scholarly journals Overview of emerging road traffic data collection methods

2021 ◽  
Author(s):  
Sandra Mihalinac ◽  
Maja Ahac ◽  
Saša Ahac ◽  
Miroslav Šimun
Keyword(s):  
Data Collection ◽  
Traffic Flow ◽  
Road Network ◽  
Road Traffic ◽  
Traffic Volume ◽  
Transport Systems ◽  
Traffic Data ◽  
Data Collection Methods ◽  
Traffic Data Collection ◽  
Collection Methods

It is a well-known fact that the data on road traffic flow characteristics is essential for sustainable road network management. First road traffic volume counts date back to the 1950s when short-term periodic road traffic counts were carried out in cities worldwide. Manual traffic counting is one of the oldest and most technologically simple methods to obtain data on road traffic volume and its composition. Today, because of the ever-growing road transport demand, it has become clear that the development of Intelligent Transport Systems (ITS) is vital to increase safety and tackle increasing emission and congestion problems. The introduction of ITS highly depends on the quality and quantity of traffic data. Under the growing requirement of long-term traffic flow information, various traffic data collection methods have evolved. They allow systematic recording of the traffic flow volume and composition but also vehicle speed, total gross weight, number of axles, axle load and travel destination. This data, which is collected continuously over longer periods, enables a detailed analysis of traffic flows, and represents the basis for decision making in planning, designing, construction and maintenance of road infrastructure. This paper gives an overview of traditional and emerging traffic data collection methods - both fixed and mobile - and the analysis of the current road traffic data collection methods used on the Croatian road network, in terms of their potential and limitations.

scholarly journals A traffic data collection and analysis method based on wireless sensor network

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Huan Wang ◽  
Min Ouyang ◽  
Qingyuan Meng ◽  
Qian Kong
Keyword(s):  
Wireless Sensor Network ◽  
Data Collection ◽  
Sensor Network ◽  
Traffic Flow ◽  
Wireless Sensor ◽  
Traffic Data ◽  
Flow Data ◽  
Analysis Method ◽  
Traffic Data Collection ◽  
Data Collection And Analysis

AbstractWith the rapid development of urbanization, collecting and analyzing traffic flow data are of great significance to build intelligent cities. The paper proposes a novel traffic data collection method based on wireless sensor network (WSN), which cannot only collect traffic flow data, but also record the speed and position of vehicles. On this basis, the paper proposes a data analysis method based on incremental noise addition for traffic flow data, which provides a criterion for chaotic identification. The method adds noise of different intensities to the signal incrementally by an improved surrogate data method and uses the delayed mutual information to measure the complexity of signals. Based on these steps, the trend of complexity change of mixed signal can be used to identify signal characteristics. The numerical experiments show that, based on incremental noise addition, the complexity trends of periodic data, random data, and chaotic data are different. The application of the method opens a new way for traffic flow data collection and analysis.

Fractal Characteristics of Mountain Cities' Traffic Flow Based on EMD and Multifractal

2013 ◽  
Vol 831 ◽  
pp. 430-434
Author(s):  
Ling Zhao ◽  
Juan Cao ◽  
Bo Mi
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Road Traffic ◽  
Multifractal Spectrum ◽  
Health State ◽  
Traffic Data ◽  
Time Data ◽  
Flow Signal ◽  
The Road ◽  
Fractal Characteristics

Aim at the characteristics of the mountain cities road traffic network, the short-time data signals in the congestion state of the road network traffic is analyzed. Fractal characteristics of traffic data signal is in research based on the self-similarity of the traffic data signals. The non-stationary property of the traffic flow signal in the congestion state is known through the calculation of the multifractal spectrum of the traffic flow signal based on EMD. The experimental results show the feasibility of the method, which also can provide theoretical support for the traffic flow control of the mountain city road network in the sub-health state.

scholarly journals Positional Accuracy Assessment for Updating Authoritative Geospatial Datasets Based on Open Source Data and Remotely Sensed Images

2020 ◽  
Vol 26 (2) ◽  
pp. 70-84 ◽  
Author(s):  
Mervat S. Jasem ◽  
Odey AL-Hamadani
Keyword(s):  
High Resolution ◽  
Data Collection ◽  
Open Source ◽  
Spatial Data ◽  
Road Network ◽  
Data Sources ◽  
National Standard ◽  
Positional Accuracy ◽  
Data Collection Methods ◽  
Collection Methods

OpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtained from the Mayoralty of Baghdad (MB). The methodology of, U.S. National Standard Spatial Data Accuracy (NSSDA) was applied to measure the degree of agreement between each data source and the formal dataset (MB) in terms of horizontal positional accuracy by computing RMSE and NSSDA values. The study concluded that each of the three data sources does not agree with the MB dataset in both study sites AL-Aadhamiyah and AL-Kadhumiyah in terms of positional accuracy.

scholarly journals The Impact of Automated Vehicles on Traffic Flow and Road Capacity on Urban Road Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Ji Eun Park ◽  
Wanhee Byun ◽  
Youngchan Kim ◽  
Hyeonjun Ahn ◽  
Doh Kyoum Shin
Keyword(s):  
Traffic Flow ◽  
Road Network ◽  
Traffic Volume ◽  
Transport Systems ◽  
Automated Vehicles ◽  
Average Delay ◽  
The Road ◽  
Capacity Increase ◽  
Road Capacity ◽  
The Impact

Automated vehicles (AVs) are believed to have great potential to improve the traffic capacity and efficiency of the current transport systems. Despite positive findings of the impact of AVs on traffic flow and potential road capacity increase for highways, few studies have been performed regarding the impact of AVs on urban roads. Moreover, studies considering traffic volume increase with a mixture of AVs and human-driven vehicles (HDVs) have rarely been conducted. Therefore, this study investigated the impact of gradual increments of AV penetration and traffic volume on urban roads. The study adopted a microsimulation approach using VISSIM with a Wiedmann 74 model for car-following behavior. Parameters for AVs were set at the SAE level 4 of automation. A real road network was chosen for the simulation having 13 intersections in a total distance of 4.5 km. The road network had various numbers of lanes from a single lane to five lanes in one direction. The network consists of a main arterial road and a parallel road serving nearby commercial and residential blocks. In total, 36 scenarios were investigated by a combination of AV penetrations and an increase in traffic volumes. The study found that, as AV penetration increased, traffic flow also improved, with a reduction of the average delay time of up to 31%. Also, as expected, links with three or four lanes had a more significant impact on the delay. In terms of road capacity increase, when the penetration of AVs was saturated at 100%, the road network could accommodate 40% more traffic.

scholarly journals Utilizing UAVs Technology on Microscopic Traffic Naturalistic Data Acquirement

2021 ◽  
Vol 6 (6) ◽  
pp. 89
Author(s):  
Apostolos Anagnostopoulos ◽  
Fotini Kehagia
Keyword(s):  
Traffic Flow ◽  
Field Experiments ◽  
Flow Characteristics ◽  
Cost Effective ◽  
Transport Systems ◽  
Fundamental Aspect ◽  
Traffic Data ◽  
Vehicle Trajectories ◽  
Traffic Data Collection ◽  
Vehicle Trajectory

Research into collecting and measuring reliable, accurate, and naturalistic microscopic traffic data is a fundamental aspect in road network planning scientific literature. The vehicle trajectory is one of the main variables in traffic flow theory that allows to extract information regarding microscopic traffic flow characteristics. Several methods and techniques have been applied regarding the acquisition of vehicle trajectory. The forthcoming applications of intelligent transport systems on vehicles and infrastructure require sufficient and innovative tools to calibrate existing models on more complex situations. Unmanned aerial vehicles (UAVs) are one of the most emerging technologies being used recently in the transportation field to monitor and analyze the traffic flow. The aim of this paper is to examine the use of UAVs as a tool for microscopic traffic data collection and analysis. A comprehensive guiding framework for accurate and cost-effective naturalistic traffic surveys and analysis using UAVs is proposed and presented in detail. Field experiments of acquiring vehicle trajectories on two multilane roundabouts were carried out following the proposed framework. Results of the experiment indicate the usefulness of the UAVs technology on various traffic analysis studies. The results of this study provide a practical guide regarding vehicle trajectory acquirement using UAVs.

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