. When the system detects that a driver is drowsy, drivers of other nearby vehicles are alerted.

Download Full-text

A study on Private Car Accidents

International Journal of Novel Trends in Pharmaceutical Sciences ◽

10.26452/ijntps.v11i1.1409 ◽

2021 ◽

Vol 11 (1) ◽

pp. 10-24

Author(s):

Abdulmajeed Alamri ◽

Tarek M. Esmael ◽

Sami Fawzy ◽

Hany Hosny ◽

Saleh Attawi ◽

...

Keyword(s):

Road Traffic Accident ◽

Traffic Accident ◽

Traffic Accidents ◽

Road Traffic ◽

Road Traffic Injury ◽

Economic Losses ◽

Moving Vehicle ◽

The Road ◽

Lost Productivity ◽

On The Road

In this study, road traffic injury (RTI) was defined as any injury resulting from a road traffic accident irrespective of severity and outcome. Road traffic accident (RTA) was defined as any crash on the road involving at least one moving vehicle, irrespective of it resulting in an injury. This could include collision with a vehicle or any non`moving object while driving/riding a vehicle, collision with a moving vehicle while walking/running/standing/ sitting on the road, or fall from a moving vehicle. The burden of road traffic accidents (RTA) is a leading cause of all trauma admissions in hospitals worldwide. Road traffic injuries cause considerable economic losses to victims, their families, and to nations as a whole. These losses arise from the cost of treatment (including rehabilitation and incident investigation) as well as reduced/lost productivity (e.g. in wages) for those killed or disabled by their injuries and for family members who need to take time off work (or school) to care for the injured. Road traffic fatality in the Kingdom of Saudi Arabia (KSA) is the highest, accounts for 4.7% of all mortalities. Road injuries also are reported to be the most serious in this country, with an accident to injury ratio of 8:6. In this study, we try to focus on some causes of the accidents in KSA, so we can implement the prevention plan.

Download Full-text

The Impact of Emergency Parking Bays on Quasi-Eight-Lane Expressway Traffic Operations

Sustainability ◽

10.3390/su12083432 ◽

2020 ◽

Vol 12 (8) ◽

pp. 3432

Author(s):

Zhen Yang ◽

Xiaocan Chen ◽

Dazhi Sun

Keyword(s):

High Volume ◽

Traffic Volume ◽

Simulation Software ◽

Traffic Operations ◽

Microscopic Simulation ◽

Lane Changing ◽

Traffic Demand ◽

The Road ◽

Traffic Operation ◽

The Impact

Recently, with the discrepancy between increasing traffic demand and limited land resources, more and more expressways are choosing to use hard shoulders to expand into quasi-six-lane or quasi-eight-lane roads. Therefore, more emergency parking bays are used in place of traditional parking belts. However, there are no standards defining clear and unified specifications for the design of parking bays. This paper aimed to investigate the impact of emergency parking bays on expressway traffic operations with various traffic volumes and setting conditions. Based on the Monte Carlo method, VISSIM (Verkehr in Städten Simulation, a microscopic simulation software) simulation experiments were conducted using measured traffic operation data from one expressway in Zhejiang province. The probability of unsafe deceleration, lane-changing maneuvers and delay times were considered as the safety and efficiency indexes in this simulation study. The simulation results indicated that the emergency parking vehicle had an increasing impact on the following vehicle as the traffic volume increased. However, the impact pattern was found to be insensitive to the changing of the bay taper length. For low traffic volume, compared with the arrival vehicle, the departure vehicle had more impact on the traffic operation of the mainline. However, the impact of the arrival vehicle became more remarkable as the traffic volume increased. After parking, the waiting time for merging into the mainline was reduced as the volume decreased or as the bay taper increased. Furthermore, reductions caused by varying bay tapers were more significant under high volume conditions. Finally, this study suggests that parking bays are inapplicable when the occupancy of the road space exceeds 20% (about 3000 veh/h), because they would cause significant impact on the safety and efficiency of the expressway. The results of this paper are useful for the design and implementation of emergency parking bays.

Download Full-text

A Method Framework for Automatic Airspace Reconfiguration-Monte Carlo Method for Eliminating Irregular Sector Shapes Generated by Region Growth Method

Sensors ◽

10.3390/s19183934 ◽

2019 ◽

Vol 19 (18) ◽

pp. 3934

Author(s):

Zhijian Ye ◽

Fanhe Kong ◽

Baocheng Zhang ◽

Wei Gao ◽

Jianfeng Mao

Keyword(s):

Monte Carlo ◽

Monte Carlo Method ◽

Simulated Annealing Algorithm ◽

Air Traffic ◽

Traffic Demand ◽

Dynamic Monte Carlo ◽

Growth Method ◽

Annealing Algorithm ◽

Region Growth ◽

Irregular Sector

With the growth of air traffic demand in busy airspace, there is an urgent need for airspace sectorization to increase air traffic throughput and ease the pressure on controllers. The purpose of this paper is to develop a method framework that can perform airspace sectorization automatically, reasonably, which can be used as an advisory tool for controllers as an automatic system, especially for eliminating irregular sector shapes generated by simulated annealing algorithm (SAA) based on the region growth method. The two graph cutting method, dynamic Monte Carlo method by changing location of flexible vertices (MC-CLFV) and Monte Carlo method by radius changing (MC-RC) were developed to eliminate irregular sector shapes generated by SAA in post-processing. The experimental results show that the proposed method framework of airspace sectorization (AS) can automatically and reasonably generate sector design schemes that meet the design criteria. Our methodology framework and software can provide assistant design and analysis tools for airspace planners to design airspace, improve the reliability and efficiency of airspace design, and reduce the burden of airspace planners. In addition, this lays the foundation for reconstructing airspace with the more intelligent method.

Download Full-text

Morphological and Molecular Characterization of Alternaria Species Causing Leaf Blight on Watermelon in China

Plant Disease ◽

10.1094/pdis-01-20-0130-re ◽

2021 ◽

Vol 105 (1) ◽

pp. 60-70 ◽

Cited By ~ 1

Author(s):

Guoping Ma ◽

Shuwen Bao ◽

Juan Zhao ◽

Yuan Sui ◽

Xuehong Wu

Keyword(s):

Rna Polymerase Ii ◽

Disease Incidence ◽

Disease Index ◽

Leaf Blight ◽

Economic Losses ◽

Rdna Its ◽

Detached Leaves ◽

Alternaria Species ◽

Alternaria Sp ◽

The One

Watermelon is an economically important crop in China and is commonly affected by Alternaria-like leaf blight that can result in significant economic losses. In this study, 830 Alternaria isolates, recovered from symptomatic watermelon leaves, were identified based on morphological traits, pathogenicity, and multilocus sequence analyses of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), histone 3 (HIS3), the internal transcribed spacer of ribosomal DNA (rDNA ITS), and the RNA polymerase II second largest subunit (RPB2). Watermelon isolates grouped to five Alternaria species and one unclassified Alternaria species. They were A. tenuissima, A. alternata, A. cucumerina, A. infectoria, A. gaisen, and Alternaria sp. Notably, A. tenuissima was the most prevalent (73.5%) of the six isolated species, followed by A. alternata (25.0%), A. cucumerina (1.1%), Alternaria sp. (0.2%), A. infectoria (0.1%), and A. gaisen (0.1%). Pathogenicity tests demonstrated that all six Alternaria species could produce brown necrotic lesions on detached leaves of watermelon. The average disease incidence (75.1%) and average disease index (60.8) of watermelon resulting from inoculation of leaves with A. cucumerina were significantly higher than levels resulting from A. alternata (52.9% and 37.2) and A. tenuissima (47.5% and 30.8). Inoculation with Alternaria sp. resulted in a disease incidence (70.0%) and disease index (51.5), which were lower than those of A. cucumerina. The disease incidence and disease index in watermelon leaves inoculated with the one isolate of A. infectoria and the one isolate of A. gaisen present in the inoculated leaves were 28.9% and 16.4, and 48.9% and 31.4, respectively. Results of the study indicate that Alternaria species associated with watermelon leaf blight in China are more diverse than that has been previously reported. This is the first report globally of A. infectoria, A. gaisen, and an unclassified Alternaria species as causal agents of leaf blight on watermelon.

Download Full-text

CONGESTION EFFECTS OF AUTONOMOUS TAXI FLEETS

Transport ◽

10.3846/16484142.2017.1347827 ◽

2018 ◽

Vol 33 (4) ◽

pp. 971-980 ◽

Cited By ~ 21

Author(s):

Michal Maciejewski ◽

Joschka Bischoff

Keyword(s):

Traffic Congestion ◽

Autonomous Vehicles ◽

Large Scale ◽

Traffic Volume ◽

City Centre ◽

Conventional Vehicle ◽

Road Capacity ◽

Private Car ◽

The One ◽

The Impact

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.

Download Full-text