scholarly journals Demand Model in the Agglomeration using Sim Cards

2019 ◽  
Vol 65 (1) ◽  
pp. 143-156
Author(s):  
A. Brzeziński ◽  
T. Dybicz ◽  
Ł. Szymański
Keyword(s):  
Urban Areas ◽  
Large City ◽  
Transport Systems ◽  
Demand Model ◽  
Long Distance ◽  
The Road ◽  
Planning And Design ◽  
Traffic Generation ◽  
Current Experience ◽  
City Models

AbstractThe road network development programme, as well as planning and design of transport systems of cities and agglomerations require complex analyses and traffic forecasts. It particularly applies to higher-class roads (motorways and expressways), which in urban areas, support different types of traffic. Usually there is a conflict between the needs of long-distance traffic, in the interest of which higher-class roads run through undeveloped areas, and the needs of bringing such road closer to potential destinations, cities [1]. By recognising the importance of this problem it is necessary to develop the research and methodology of traffic analysis, especially trip models. The current experience shows that agglomeration models are usually simplified in comparison to large city models, what results from misunderstanding of the significance of these movements for the entire model functioning, or the lack of input data. The article presents the INMOP 3 research project results, within the framework of which it was attempted to increase the accuracy of traffic generation in agglomeration model owing to the use of BigData – the mobile operator’s data on SIM card movements in the Warsaw agglomeration.

Safety at Curves and Road Geometry Standards in Some European Countries

1996 ◽  
Vol 1523 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Thierry Brenac
Keyword(s):  
Urban Areas ◽  
National Standards ◽  
European Countries ◽  
Design Standards ◽  
The Road ◽  
Horizontal Curves ◽  
Road Design ◽  
Road Geometry ◽  
Design Speed ◽  
Curve Geometry

This paper deals with safety at horizontal curves on two-lane roads outside urban areas and the way the road design standards of different European countries account for this safety aspect. After a review of some research results, the main aspects of curve geometry and the curve's place in the horizontal alignment are analyzed. The main conclusions are that the traditional design speed approach is insufficient and that formal complementary rules in road design standards, especially to improve compatibility between successive elements of the alignment, must be introduced. If such complementary rules already exist in some national standards, they are neither frequent nor homogeneous throughout the different countries, and it seems that they are not based on sufficiently developed knowledge.

scholarly journals Smart Cities in Turkey: Approaches, Advances and Applications with Greater Consideration for Future Urban Transport Development

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2308 ◽  
Author(s):  
Can Bıyık
Keyword(s):  
Urban Areas ◽  
Planning Process ◽  
Smart Cities ◽  
Radical Change ◽  
Urban Transport ◽  
Transport Systems ◽  
Structured Interviews ◽  
Policy Makers ◽  
Comprehensive Survey ◽  
Future Vision

The smart city transport concept is viewed as a future vision aiming to undertake investigations on the urban planning process and to construct policy-pathways for achieving future targets. Therefore, this paper sets out three visions for the year 2035 which bring about a radical change in the level of green transport systems (often called walking, cycling, and public transport) in Turkish urban areas. A participatory visioning technique was structured according to a three-stage technique: (i) Extensive online comprehensive survey, in which potential transport measures were researched for their relevance in promoting smart transport systems in future Turkish urban areas; (ii) semi-structured interviews, where transport strategy suggestions were developed in the context of the possible imaginary urban areas and their associated contextual description of the imaginary urban areas for each vision; (iii) participatory workshops, where an innovative method was developed to explore various creative future choices and alternatives. Overall, this paper indicates that the content of the future smart transport visions was reasonable, but such visions need a considerable degree of consensus and radical approaches for tackling them. The findings offer invaluable insights to researchers inquiring about the smart transport field, and policy-makers considering applying those into practice in their local urban areas.

scholarly journals Smartphone monitoring of in-ambulance vibration and noise

2021 ◽  
pp. 095441192098599
Author(s):  
Tom Partridge ◽  
Lorelei Gherman ◽  
David Morris ◽  
Roger Light ◽  
Andrew Leslie ◽  
...  
Keyword(s):  
Transport Systems ◽  
Vertical Acceleration ◽  
Vehicle Speed ◽  
Noise Levels ◽  
The Road ◽  
Neonatal Transport ◽  
Mass Data ◽  
Transport Team ◽  
Vertical Accelerations ◽  
Noise Vibration

Transferring sick premature infants between hospitals increases the risk of severe brain injury, potentially linked to the excessive exposure to noise, vibration and driving-related accelerations. One method of reducing these levels may be to travel along smoother and quieter roads at an optimal speed, however this requires mass data on the effect of roads on the environment within ambulances. An app for the Android operating system has been developed for the purpose of recording vibration, noise levels, location and speed data during ambulance journeys. Smartphone accelerometers were calibrated using sinusoidal excitation and the microphones using calibrated pink noise. Four smartphones were provided to the local neonatal transport team and mounted on their neonatal transport systems to collect data. Repeatability of app recordings was assessed by comparing 37 journeys, made during the study period, along an 8.5 km single carriageway. The smartphones were found to have an accelerometer accurate to 5% up to 55 Hz and microphone accurate to 0.8 dB up to 80 dB. Use of the app was readily adopted by the neonatal transport team, recording more than 97,000 km of journeys in 1 year. To enable comparison between journeys, the 8.5 km route was split into 10 m segments. Interquartile ranges for vehicle speed, vertical acceleration and maximum noise level were consistent across all segments (within 0.99 m . s−1, 0.13 m · s−2 and 1.4 dB, respectively). Vertical accelerations registered were representative of the road surface. Noise levels correlated with vehicle speed. Android smartphones are a viable method of accurate mass data collection for this application. We now propose to utilise this approach to reduce potential harmful exposure, from vibration and noise, by routing ambulances along the most comfortable roads.

scholarly journals A Theoretical Model with Which to Safely Optimize the Configuration of Hydraulic Suspension of Modular Trailers in Special Road Transport

2020 ◽  
Vol 11 (1) ◽  
pp. 305
Author(s):  
Rubén Escribano-García ◽  
Marina Corral-Bobadilla ◽  
Fátima Somovilla-Gómez ◽  
Rubén Lostado-Lorza ◽  
Ash Ahmed
Keyword(s):  
Theoretical Model ◽  
Wind Turbine ◽  
Optimization Algorithm ◽  
Hydraulic Cylinder ◽  
Road Transport ◽  
Automatic Testing ◽  
Transport Systems ◽  
The Road ◽  
Proposed Model ◽  
On The Road

The dimensions and weight of machines, structures, and components that need to be transported safely by road are growing constantly. One of the safest and most widely used transport systems on the road today due to their versatility and configuration are modular trailers. These trailers have hydraulic pendulum axles that are that are attached in pairs to the rigid platform above. In turn, these modular trailers are subject to limitations on the load that each axle carries, the tipping angle, and the oil pressure of the suspension system in order to guarantee safe transport by road. Optimizing the configuration of these modular trailers accurately and safely is a complex task. Factors to be considered include the load’s characteristics, the trailer’s mechanical properties, and road route conditions including the road’s slope and camber, precipitation and direction, and force of the wind. This paper presents a theoretical model that can be used for the optimal configuration of hydraulic cylinder suspension of special transport by road using modular trailers. It considers the previously mentioned factors and guarantees the safe stability of road transport. The proposed model was validated experimentally by placing a nacelle wind turbine at different points within a modular trailer. The weight of the wind turbine was 42,500 kg and its dimensions were 5133 × 2650 × 2975 mm. Once the proposed model was validated, an optimization algorithm was employed to find the optimal center of gravity for load, number of trailers, number of axles, oil pressures, and hydraulic configuration. The optimization algorithm was based on the iterative and automatic testing of the proposed model for different positions on the trailer and different hydraulic configurations. The optimization algorithm was tested with a cylindrical tank that weighed 108,500 kg and had dimensions of 19,500 × 3200 × 2500 mm. The results showed that the proposed model and optimization algorithm could safely optimize the configuration of the hydraulic suspension of modular trailers in special road transport, increase the accuracy and reliability of the calculation of the load configuration, save time, simplify the calculation process, and be easily implemented.

scholarly journals RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 193
Author(s):  
Mohamed Ben bezziane ◽  
Ahmed Korichi ◽  
Chaker Abdelaziz Kerrache ◽  
Mohamed el Amine Fekair
Keyword(s):  
Urban Areas ◽  
High Speed ◽  
Service Discovery ◽  
Cluster Head ◽  
Experimental Comparison ◽  
The Road ◽  
Road Side Unit ◽  
End To End Delay ◽  
End To End ◽  
On The Road

As a promising topic of research, Vehicular Cloud (VC) incorporates cloud computing and ad-hoc vehicular network (VANET). In VC, supplier vehicles provide their services to consumer vehicles in real-time. These services have a significant impact on the applications of internet access, storage and data. Due to the high-speed mobility of vehicles, users in consumer vehicles need a mechanism to discover services in their vicinity. Besides this, quality of service varies from one supplier vehicle to another; thus, consumer vehicles attempt to pick out the most appropriate services. In this paper, we propose a novel protocol named RSU-aided Cluster-based Vehicular Clouds protocol (RCVC), which constructs the VC using the Road Side Unit (RSU) directory and Cluster Head (CH) directory to make the resources of supplier vehicles more visible. While clusters of vehicles that move on the same road form a mobile cloud, the remaining vehicles form a different cloud on the road side unit. Furthermore, the consumption operation is achieved via the service selection method, which is managed by the CHs and RSUs based on a mathematical model to select the best services. Simulation results prove the effectiveness of our protocol in terms of service discovery and end-to-end delay, where we achieved service discovery and end-to-end delay of 3 × 10−3 s and 13 × 10−2 s, respectively. Moreover, we carried out an experimental comparison, revealing that the proposed method outperformed several states of the art protocols.

scholarly journals iBikeSafe: A Multi-Parameter System for Monitoring, Evaluation and Visualization of Cycling Paths in Smart Cities Targeted at Cycling Adverse Conditions

Smart Cities ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 1058-1086
Author(s):  
Franklin Oliveira ◽  
Daniel G. Costa ◽  
Luciana Lima ◽  
Ivanovitch Silva
Keyword(s):  
Urban Areas ◽  
Smart Cities ◽  
Large City ◽  
Health And Safety ◽  
Parameter System ◽  
Urban Centers ◽  
Adverse Conditions ◽  
Last Mile ◽  
Real Scenario

The fast transformation of the urban centers, pushed by the impacts of climatic changes and the dramatic events of the COVID-19 Pandemic, will profoundly influence our daily mobility. This resulted scenario is expected to favor adopting cleaner and flexible modal solutions centered on bicycles and scooters, especially as last-mile options. However, as the use of bicycles has rapidly increased, cyclists have been subject to adverse conditions that may affect their health and safety when cycling in urban areas. Therefore, whereas cities should implement mechanisms to monitor and evaluate adverse conditions in cycling paths, cyclists should have some effective mechanism to visualize the indirect quality of cycling paths, eventually supporting choosing more appropriate routes. Therefore, this article proposes a comprehensive multi-parameter system based on multiple independent subsystems, covering all phases of data collecting, formatting, transmission, and processing related to the monitoring, evaluating, and visualizing the quality of cycling paths in the perspective of adverse conditions that affect cyclist. The formal interactions of all modules are carefully described, as well as implementation and deployment details. Additionally, a case study is considered for a large city in Brazil, demonstrating how the proposed system can be adopted in a real scenario.

scholarly journals Variations in Levels and Sources of Atmospheric VOCs during the Continuous Haze and Non-Haze Episodes in the Urban Area of Beijing: A Case Study in Spring of 2019

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 171
Author(s):  
Lihui Zhang ◽  
Xuezhong Wang ◽  
Hong Li ◽  
Nianliang Cheng ◽  
Yujie Zhang ◽  
...  
Keyword(s):  
Diesel Exhaust ◽  
Urban Areas ◽  
Photochemical Reaction ◽  
Petrochemical Industry ◽  
Exhaust Emission ◽  
Long Distance ◽  
Air Mass ◽  
Source Contributions ◽  
The Government ◽  
Haze Days

To better evaluate the variations in concentration characteristics and source contributions of atmospheric volatile organic compounds (VOCs) during continuous haze days and non-haze days, hourly observations of atmospheric VOCs were conducted using a continuous on-line GC-FID (Airmo VOC GC-866) monitoring system during 1–15 March 2019, in urban areas of Beijing, China. The results showed that the total VOC concentrations during haze days and non-haze days were 59.13 ± 31.08 μg/m3 and 16.91 ± 7.19 μg/m3, respectively. However, the average O3 concentrations during the two haze days were lower than those of non-haze days due to the extremely low concentrations at night instead of the reported lower photochemical reaction in daytime. The ratio of OH radical concentration during haze and non-haze days indicating that the rate of photochemical reaction during haze days was higher than those of non-haze days from 13:00–19:00. The stable air conditions and the local diesel emission at night were the main reasons for the decreased O3 concentrations during haze days. Six major sources were identified by positive matrix factorization (PMF), namely, diesel exhaust, combustion, gasoline evaporation, solvent usage, gasoline exhaust, and the petrochemical industry, contributing 9.93%, 25.29%, 3.90%, 16.88%, 35.59% and 8.41%, respectively, during the whole observation period. The contributions of diesel exhaust and the petrochemical industry emissions decreased from 26.14% and 6.43% during non-haze days to 13.70% and 2.57%, respectively, during haze days. These reductions were mainly ascribed to the emergency measures that the government implemented during haze days. In contrast, the contributions of gasoline exhaust increased from 34.92% during non-haze days to 48.77% during haze days. The ratio of specific VOC species and PMF both showed that the contributions of gasoline exhaust emission increased during haze days. The backward trajectories, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) showed that the air mass of VOCs during haze days was mainly affected by the short-distance transportation from the southwestern of Hebei province. However, the air mass of VOCs during non-haze days was mainly affected by the long-distance transportation from the northwest.

scholarly journals Remote Sensing Road Extraction by Road Segmentation Network

2021 ◽  
Vol 11 (11) ◽  
pp. 5050
Author(s):  
Jiahai Tan ◽  
Ming Gao ◽  
Kai Yang ◽  
Tao Duan
Keyword(s):  
Remote Sensing ◽  
Attention Mechanism ◽  
Context Information ◽  
Road Extraction ◽  
Remote Sensing Images ◽  
Long Distance ◽  
The Road ◽  
Road Segmentation ◽  
Context Characteristics

Road extraction from remote sensing images has attracted much attention in geospatial applications. However, the existing methods do not accurately identify the connectivity of the road. The identification of the road pixels may be interfered with by the abundant ground such as buildings, trees, and shadows. The objective of this paper is to enhance context and strip features of the road by designing UNet-like architecture. The overall method first enhances the context characteristics in the segmentation step and then maintains the stripe characteristics in a refinement step. The segmentation step exploits an attention mechanism to enhance the context information between the adjacent layers. To obtain the strip features of the road, the refinement step introduces the strip pooling in a refinement network to restore the long distance dependent information of the road. Extensive comparative experiments demonstrate that the proposed method outperforms other methods, achieving an overall accuracy of 98.25% on the DeepGlobe dataset, and 97.68% on the Massachusetts dataset.

scholarly journals Vehicle Counting in Video Sequences: An Incremental Subspace Learning Approach

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2848 ◽  
Author(s):  
Leonel Rosas-Arias ◽  
Jose Portillo-Portillo ◽  
Aldo Hernandez-Suarez ◽  
Jesus Olivares-Mercado ◽  
Gabriel Sanchez-Perez ◽  
...  
Keyword(s):  
Principal Component ◽  
Subspace Learning ◽  
Transport Systems ◽  
Video Sequences ◽  
Projected Image ◽  
The Road ◽  
Illumination Changes ◽  
On Line ◽  
Incremental Learning Method ◽  
On Line Learning

The counting of vehicles plays an important role in measuring the behavior patterns of traffic flow in cities, as streets and avenues can get crowded easily. To address this problem, some Intelligent Transport Systems (ITSs) have been implemented in order to count vehicles with already established video surveillance infrastructure. With this in mind, in this paper, we present an on-line learning methodology for counting vehicles in video sequences based on Incremental Principal Component Analysis (Incremental PCA). This incremental learning method allows us to identify the maximum variability (i.e., motion detection) between a previous block of frames and the actual one by using only the first projected eigenvector. Once the projected image is obtained, we apply dynamic thresholding to perform image binarization. Then, a series of post-processing steps are applied to enhance the binary image containing the objects in motion. Finally, we count the number of vehicles by implementing a virtual detection line in each of the road lanes. These lines determine the instants where the vehicles pass completely through them. Results show that our proposed methodology is able to count vehicles with 96.6% accuracy at 26 frames per second on average—dealing with both camera jitter and sudden illumination changes caused by the environment and the camera auto exposure.

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