A Security-Minded Approach to Vehicle Automation, Road Infrastructure Technology, and Connectivity

2015 ◽  
Author(s):  
H.A. Boyes ◽  
A.E.A. Luck
Keyword(s):  
Road Infrastructure ◽  
Vehicle Automation

The influence of driver stress, partial-vehicle automation, and subjective state on driver performance

2005 ◽  
Author(s):  
Gregory J. Funke ◽  
Gerald Matthews ◽  
Joel S. Warm ◽  
Amanda Emo ◽  
Angela N. Fellner
Keyword(s):  
Subjective State ◽  
Driver Performance ◽  
Vehicle Automation ◽  
Driver Stress

Integration of cross asset risk assessment into road infrastructure asset management

2015 ◽  
Vol 105 (28) ◽  
pp. 1-7
Author(s):  
Alfred Weninger-Vycudil ◽  
Barbara Brozek ◽  
Roland Spielhofer ◽  
Chris Britton ◽  
Mark Oldfield
Keyword(s):  
Risk Assessment ◽  
Asset Management ◽  
Road Infrastructure ◽  
Asset Risk ◽  
Infrastructure Asset Management

PENGARUH INFRASTRUKTUR SECARA SPASIAL TERHADAP KONVERGENSI PERTUMBUHAN EKONOMI DI INDONESIA

INFO ARTHA ◽  
2017 ◽  
Vol 1 ◽  
pp. 17-28
Author(s):  
Anisa Fahmi
Keyword(s):  
Economic Growth ◽  
Regional Economics ◽  
Developed Countries ◽  
Road Infrastructure ◽  
Long Run ◽  
Catch Up ◽  
The Developed Countries ◽  
Positive Effect ◽  
Neoclassical Growth Theory

Motivated by inter-regional disparities condition that occurs persistently, this study examines the Indonesian economy in the long run in order to know whether it tends to converge or diverge. This convergence is based on the Solow Neoclassical growth theory assuming the existence of diminishing returns to capital so that when the developed countries reach steady state conditions, developing countries will continuously grow up to 'catch-up' with developed countries. Based on regional economics perspective, each region can not be treated as a stand-alone unit,therefore, this study also focuses on the influence of spatial dependency and infrastructure. Economical and political situations of a region will influence policy in that region which will also have an impact to the neighboring regions. The estimation results of spatial cross-regressive model using fixed effect method consistently confirmed that the Indonesian economy in the long term will likely converge with a speed of 8.08 percent per year. Other findings are road infrastructure has a positive effect on economic growth and investment and road infrastructure are spatially showed a positive effect on economic growth. In other words, the investment and infrastructure of a region does not only affect the economic growth of that region but also to the economy of the contiguous regions. 

PENGARUH PEMBANGUNAN INFRASTRUKTUR TERHADAP PDRB DI PROVINSI INDONESIA

Wahana ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 15-27
Author(s):  
Suripto Suripto ◽  
Eva Dwi Lestari
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Infrastructure Investment ◽  
Water Infrastructure ◽  
Infrastructure Development ◽  
Road Infrastructure ◽  
Health Infrastructure ◽  
Spatial Coverage ◽  
The Government

Economic growth is one indicator to measure  the success of economic development in a country. Economic development is closely related to infrastructure. Infrastructure development will have an impact on economic growth both directly and indirectly. Therefore, the role of the government in determining infrastructure development policies is very important to increase economic growth in Indonesia. The purpose of this study is to determine the effect of infrastructure on economic growth in Indonesia including road infrastructure, electricity infrastructure, investment, water infrastructure, education infrastructure and health infrastructure in Indonesia in 2015-2017.The analytical tool used in this study is panel data regression with the approach of Fixed Effect Model. The spatial coverage of this study is all provinces in Indonesia, namely 34 provinces, with a series of data from 2015 to 2017 with a total of 102 observations. The data used is secondary data obtained from BPS Indonesia.The results of the study show that (1) the road infrastructure variables have a negative and not significant effect on GDRP. (2) electrical infrastructure variables have a negative and not significant effect on GDRP. (3) investment variables have a positive and significant effect on GDRP. (4) water infrastructure variables have a positive and not significant effect on GDRP. (5) educational infrastructure variables have a positive and not significant effect on GDRP. (6) health infrastructure variables have a positive and significant effect on GDRP. Keywords: development, infrastructure, investment, GDRP, panel data

Safety Enhancement by Automated Driving: What are the Relevant Scenarios?

2020 ◽  
Vol 64 (1) ◽  
pp. 1686-1690
Author(s):  
Niklas Grabbe ◽  
Michael Höcher ◽  
Alexander Thanos ◽  
Klaus Bengler
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Test Cases ◽  
Automated Driving ◽  
Road Traffic Safety ◽  
Human Driver ◽  
Driving Task ◽  
Promising Solution ◽  
Vehicle Automation ◽  
Safety Enhancement

Automated driving offers great possibilities in traffic safety advancement. However, evidence of safety cannot be provided by current validation methods. One promising solution to overcome the approval trap (Winner, 2015) could be the scenario-based approach. Unfortunately, this approach still results in a huge number of test cases. One possible way out is to show the current, incorrect path in the argumentation and strategy of vehicle automation, and focus on the systemic mechanisms of road traffic safety. This paper therefore argues the case for defining relevant scenarios and analysing them systemically in order to ultimately reduce the test cases. The relevant scenarios are based on the strengths and weaknesses, in terms of the driving task, for both the human driver and automation. Finally, scenarios as criteria for exclusion are being proposed in order to systemically assess the contribution of the human driver and automation to road safety.

scholarly journals The Way Forward for Indirect Structural Health Monitoring (iSHM) Using Connected and Automated Vehicles in Europe

2021 ◽  
Vol 6 (3) ◽  
pp. 43
Author(s):  
Konstantinos Gkoumas ◽  
Kyriaki Gkoktsi ◽  
Flavio Bono ◽  
Maria Cristina Galassi ◽  
Daniel Tirelli
Keyword(s):  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Transport Infrastructure ◽  
Policy Framework ◽  
Strategic Decisions ◽  
Automated Vehicles ◽  
Civil Infrastructures ◽  
Vehicle Automation ◽  
Labor Requirements

Europe’s aging transportation infrastructure requires optimized maintenance programs. However, data and monitoring systems may not be readily available to support strategic decisions or they may require costly installations in terms of time and labor requirements. In recent years, the possibility of monitoring bridges by indirectly sensing relevant parameters from traveling vehicles has emerged—an approach that would allow for the elimination of the costly installation of sensors and monitoring campaigns. The advantages of cooperative, connected, and automated mobility (CCAM), which is expected to become a reality in Europe towards the end of this decade, should therefore be considered for the future development of iSHM strategies. A critical review of methods and strategies for CCAM, including Intelligent Transportation Systems, is a prerequisite for moving towards the goal of identifying the synergies between CCAM and civil infrastructures, in line with future developments in vehicle automation. This study presents the policy framework of CCAM in Europe and discusses the policy enablers and bottlenecks of using CCAM in the drive-by monitoring of transport infrastructure. It also highlights the current direction of research within the iSHM paradigm towards the identification of technologies and methods that could benefit from the use of connected and automated vehicles (CAVs).

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