scholarly journals A data-driven approach to characterize the impact of connected and autonomous vehicles on traffic flow

2020 ◽  
pp. 1-9
Author(s):  
Amir Bahador Parsa ◽  
Ramin Shabanpour ◽  
Abolfazl (Kouros) Mohammadian ◽  
Joshua Auld ◽  
Thomas Stephens
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Data Driven ◽  
Data Driven Approach ◽  
The Impact

scholarly journals High-Resolution Traffic Sensing with Probe Autonomous Vehicles: A Data-Driven Approach

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 464
Author(s):  
Wei Ma ◽  
Sean Qian
Keyword(s):  
High Resolution ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Data Driven ◽  
Traffic Information ◽  
Flow Density ◽  
Massive Data ◽  
Market Penetration ◽  
High Resolution Data ◽  
Data Driven Approach

Recent decades have witnessed the breakthrough of autonomous vehicles (AVs), and the sensing capabilities of AVs have been dramatically improved. Various sensors installed on AVs will be collecting massive data and perceiving the surrounding traffic continuously. In fact, a fleet of AVs can serve as floating (or probe) sensors, which can be utilized to infer traffic information while cruising around the roadway networks. Unlike conventional traffic sensing methods relying on fixed location sensors or moving sensors that acquire only the information of their carrying vehicle, this paper leverages data from AVs carrying sensors for not only the information of the AVs, but also the characteristics of the surrounding traffic. A high-resolution data-driven traffic sensing framework is proposed, which estimates the fundamental traffic state characteristics, namely, flow, density and speed in high spatio-temporal resolutions and of each lane on a general road, and it is developed under different levels of AV perception capabilities and for any AV market penetration rate. Experimental results show that the proposed method achieves high accuracy even with a low AV market penetration rate. This study would help policymakers and private sectors (e.g., Waymo) to understand the values of massive data collected by AVs in traffic operation and management.

La orientación al dato, nuevos desafíos

Tábula ◽  
2021 ◽  
Author(s):  
Miguel Ángel Amutio Gómez
Keyword(s):  
European Union ◽  
Digital Transformation ◽  
Data Driven ◽  
The European Union ◽  
Data Preservation ◽  
The Future ◽  
Data Driven Approach ◽  
New Challenges ◽  
The Impact

La orientación al dato en el contexto de la transformación digital lleva aparejada la aparición de nuevas regulaciones, dinámicas de gobernanza y roles, y servicios, junto con las correspondientes prácticas, instrumentos y estándares. A la vez se suscitan retos en relación con la ciberseguridad y la preservación de los datos. En este artículo se exponen la transformación digital y la orientación al dato, la proyección de lo anterior en la administración digital, el contexto de la Unión Europea, trayectoria y su orientación, aspectos de la interoperabilidad, ciberseguridad y preservación de los datos, cuestiones de gobernanza y roles en la orientación al dato y, finalmente, unas conclusiones. The data-driven approach in the context of digital transformation entails the appearance of new regulations, governance dynamics and roles, and services, together with the corresponding practices, instruments and standards. At the same time new challenges appear in relation to cybersecurity and data preservation. This article presents the digital transformation and data-driven approach, the impact in digital administration, the context of the European Union, trajectory and orientation towards the future, along with aspects of interoperability, cybersecurity and data preservation, as well as issues of governance and roles in data orientation and finally some conclusions.

scholarly journals Data-driven profiling of traffic flow with varying road conditions

2019 ◽  
pp. 149-157 ◽  
Author(s):  
O K Golovnin
Keyword(s):  
Traffic Flow ◽  
Road Traffic ◽  
Flow Characteristics ◽  
Weather Conditions ◽  
Flow Speed ◽  
Data Driven ◽  
The Road ◽  
Data Driven Approach ◽  
Traffic Flow Characteristics ◽  
The City

The article describes the road, institutional and weather conditions that affect the traffic flow. I proposed a method for traffic flow profiling using a data-driven approach. The method operates with macroscopic traffic flow characteristics and detailed data of road conditions. The article presents the results of traffic flow speed and intensity profiling taking into account weather conditions. The study used road traffic and conditions data for the city of Aarhus, Denmark. The results showed that the method is effective for traffic flow forecasting due to varying road conditions.

scholarly journals An attempt to evaluate the influence of automated vehicles on traffic flow and design of road infrastructure

2019 ◽  
Vol 2019 (9) ◽  
pp. 29-38
Author(s):  
Nina Kozaczka ◽  
Stanisław Gaca
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Communication Systems ◽  
Road Traffic ◽  
Negative Impact ◽  
Automated Vehicles ◽  
Road Infrastructure ◽  
The Road ◽  
Self Driving Cars ◽  
The Impact

The article evaluates the impact of autonomous vehicles on road infrastructure de- sign, road traffic conditions and safety based on a review of existing literature. Levels of driv- ing automation and equipment of self-driving vehicles were presented. Attention was drawn to the benefits of developing communication systems between vehicle and the environment. The possible negative impact of autonomous vehicles on mixed traffic capacity was noted. The potential needs to adapt the road infrastructure to the traffic flow of automated vehicles were also presented. Separation of the lane, dedicated to self-driving vehicles, with a high share of these vehicles was presented as an element that improves the flow of traffic and safe- ty. Keywords: Autonomous vehicles; Road infrastructure; Self-driving cars

Effect of connected and autonomous vehicles on traffic flow at a bidirectional road

2021 ◽  
Author(s):  
H. Echab ◽  
A. Khallouk ◽  
H. Ez-Zahraouy
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Negative Influence ◽  
Conventional Vehicle ◽  
Cooperative Driving ◽  
Moving Vehicles ◽  
Penetration Ratio ◽  
Slow Moving ◽  
The Impact ◽  
Cv Model

The objective of this study was to investigate the impact of connected and autonomous vehicles (CAVs) on traffic flow under various parameters. For this purpose, we propose a mixed CAV and conventional vehicle (CV) model to investigate a bidirectional two-lane traffic flow under the periodic boundary condition. The traffic flux and the phase diagrams of the system in the ([Formula: see text]) area are constructed in both cases: with and without CAVs. The overtaking frequency is also calculated. The simulation findings show that the traffic capacity is greatly enhanced with the increase in the CAV penetration ratio. Owing to the cooperative driving strategy, with the increase in penetration ratio of the CAV, the portion of smooth overtaking is boosted. Furthermore, it is found that the traffic throughput is positively correlated to the speed limit of the fast vehicle where the flux increases as [Formula: see text] increases. Also, even if there is a low rate of slow moving vehicles in the system, it will have an appreciable and a significant negative influence.

Will the relevance of review language and destination attractions be helpful? A data-driven approach

2020 ◽  
pp. 135676672095035
Author(s):  
Sunyoung Hlee ◽  
Hyunae Lee ◽  
Chulmo Koo ◽  
Namho Chung
Keyword(s):  
Online Reviews ◽  
Data Driven ◽  
Online Review ◽  
Cognitive Fit ◽  
Theoretical Contribution ◽  
Language Style ◽  
Data Driven Approach ◽  
Managerial Implications ◽  
Tourism Destinations ◽  
The Impact

Because tourism destinations are difficult to assess in certain standard aspects, the factors that contribute to the helpfulness of reviews remain largely unknown. Moreover, the helpfulness of online reviews has not been explored in terms of the interaction between language style (high- vs. low-cognitive) and attraction type (hedonic vs. utilitarian). Hence, this study examines the impact of language style on the helpfulness of an online review of an attraction, depending on the type of attraction and the meaning of the destination. This study’s data included 8,032 reviews of four attractions (2 hedonic x 2 utilitarian), drawn from TripAdvisor in two different meanings of destinations. Specifically, our findings indicate that when a reviewer posts a utilitarian attraction of the destination, high-cognitive language is perceived to be more helpful. First, we discuss the theoretical contribution of our study using cognitive fit theory, and then provide the study’s managerial implications.

scholarly journals Discovery of the Environmental Factors Affecting Urban Dwellers’ Mental Health: A Data-Driven Approach

2020 ◽  
Vol 17 (21) ◽  
pp. 8167
Author(s):  
Chao Wu ◽  
Pei Zheng ◽  
Xinyuan Xu ◽  
Shuhan Chen ◽  
Nasi Wang ◽  
...  
Keyword(s):  
Mental Health ◽  
Environmental Factors ◽  
Mental States ◽  
Data Driven ◽  
Neural Network Modeling ◽  
Starting Point ◽  
Data Driven Approach ◽  
Linear And Nonlinear ◽  
The Impact ◽  
Maximal Information Coefficient

Mental health is the foundation of health and happiness as well as the basis for an individual’s meaningful life. The environmental and social health of a city can measure the mental state of people living in a certain areas, and exploring urban dwellers’ mental states is an important factor in understanding and better managing cities. New dynamic and granular urban data provide us with a way to determine the environmental factors that affect the mental states of urban dwellers. The characteristics of the maximal information coefficient can identify the linear and nonlinear relationships so that we can fully identify the physical and social environmental factors that affect urban dwellers’ mental states and further test these relationships through linear and nonlinear modeling. Taking the Greater London as an example, we used data from the London Datastore to discover the environmental factors that had the highest correlation with urban mental health from 2015 to 2017 and to prove that they had a high nonlinear correlation through neural network modeling. This paper aimed to use a data-driven approach to find environmental factors that had not yet received enough attention and to provide a starting point for research by establishing hypotheses for further exploration of the impact of environmental factors on mental health.

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