scholarly journals Technology: A Necessary but Not Sufficient Condition for Future Personal Mobility

2018 ◽  
Vol 10 (11) ◽  
pp. 4141 ◽  
Author(s):  
Margarita Martínez-Díaz ◽  
Francesc Soriguera ◽  
Ignacio Pérez
Keyword(s):  
Autonomous Vehicles ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Monitoring ◽  
Sustainable Mobility ◽  
Economic Interests ◽  
Personal Mobility ◽  
Technological Advances ◽  
Potential Benefits ◽  
Potential Improvement

Technological advances revolutionize industrial processes, science, communications, and our way of life. However, developed societies have reached a stage in which the fascination with technological innovations often results in their indiscriminate consumption. In this paper, road traffic is used as a line of argument to demonstrate that the random introduction of technology does not imply benefits to society. Particularly, it is analyzed why some of the potential benefits of technological progress are lost in fields such as traffic monitoring, data handling, and traffic management, or in sustainable mobility initiatives, such as the introduction of electric vehicles or the implementation vehicle sharing projects. The risks faced in the future advent of autonomous vehicles are also discussed, and ideas for improvement suggested. A critical reflection on other transportation modes that are expected to be realized in the near future is included as well. The performed analysis evidences that the potential improvement in personal mobility will not become a reality if it exclusively relies on the latest technological devices, in line with consumers’ fantasies or economic interests. This is a statement that could be generalized to many other fields. The implementation/consumption of a particular technology should not be an objective in itself, but a tool to bring benefits to society.

Joint Human-Automation Decision Making in Road Traffic Management

2017 ◽  
Vol 61 (1) ◽  
pp. 385-389 ◽  
Author(s):  
Natan Morar ◽  
Chris Baber
Keyword(s):  
Decision Making ◽  
Traffic Management ◽  
Road Traffic ◽  
High Reliability ◽  
Traffic Monitoring ◽  
Human Intervention ◽  
Joint Decision ◽  
Monitoring Task ◽  
Reliability Level ◽  
Overall Performance

In this paper we explore automation bias in terms of joint decision making between humans and automation. In an experiment, participants made decisions, and indicated the reason for this decision, in a road traffic monitoring task with the aid of automation of varying reliability (i.e., 25% or 81%). Reliability level had a clear impact on the user’s behavior: at low reliability, participants ignored automation suggestion and rely on their own decision making, whereas in the high reliability condition, participants tended to accept the automation suggestion (even if this was incorrect). Overall, performance is higher as a result of the human intervention that would be expected from automation alone, i.e., accuracy is in the region of 87-96% on all conditions. Performance is affected by the order in which the human and automation give their answers and how much detail they are required to provide. We consider these results in terms of a theory of joint decision making. [156 words]

“Getting High Resolution Out of A High Voltage Microscope”

1980 ◽  
Vol 38 ◽  
pp. 822-825
Author(s):  
David J. Smith
Keyword(s):  
Electron Microscope ◽  
High Resolution ◽  
High Voltage ◽  
Theoretical Limit ◽  
Voltage Electron ◽  
High Voltage Electron Microscope ◽  
High Voltage Electron ◽  
Technological Advances ◽  
Potential Improvement ◽  
Lower Voltage

The initial attractions of the high voltage electron microscope (HVEM) stemmed mainly from the possibility of considerable increases in electron penetration through thick specimens compared with conventional 100KV microscopes, although the potential improvement in resolution associated with the decrease in election wavelength had been fully appreciated for many years (eg. Cosslett, 1946)1, even if not realizable in practice. Subsequent technological advances enabled the performance of lower voltage machines to be brought closer to the theoretical limit, to be followed in turn by more recent projects which have been successful, eventually, in achieving even higher resolution with dedicated higher voltage instruments such as those at Kyoto (500KV)2, Munich (400KV)3, Ibaraki (1250KV)4 and Cambridge (600KV)5. It does not necessarily follow however that the performance of journal high voltage microscopes can be easily upgraded, retrospectively, to the same level, as will be discussed in detail below.

Road Traffic Monitoring

IEE Review ◽  
1989 ◽  
Vol 35 (5) ◽  
pp. 188
Author(s):  
P.L. Belcher
Keyword(s):  
Road Traffic ◽  
Traffic Monitoring

scholarly journals LPWAN-based hybrid backhaul communication for intelligent transportation systems: architecture and performance evaluation

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Taghi Shahgholi ◽  
Amir Sheikhahmadi ◽  
Keyhan Khamforoosh ◽  
Sadoon Azizi
Keyword(s):  
Low Power ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Traffic Monitoring ◽  
Transportation Systems ◽  
Area Network ◽  
Emergency Vehicle ◽  
Wide Area Network

AbstractIncreased number of the vehicles on the streets around the world has led to several problems including traffic congestion, emissions, and huge fuel consumption in many regions. With advances in wireless and traffic technologies, the Intelligent Transportation System (ITS) has been introduced as a viable solution for solving these problems by implementing more efficient use of the current infrastructures. In this paper, the possibility of using cellular-based Low-Power Wide-Area Network (LPWAN) communications, LTE-M and NB-IoT, for ITS applications has been investigated. LTE-M and NB-IoT are designed to provide long range, low power and low cost communication infrastructures and can be a promising option which has the potential to be employed immediately in real systems. In this paper, we have proposed an architecture to employ the LPWAN as a backhaul infrastructure for ITS and to understand the feasibility of the proposed model, two applications with low and high delay requirements have been examined: road traffic monitoring and emergency vehicle management. Then, the performance of using LTE-M and NB-IoT for providing backhaul communication infrastructure has been evaluated in a realistic simulation environment and compared for these two scenarios in terms of end-to-end latency per user. Simulation of Urban MObility has been used for realistic traffic generation and a Python-based program has been developed for evaluation of the communication system. The simulation results demonstrate the feasibility of using LPWAN for ITS backhaul infrastructure mostly in favor of the LTE-M over NB-IoT.

Night-time disability glare of constant-light LED traffic monitoring fill light

2021 ◽  
pp. 147715352098226
Author(s):  
X Cai ◽  
L Quan ◽  
J Wu ◽  
Y He
Keyword(s):  
Dynamic Range ◽  
Road Traffic ◽  
Reaction Times ◽  
High Dynamic Range ◽  
Luminance Contrast ◽  
Traffic Monitoring ◽  
Constant Light ◽  
Night Time ◽  
Disability Glare ◽  
Small Targets

Fill light, used to helps cameras capture road traffic conditions at night, can lead to serious visual consequences for drivers. Research on disability glare from LED fill light is scarce and therefore this study explored strategies for controlling disability glare of constant-light LED traffic monitoring fill light. The threshold increment was used as an index to evaluate disability glare. The effective disability glare area of LED traffic monitoring fill light was determined based on high dynamic range technology. According to visual efficacy theory, there is a relationship between disability glare conditions and reaction times. The influencing factors include background luminance, luminance contrast and fill light luminance. The results showed that disability glare was the most intense in a range of 20 m to 30 m in front of LED fill light. To reduce the effect of disability glare on drivers, luminance contrast between small targets and the road surface should be greater than 0.5. The fill light luminance should not be greater than 100,000 cd/m2.

scholarly journals The Effects of Mobility as a Service and Autonomous Vehicles on People’s Willingness to Own a Car in the Future

2021 ◽  
Vol 13 (4) ◽  
pp. 1962
Author(s):  
Timo Liljamo ◽  
Heikki Liimatainen ◽  
Markus Pöllänen ◽  
Riku Viri
Keyword(s):  
Public Transport ◽  
Autonomous Vehicles ◽  
Travel Behaviour ◽  
Car Ownership ◽  
Key Factors ◽  
Sustainable Mobility ◽  
Factors Affecting ◽  
Mobility Service ◽  
The Future ◽  
Mobility Behaviour

Car ownership is one of the key factors affecting travel behaviour and thus also essential in terms of sustainable mobility. This study examines car ownership and how people’s willingness to own a car may change in the future, when considering the effects of public transport, Mobility as a Service (MaaS) and automated vehicles (AVs). Results of two citizen surveys conducted with representative samples (NAV-survey = 2036; NMaaS-survey = 1176) of Finns aged 18–64 are presented. The results show that 39% of respondents would not want or need to own a car if public transport connections were good enough, 58% if the described mobility service was available and 65% if all vehicles in traffic were automated. Hence, car ownership can decrease as a result of the implementation of AVs and MaaS, and higher public transport quality of service. Current mobility behaviour has a strong correlation to car ownership, as respondents who use public transport frequently feel less of a will or need to own a car than others. Generally, women and younger people feel less of a will or need to own a car, but factors such as educational level and residential location seem to have a relatively low effect.

scholarly journals Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3425
Author(s):  
Huanping Li ◽  
Jian Wang ◽  
Guopeng Bai ◽  
Xiaowei Hu
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Flow Model ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Transformation Model ◽  
Hydrodynamic Theory ◽  
Traffic Flow Model ◽  
Traffic System ◽  
The Stability

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

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