System design for predictive road-traffic information delivery using edge-cloud computing

2018 ◽  
Author(s):  
Ryoichi Shinkuma ◽  
Shingo Kato ◽  
Masahiro Kanbayashi ◽  
Yasuhiro Ikeda ◽  
Ryoichi Kawahara ◽  
...  
Keyword(s):  
Cloud Computing ◽  
System Design ◽  
Road Traffic ◽  
Information Delivery ◽  
Traffic Information

A real-time push system on road traffic information

2014 ◽  
Author(s):  
Yang Xu ◽  
Zhang Zhenjiang ◽  
Liu Yun
Keyword(s):  
Real Time ◽  
Road Traffic ◽  
Traffic Information

Travel mode recognition of urban residents using mobile phone data and MapAPI

2021 ◽  
pp. 239980832098300
Author(s):  
Zhenghong Peng ◽  
Guikai Bai ◽  
Hao Wu ◽  
Lingbo Liu ◽  
Yang Yu
Keyword(s):  
Urban Planning ◽  
Mobile Phone ◽  
Traffic Flow ◽  
Road Traffic ◽  
Urban Traffic ◽  
Phone Call ◽  
Traffic Information ◽  
Mobile Phone Data ◽  
Urban Residents ◽  
Travel Mode

Obtaining the time and space features of the travel of urban residents can facilitate urban traffic optimization and urban planning. As traditional methods often have limited sample coverage and lack timeliness, the application of big data such as mobile phone data in urban studies makes it possible to rapidly acquire the features of residents’ travel. However, few studies have attempted to use them to recognize the travel modes of residents. Based on mobile phone call detail records and the Web MapAPI, the present study proposes a method to recognize the travel mode of urban residents. The main processes include: (a) using DBSCAN clustering to analyze each user’s important location points and identify their main travel trajectories; (b) using an online map API to analyze user’s means of travel; (c) comparing the two to recognize the travel mode of residents. Applying this method in a GIS platform can further help obtain the traffic flow of various means, such as walking, driving, and public transit, on different roads during peak hours on weekdays. Results are cross-checked with other data sources and are proven effective. Besides recognizing travel modes of residents, the proposed method can also be applied for studies such as travel costs, housing–job balance, and road traffic pressure. The study acquires about 6 million residents’ travel modes, working place and residence information, and analyzes the means of travel and traffic flow in the commuting of 3 million residents using the proposed method. The findings not only provide new ideas for the collection and application of urban traffic information, but also provide data support for urban planning and traffic management.

Air pollution in an urban street canyon: Novel insights from highly resolved traffic information and meteorology

2021 ◽  
Author(s):  
Laura Ehrnsperger ◽  
Otto Klemm
Keyword(s):  
Air Pollution ◽  
Temporal Dynamics ◽  
Road Traffic ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Traffic Information ◽  
Pollutant Emission ◽  
Urban Site ◽  
Gasoline Vehicles ◽  
Agricultural Areas

<p>Ambient air pollution caused by fine particulate matter (PM) and trace gases is a pressing topic as it affects the vast majority of the world's population, especially in densely populated urban environments. The main sources of ambient air pollution in cities are road traffic, industries and domestic heating. Alongside nitrogen oxides (NO<sub>x</sub>) and PM, ammonia (NH<sub>3</sub>) is also a relevant air pollutant due to its role as a precursor of particulate ammonium (NH<sub>4</sub><sup>+</sup>). To examine the temporal patterns and sources of air pollutants, this study used fast-response air quality measurements in combination with highly resolved traffic information in Münster, NW Germany. The temporal dynamics of NO<sub>x</sub> and the particle number concentration (PN<sub>10</sub>) were similar to the diurnal and weekly courses of the traffic density. On very short timescales, the real-world peak ratios of NO<sub>x</sub> and PM ≤ 10 µm diameter (PM<sub>10</sub>) exceeded the predicted pollutant emission ratios of the Handbook for Emission Factors for Road Transport (HBEFA) by a factor of 6.4 and 2.0, respectively. A relative importance model revealed that light-duty vehicles (LDVs) are the major relative contributor to PN<sub>10</sub> (38 %) despite their low abundance (4 %) in the local vehicle fleet.  Diesel and gasoline vehicles contributed similarly to the concentrations of PM<sub>10</sub> and PN<sub>10</sub>, while the impact of gasoline vehicles on the PM<sub>1</sub> concentration was greater than that of diesel vehicles by a factor of 4.4. The most recent emission class Euro 6 had the highest influence on PM<sub>10</sub>. Meteorological parameters explained a large portion of the variations in PM<sub>10</sub> and PM<sub>1</sub>, while meteorology had only a minor influence on PN<sub>10</sub>. We also studied the short-term temporal dynamics of urban NH<sub>3 </sub>concentrations, the role of road traffic and agriculture as NH<sub>3</sub> sources and the importance of ammonia for secondary particle formation (SPF). The NH<sub>3</sub> mixing ratio was rather high (mean: 17 ppb) compared to other urban areas and showed distinct diurnal maxima around 10 a.m. and 9 p.m. The main source for ammonia in Münster was agriculture, but road traffic also contributed through local emissions from vehicle catalysts. NH<sub>3</sub> from surrounding agricultural areas accumulated in the nocturnal boundary layer and contributed to SPF in the city center. The size-resolved chemical composition of inorganic ions in PM<sub>10</sub> was dominated by NH<sub>4</sub><sup>+</sup> (8.7 µg m<sup>-3</sup>), followed by NO<sub>3</sub><sup>-</sup> (3.9 µg m<sup>-3</sup>), SO<sub>4</sub><sup>2-</sup> (1.6 µg m<sup>-3</sup>) and Cl<sup>-</sup> (1.3 µg m<sup>-3</sup>). Particles in the accumulation range (diameter: 0.1 – 1 µm) showed the highest inorganic ion concentrations. The ammonium neutralization index J (111 %) indicated an excess of NH<sub>4</sub><sup>+</sup> leading to mostly alkaline PM. High ammonia emissions from surrounding agricultural areas combined with large amounts of NO<sub>x</sub> from road traffic play a crucial role for SPF in Münster. Our results further indicate that replacing fossil-fuelled LDVs with electrical vehicles would greatly reduce the PN<sub>10</sub> concentrations at this urban site.</p>

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

scholarly journals 3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing

2021 ◽  
Vol 2083 (3) ◽  
pp. 032022
Author(s):  
Yunpeng Guo ◽  
Kai Zou ◽  
Shengdong Chen ◽  
Feng Yuan ◽  
Fang Yu
Keyword(s):  
Virtual World ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Physical World ◽  
Transportation System ◽  
Traffic Information ◽  
Digital Twin ◽  
Twin System ◽  
Infrastructure System

Abstract Cooperative vehicle-infrastructure is one of the most import developing direction of future intelligent transportation system, while digital twin system can record, reproduce, and even deduce the physical system, which could be helpful for the development of cooperative vehicle-infrastructure. In this study, we proposed a 3D digital twin platform of intelligent transportation system based on road-side sensing, a core component of cooperative vehicle-infrastructure system. This platform consists of real road-side sensing unit,3D virtual environment, and the ROS bridge between them, by receiving the sensing results of physical world in real-time, the virtual world can reproduce the compatible road traffic information, such as the type,3D position and orientation of traffic participants.

scholarly journals Cooperative Adaptive Driving for Platooning Autonomous Self Driving Based on Edge Computing

2019 ◽  
Vol 29 (2) ◽  
pp. 213-225 ◽  
Author(s):  
Ben-Jye Chang ◽  
Ren-Hung Hwang ◽  
Yueh-Lin Tsai ◽  
Bo-Han Yu ◽  
Ying-Hsin Liang
Keyword(s):  
Shock Waves ◽  
Traffic Flow ◽  
Road Traffic ◽  
Edge Computing ◽  
Traffic Information ◽  
Velocity Variation ◽  
Traffic Density ◽  
Cruise Control ◽  
Safe Driving ◽  
Butterfly Effect

Abstract Cooperative adaptive cruise control (CACC) for human and autonomous self-driving aims to achieve active safe driving that avoids vehicle accidents or traffic jam by exchanging the road traffic information (e.g., traffic flow, traffic density, velocity variation, etc.) among neighbor vehicles. However, in CACC, the butterfly effect is encountered while exhibiting asynchronous brakes that easily lead to backward shock-waves and are difficult to remove. Several critical issues should be addressed in CACC, including (i) difficulties with adaptive steering of the inter-vehicle distances among neighbor vehicles and the vehicle speed, (ii) the butterfly effect, (iii) unstable vehicle traffic flow, etc. To address the above issues in CACC, this paper proposes the mobile edge computing-based vehicular cloud of the cooperative adaptive driving (CAD) approach to avoid shock-waves efficiently in platoon driving. Numerical results demonstrate that the CAD approach outperforms the compared techniques in the number of shock-waves, average vehicle velocity, average travel time and time to collision (TTC). Additionally, the adaptive platoon length is determined according to the traffic information gathered from the global and local clouds.

scholarly journals Overview of Intelligent Transport System (ITS) and Its Applications

2021 ◽  
Author(s):  
Purnendu S M Tripathi ◽  
Ambuj Kumar ◽  
Ashok Chandra
Keyword(s):  
Air Pollution ◽  
Radio Frequency ◽  
Transport System ◽  
Urban Areas ◽  
Road Traffic ◽  
Traffic Information ◽  
Intelligent Transport System ◽  
Comprehensive Overview ◽  
Frequency Bands ◽  
Intelligent Transport

Since last decades world, predominantly urban areas, is experiencing huge voluminous road traffic growth, resulting in heavy congestion, air pollution, accidents, and poor efficiency.  Many people every day are the victims of this poor management of tremendous traffic. Since many years, there had been some automation in managing the traffic namely Electronic Toll Collection (ETC), Electronic parking payment, normal traffic information etc. However, there are little efforts for making the system more advanced. Recently, several kinds of research are being launched by many countries to develop Intelligent Transport System (ITS), with the objectives to minimize congestion, ensure better safety, reduce air pollution etc. ITS are planned to establish robust communication between vehicle to vehicle (V2V), vehicle to pedestrian (V2P), vehicle to infrastructure (V2I), and vehicle to network (V2N). Initially, for communication links ITS, deploys Wi-Fi network, but because of limited capacity and huge requirement, some links use 5.8 GHz radio frequency for such purposes. IEEE, International Telecommunications Union (ITU) and other advanced research organisations are studying 700 MHz band and mm frequency bands for advanced ITS. ITS is poised to use Information & Communication Technology (ICT) networks for such purposes. ITU has established Study Groups/study questions for addressing ITS issues. The World Radio Conference (WRC-2019) has made a Recommendation 208 regarding harmonization of frequency bands for ITS applications. This paper presents a comprehensive overview of ITS, its applications and analysis etc. The radio frequency spectrum aspects and role of 5 G in ITS are also described in detail.  

Using Expert Systems and Cloud Computing to Build a Diabetes Diagnosis System

2014 ◽  
Vol 651-653 ◽  
pp. 2063-2066
Author(s):  
Chung C. Chang ◽  
Shu Hui Tsai
Keyword(s):  
Cloud Computing ◽  
Diabetic Retinopathy ◽  
Expert System ◽  
Expert Systems ◽  
System Design ◽  
Research Method ◽  
Research Topic ◽  
Prototype System ◽  
Diabetes Diagnosis ◽  
Cloud Platform

This study combines an expert system with cloud computing, establishing the expert system on a cloud platform to provide users with assistance and recommendations about diabetes and diabetic retinopathy diagnosis. This study mainly adopts an empirical approach. The first step is to define the research topic, and then propose questions and the research purpose based on the research background and motivation. Research results are related to three areas, specifically diabetes and diabetic retinopathy, expert systems, and cloud computing. After analyzing and organizing the literature, the research method and scope of research are established with a system design based on the three areas. This study then develops a prototype system to validate, evaluate, and test the expert system. Finally, study gives the conclusion and recommendations.

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