The increasing worldwide demand on urban road transportation systems requires more restrictive measures and policies to reduce congestion, time delay and pollution. Autonomous vehicle mobility services, both shared and private, are possibly a good step towards a better road transportation future. This article aims to study the expected impact of private autonomous vehicles on road traffic parameters from a macroscopic level. The proposed methodology focuses on finding the different effects of different combinations of autonomous vehicle penetration and Passenger Car Units (PCU) on the chosen road traffic model. Four parameters are studied: traveled daily kilometers, daily hours, total daily delay and average network speed. The analysis improves the four parameters differently by implementing autonomous vehicles. The parameter total delay has the most significant reduction. Finally, several mathematical models are developed for the percentage of improvement for each chosen parameter.
Cooperative Intelligent Transport Systems is C-ITS a set of ITS technologies that can provide services supported by the permanent, real time, information circulation among the components of the system. The paper aims to give an overview related to the modelling and evaluation possibilities of cooperative intelligent transportation system and to clarify the definition of the C-ITS and its differences from the regular ITS solutions. The paper introduce a proposed architecture of C-ITS modelling framework by describing C-ITS components, transferred data and its applications.
Background
Telesonography systems have been developed to overcome barriers to accessing diagnostic ultrasound for patients in rural and remote communities. However, most previous telesonography systems have been designed for performing only abdominal and obstetrical exams. In this paper, we describe the development and assessment of a musculoskeletal (MSK) telesonography system.
Methods
We developed a 4-degrees-of-freedom (DOF) robot to manipulate an ultrasound probe. The robot was remotely controlled by a radiologist operating a joystick at the master site. The telesonography system was used to scan participants’ forearms, and all participants were conventionally scanned for comparison. Participants and radiologists were surveyed regarding their experience. Images from both scanning methods were independently assessed by an MSK radiologist.
Results
All ten ultrasound exams were successfully performed using our developed MSK telesonography system, with no significant delay in movement. The duration (mean ± standard deviation) of telerobotic and conventional exams was 4.6 ± 0.9 and 1.4 ± 0.5 min, respectively (p = 0.039). An MSK radiologist rated quality of real-time ultrasound images transmitted over an internet connection as “very good” for all telesonography exams, and participants rated communication with the radiologist as “very good” or “good” for all exams. Visualisation of anatomic structures was similar between telerobotic and conventional methods, with no statistically significant differences.
Conclusions
The MSK telesonography system developed in this study is feasible for performing soft tissue ultrasound exams. The advancement of this system may allow MSK ultrasound exams to be performed over long distances, increasing access to ultrasound for patients in rural and remote communities.
Several transport policies reduce pollution levels caused by private vehicles by introducing autonomous or electric vehicles and encouraging mode shift from private to public transport through park and ride (P&R) facilities. However, combining the policies of introducing autonomous vehicles with the implementation of electric vehicles and using the P&R system could amplify the decrease of transport sector emissions. The COPERT software has been used to calculate the emissions. This article aims to study these policies and determine which combinations can better reduce pollution. The result shows that each combination of autonomous vehicles reduces pollution to different degrees. In conclusion, the shift to more sustainable transport modes through autonomous electric vehicles and P&R systems reduces pollution in the urban environment to a higher percentage. In contrast, the combination of autonomous vehicles has lower emission reduction but is easier to implement with the currently available infrastructure.
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