A Modular Weather and Traffic Data Acquisition Network to Improve Green Traffic Management

2011 ◽  
pp. 136-142
Author(s):  
Andreas Herrmann ◽  
Ulrike Hempel
Keyword(s):  
Data Acquisition ◽  
Traffic Management ◽  
Traffic Data

scholarly journals Evaluation of the Applicability of the Ramp Metering to a Freeway Using Microsimulation: A Case Study in Riyadh, Saudi Arabia

2019 ◽  
Vol 9 (20) ◽  
pp. 4406
Author(s):  
Seongkwan Lee ◽  
Amr Shokri ◽  
Abdullah Al-Mansour
Keyword(s):  
Saudi Arabia ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Fixed Time ◽  
Ramp Metering ◽  
Traffic Data ◽  
Geometrical Data ◽  
Overall Performance ◽  
Length Reduction

Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from the Active Traffic Management (ATM) aspect. Ramp metering (RM) is one of the representative methods of the ATM and has already proven its value in many locations worldwide. Unfortunately, RM has not yet been fully implemented in Saudi Arabia. This research aimed to assess the applicability of RM to a freeway in Riyadh using microsimulation. The widely known software VISSIM (PTV Planung Transport Verkehr AG, Germany, 1992) was chosen to compare the performances of various RM operating scenarios, such as fixedtime operation with different sub-scenarios and traffic-responsive operation using ALINEA (Asservissement Lineaire d’entree Autoroutiere) algorithm. For the simulations, this study targeted Makkah Road, one of the major freeways in Riyadh, and collected geometrical data and traffic data from that freeway. Analysis of four main scenarios and eight sub-scenarios, proved that overall performance of the fixed-time RM operation is generally good. The sub-scenario 4V3R of the fixed-time RM operation was the best in average queue length reduction. However, the traffic-responsive operation was best in average speed improvement.

Feasibility Study of Traffic Signals at Intersections in Peshawar, Pakistan

2012 ◽  
Vol 253-255 ◽  
pp. 1645-1649
Author(s):  
Rawid Khan ◽  
Ghulam Dastagir ◽  
Omar Shahid ◽  
Zeeshan Ahmed ◽  
Bashir Alam
Keyword(s):  
Traffic Management ◽  
Management Strategies ◽  
Traffic Signals ◽  
Level Of Service ◽  
Signal Timing ◽  
Traffic Data ◽  
Ongoing Research ◽  
The Road ◽  
Micro Simulation ◽  
Signal Time

The paper is part of an ongoing research project on traffic management strategies for Peshawar Pakistan. Traffic data collected and warrant tests checked at selected intersections. Peak hour vehicular volume warrant test selected and performed at intersections. Signal timing capacity and delay analysis performed and level of service determined for selected intersection. It was found that “for the same width of the road” the delay and level of service is different at different locations and the corresponding signal time is also different. Some data also analysed in 3D micro simulation.

scholarly journals A Framework for Secure Data Acquisition In VANET

2021 ◽  
Vol 9 (9) ◽  
pp. 1139-1143
Author(s):  
Dr. B. Balakumar
Keyword(s):  
Data Acquisition ◽  
Ad Hoc Network ◽  
Traffic Management ◽  
Ad Hoc ◽  
Safety Information ◽  
Mobile Network ◽  
Vehicular Ad Hoc Network ◽  
Real Time Traffic ◽  
Wide Range ◽  
Types Of Information

Abstract: Recent advances in software, hardware communication technologies are enabling the design and implementation of whole range of different type of network that are various environments. Vehicular Ad-Hoc network is received a lot of interest in the couple years in the one of the networks. A Vehicular Ad-Hoc Network or VANET is a technology that uses moving cars as nodes in a network to create a mobile network. In VANET improving the driving comfort and safety information message are broadcasted regularly. VANET turns every participating car approximately 100 to 300 meters to connect and turn create network with a wide range. In enable vehicle to communicate which other with roadside units (RSUs). Vehicular network are special types of VANET that supported infrastructure based real time traffic management, including internet access, video streaming and content distribution. Privacy - preserving data Acquisition and forwarding scheme by introducing the novel cryptographic algorithm for key generation and powerful encryption. This paper introduces system that takes Advantages of the RSUs that are the connected to the internet provide various types of information to VANET users. Keywords: VANET, RSU, Ad-Hoc Network, URE, ITS

scholarly journals Spatio-Temporal Synchronization of Cross Section Based Sensors for High Precision Microscopic Traffic Data Reconstruction

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3193
Author(s):  
Adrian Fazekas ◽  
Markus Oeser
Keyword(s):  
Data Acquisition ◽  
Cross Section ◽  
Intelligent Transportation Systems ◽  
Estimation Algorithm ◽  
Initial Step ◽  
Original Data ◽  
Transportation Systems ◽  
Location Estimation ◽  
Traffic Data ◽  
Multiple Sensors

The next generation of Intelligent Transportation Systems (ITS) will strongly rely on a high level of detail and coverage in traffic data acquisition. Beyond aggregated traffic parameters like the flux, mean speed, and density used in macroscopic traffic analysis, a continuous location estimation of individual vehicles on a microscopic scale will be required. On the infrastructure side, several sensor techniques exist today that are able to record the data of individual vehicles at a cross-section, such as static radar detectors, laser scanners, or computer vision systems. In order to record the position data of individual vehicles over longer sections, the use of multiple sensors along the road with suitable synchronization and data fusion methods could be adopted. This paper presents appropriate methods considering realistic scale and accuracy conditions of the original data acquisition. Datasets consisting of a timestamp and a speed for each individual vehicle are used as input data. As a first step, a closed formulation for a sensor offset estimation algorithm with simultaneous vehicle registration is presented. Based on this initial step, the datasets are fused to reconstruct microscopic traffic data using quintic Beziér curves. With the derived trajectories, the dependency of the results on the accuracy of the individual sensors is thoroughly investigated. This method enhances the usability of common cross-section-based sensors by enabling the deriving of non-linear vehicle trajectories without the necessity of precise prior synchronization.

Method for analytic subscriber traffic data acquisition in telephone networks

1987 ◽  
Vol 23 (20) ◽  
pp. 1057
Author(s):  
D. Lymberopoulos ◽  
G. Kokkinakis
Keyword(s):  
Data Acquisition ◽  
Traffic Data ◽  
Telephone Networks

Framework for Dynamic OD Matrix Estimation Based on Multi-Source Traffic Data Fusion

2014 ◽  
Vol 505-506 ◽  
pp. 1153-1156 ◽  
Author(s):  
Xu Zhou ◽  
Zhao Liu ◽  
Xiao Xiao Zhao ◽  
Jian Hua Guo
Keyword(s):  
Information Systems ◽  
Traffic Management ◽  
Management Systems ◽  
Traffic Data ◽  
Transportation Management ◽  
Matrix Estimation ◽  
Od Estimation ◽  
The Road ◽  
Data Estimation

The advanced transportation management and information systems (ATMIS) are strengthening the capability of collecting multi-source traffic data constantly from the road networks. Considering the fundamental role of dynamic Origin-Destination data for many advanced traffic management systems, it is promising to apply the multi-source traffic data to improve the dynamic OD estimation. Targeting dynamic OD data estimation, the classical OD data estimation approaches are discussed, and a framework of dynamic OD estimation based on multi-source traffic data is proposed and analyzed. Future researches are recommended in the end.

scholarly journals Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey

2021 ◽  
Vol 13 (23) ◽  
pp. 13068
Author(s):  
Akbar Ali ◽  
Nasir Ayub ◽  
Muhammad Shiraz ◽  
Niamat Ullah ◽  
Abdullah Gani ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Low Cost ◽  
Urban Traffic ◽  
Traffic Data ◽  
Mobile Crowdsensing ◽  
Traffic Efficiency ◽  
Crowd Sensing ◽  
Management Schemes ◽  
Mobile Crowd

The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is to present the literature and propose such a realistic traffic efficiency model to collect vehicular traffic data without roadside sensor deployment and manage traffic dynamically. Today’s urban traffic congestion is one of the core problems to be solved by such a traffic management scheme. Due to traffic congestion, static control systems may stop emergency vehicles during congestion. In daily routine, there are two-time slots in which the traffic is at peak level, which causes traffic congestion to occur in an urban transportation environment. Traffic congestion mostly occurs in peak hours from 8 a.m. to 10 a.m. when people go to offices and students go to educational institutes and when they come back home from 4 p.m. to 8 p.m. The main purpose of this survey is to provide a taxonomy of different traffic management schemes for avoiding traffic congestion. The available literature categorized and classified traffic congestion in urban areas by devising a taxonomy based on the model type, sensor technology, data gathering techniques, selected road infrastructure, traffic flow model, and result verification approaches. Consider the existing urban traffic management schemes to avoid congestion and to provide an alternate path, and lay the foundation for further research based on the IoT using a Mobile crowd sensing-based traffic congestion control model. Mobile crowdsensing has attracted increasing attention in traffic prediction. In mobile crowdsensing, the vehicular traffic data are collected at a very low cost without any special sensor network infrastructure deployment. Mobile crowdsensing is very popular because it can transmit information faster, collect vehicle traffic data at a very low cost by using motorists’ smartphone or GPS vehicular embedded sensor, and it is easy to install, requires no special network deployment, has less maintenance, is compact, and is cheaper compared to other network options.

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