scholarly journals Computational Solutions Based on Bayesian Networks to Hierarchize and to Predict Factors Influencing Gender Fairness in the Transport System: Four Use Cases

2021 ◽  
Vol 13 (20) ◽  
pp. 11372
Author(s):  
Gemma Dolores Molero ◽  
Sara Poveda-Reyes ◽  
Ashwani Kumar Malviya ◽  
Elena García-Jiménez ◽  
Maria Chiara Leva ◽  
...  
Keyword(s):  
Bayesian Networks ◽  
Transport System ◽  
Autonomous Vehicles ◽  
Personal Space ◽  
Use Cases ◽  
Railway Transport ◽  
Analytic Hierarchy ◽  
Perception Of Safety ◽  
Level 3 ◽  
The Difference

Previous studies have highlighted inequalities and gender differences in the transport system. Some factors or fairness characteristics (FCs) strongly influence gender fairness in the transport system. The difference with previous studies, which focus on general concepts, is the incorporation of level 3 FCs, which are more detailed aspects or measures that can be implemented by companies or infrastructure managers and operators in order to increase fairness and inclusion in each use case. The aim of this paper is to find computational solutions, Bayesian networks, and analytic hierarchy processes capable of hierarchizing level 3 FCs and to predict by simulation their values in the case of applying some improvements. This methodology was applied to data from women in four use cases: railway transport, autonomous vehicles, bicycle sharing stations, and transport employment. The results showed that fairer railway transport requires increased personal space, hospitality rooms, help points, and helpline numbers. For autonomous vehicles, the perception of safety, security, and sustainability should be increased. The priorities for bicycle sharing stations are safer cycling paths avoiding hilly terrains and introducing electric bicycles, child seats, or trailers to carry cargo. In transport employment, the priorities are fair recruitment and promotion processes and the development of family-friendly policies.

scholarly journals Application of Mathematical and Computational Methods to Identify Women’s Priorities in Transport

2021 ◽  
Vol 13 (5) ◽  
pp. 2845
Author(s):  
Sara Poveda-Reyes ◽  
Ashwani Kumar Malviya ◽  
Elena García-Jiménez ◽  
Gemma Dolores Molero ◽  
Maria Chiara Leva ◽  
...  
Keyword(s):  
Transport System ◽  
Autonomous Vehicles ◽  
Transport Sector ◽  
Sustainable Society ◽  
Analytic Hierarchy ◽  
Family Responsibilities ◽  
Factors Affecting ◽  
Participation Of Women ◽  
Bike Sharing ◽  
Safe Transport

It is well established that the transport sector is not an equalitarian sector. To develop a sustainable society, a more equalitarian and safe transport system for both users and transport sector employees is needed. This work prioritizes the needs and barriers previously identified as relevant among transport system users and employees for four different transport scenarios (railways, autonomous vehicles (AVs), bicycle-sharing services (BSSs), and employment). The aim of this paper is to prioritize the factors affecting women in these four transport scenarios with the help of a survey followed by the application of mathematical and computational algorithms based on the analytic hierarchy process (AHP) methodology. The identification of factors with higher influence in the fair participation of women in the transport sector will help transport planners, bike-sharing system owners, decision-makers, transport companies, and regulatory professionals to develop measures that could plausibly increase the proportion of women as users of BSSs, users of rail public transport, and AVs, as well as employees in the transport sector for a sustainable society. The results indicated that safety and security were the most challenging factors for railways. Weather, topography, and family responsibilities were shown to have a high influence on the use of BSSs. In the case of autonomous vehicles, the simultaneity and trust in the technology are the main opportunities to influence the acceptance of such vehicles. Finally, for transport employment, caring and parenting responsibilities were the factors that had the largest effect. Some differences in priorities were found for different profiles of women.

scholarly journals Implications of Autonomous Vehicles for Accessibility and Transport Equity: A Framework Based on Literature

2021 ◽  
Vol 13 (8) ◽  
pp. 4448
Author(s):  
Alberto Dianin ◽  
Elisa Ravazzoli ◽  
Georg Hauger
Keyword(s):  
Conceptual Model ◽  
Transport System ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Scientific Literature ◽  
Social Groups ◽  
Future Studies ◽  
Social Accessibility ◽  
The Relationship

Increasing accessibility and balancing its distribution across space and social groups are two fundamental goals to make transport more sustainable and equitable. In the next decades, autonomous vehicles (AVs) could significantly transform the transport system, influencing accessibility and transport equity. In particular, depending on the assumed features of AVs (e.g., private or collective) and the considered spatial, social, and regulative context (e.g., rural or urban areas), impacts may be very different. Nevertheless, research in this field is still limited, and the relationship between AV assumptions and accessibility impacts is still partially unclear. This paper aims to provide a framework of the key and emerging aspects related to the implications of AVs for accessibility and transport equity. To set this framework, we perform an analysis of the scientific literature based on a conceptual model describing the implications of AVs for the distribution of accessibility across space and social groups. We recognize four main expected impacts of AVs on accessibility: (1) accessibility polarization, (2) accessibility sprawl, (3) exacerbation of social accessibility inequities, and (4) alleviation of social accessibility inequities. These impacts are described and analyzed in relation to the main AV assumptions expected to trigger them through different mechanisms. Based on the results, some recommendations for future studies intending to focus on the relation between AVs, accessibility, and transport equity are provided.

scholarly journals Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed
Keyword(s):  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Autonomous Driving ◽  
Use Cases ◽  
Cooperative Driving ◽  
Vehicle To Vehicle ◽  
Future Challenges ◽  
Vehicle To Infrastructure ◽  
High Level ◽  
Intersection Management

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

scholarly journals Tooth loss in complying and non-complying periodontitis patients with different periodontal risk levels during supportive periodontal care

2021 ◽  
Author(s):  
Roberto Farina ◽  
Anna Simonelli ◽  
Andrea Baraldi ◽  
Mattia Pramstraller ◽  
Luigi Minenna ◽  
...  
Keyword(s):  
Active Treatment ◽  
Clinical Relevance ◽  
Tooth Loss ◽  
Loss Rate ◽  
Risk Levels ◽  
Recall Interval ◽  
Level 3 ◽  
The Difference ◽  
Periodontal Risk

Abstract Objectives To evaluate yearly tooth loss rate (TLR) in periodontitis patients with different periodontal risk levels who had complied or not complied with supportive periodontal care (SPC). Materials and methods Data from 168 periodontitis patients enrolled in a SPC program based on a 3-month suggested recall interval for at least 3.5 years were analyzed. For patients with a mean recall interval within 2–4 months (“compliers”) or > 4 months (“non-compliers”) with different PerioRisk levels (Trombelli et al. 2009), TLR (irrespective of the cause for tooth loss) was calculated. TLR values were considered in relation to meaningful TLR benchmarks from the literature for periodontitis patients either under SPC (0.15 teeth/year; positive benchmark) or irregularly complying with SPC (0.36 teeth/year; negative benchmark). Results In both compliers and non-compliers, TLR was significantly below or similar to the positive benchmark in PerioRisk level 3 (0.08 and 0.03 teeth/year, respectively) and PerioRisk level 4 (0.12 and 0.18 teeth/year, respectively). Although marked and clinically relevant in non-compliers, the difference between TLR of compliers (0.32 teeth/year) and non-compliers (0.52 teeth/year) with PerioRisk level 5 and the negative benchmark was not significant. Conclusion A SPC protocol based on a 3- to 6-month recall interval may effectively limit long-term tooth loss in periodontitis patients with PerioRisk levels 3 and 4. A fully complied 3-month SPC protocol seems ineffective when applied to PerioRisk level 5 patients. Clinical relevance PerioRisk seems to represent a valid tool to inform the SPC recall interval as well as the intensity of active treatment prior to SPC enrollment.

scholarly journals Driver seat comfort for level 3-4 autonomous vehicles

Work ◽  
2021 ◽  
Vol 68 (s1) ◽  
pp. S111-S118
Author(s):  
Neil J. Mansfield ◽  
Kartikeya Walia ◽  
Aditya Singh
Keyword(s):  
Autonomous Vehicles ◽  
Driving Simulator ◽  
Case Methods ◽  
Driving Mode ◽  
Full Control ◽  
Seat Comfort ◽  
Autonomous Mode ◽  
Different Types ◽  
Level 3 ◽  
Level 2

BACKGROUND: Autonomous vehicles can be classified on a scale of automation from 0 to 5, where level 0 corresponds to vehicles that have no automation to level 5 where the vehicle is fully autonomous and it is not possible for the human occupant to take control. At level 2, the driver needs to retain attention as they are in control of at least some systems. Level 3-4 vehicles are capable of full control but the human occupant might be required to, or desire to, intervene in some circumstances. This means that there could be extended periods of time where the driver is relaxed, but other periods of time when they need to drive. OBJECTIVE: The seat must therefore be designed to be comfortable in at least two different types of use case. METHODS: This driving simulator study compares the comfort experienced in a seat from a production hybrid vehicle whilst being used in a manual driving mode and in autonomous mode for a range of postures. RESULTS: It highlights how discomfort is worse for cases where the posture is non-optimal for the task. It also investigates the design of head and neckrests to mitigate neck discomfort, and shows that a well-designed neckrest is beneficial for drivers in autonomous mode.

scholarly journals Prototype Design and Experimental Evaluation of Autonomous Collaborative Communication System for Emerging Maritime Use Cases

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3871
Author(s):  
Jiri Pokorny ◽  
Khanh Ma ◽  
Salwa Saafi ◽  
Jakub Frolka ◽  
Jose Villa ◽  
...  
Keyword(s):  
Communication System ◽  
Autonomous Vehicles ◽  
High Speed ◽  
High Capacity ◽  
Workplace Safety ◽  
Unmanned Vehicles ◽  
Use Cases ◽  
Automated Systems ◽  
Collaborative Communication ◽  
Wide Range

Automated systems have been seamlessly integrated into several industries as part of their industrial automation processes. Employing automated systems, such as autonomous vehicles, allows industries to increase productivity, benefit from a wide range of technologies and capabilities, and improve workplace safety. So far, most of the existing systems consider utilizing one type of autonomous vehicle. In this work, we propose a collaboration of different types of unmanned vehicles in maritime offshore scenarios. Providing high capacity, extended coverage, and better quality of services, autonomous collaborative systems can enable emerging maritime use cases, such as remote monitoring and navigation assistance. Motivated by these potential benefits, we propose the deployment of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV) in an autonomous collaborative communication system. Specifically, we design high-speed, directional communication links between a terrestrial control station and the two unmanned vehicles. Using measurement and simulation results, we evaluate the performance of the designed links in different communication scenarios and we show the benefits of employing multiple autonomous vehicles in the proposed communication system.

Crisp and Fuzzy AHP in GIS-MCDA for Wildlife Habitat Suitability Analysis

2020 ◽  
pp. 1-23
Author(s):  
Suman Sinha
Keyword(s):  
Habitat Suitability ◽  
Fuzzy Ahp ◽  
Relative Difference ◽  
Suitability Analysis ◽  
Value Judgments ◽  
Analytic Hierarchy ◽  
Chi Square ◽  
Chi Square Test ◽  
The Difference ◽  
Wildlife Reserve

Geographic information system-based multi-criteria decision analysis (GIS-MCDA) is a process of decision making where geographical data and value judgments are integrated. Analytic hierarchy process (AHP) is a useful technique in MCDA for determining weights. This study focuses on the evaluation of GIS-MCDA using different uncertainty levels in AHP. Best suitable sites for tiger habitats are located and analyzed in Sariska Wildlife Reserve, India using crisp and fuzzy AHP in GIS-MCDA, and thereafter, an optimal habitat suitability model is proposed. The percentage deviation over the uncertainty levels ranges slightly over 5%. The relative difference between CAHP and FAHP is nearly 2.7%. Chi-square test reveals relationship between the degree of uncertainty and the difference between the maps. For real-world situations with increased variability, fuzzification is preferred and shows the best results. The worldwide declining status of the tigers is a serious threat to the overall biodiversity, and the methods adopted in this study thus target their conservation and management.

scholarly journals Multimodal Cue Combinations: A Possible Approach to Designing In-Vehicle Takeover Requests for Semi-autonomous Driving

2019 ◽  
Vol 63 (1) ◽  
pp. 1739-1743
Author(s):  
Gaojian Huang ◽  
Clayton Steele ◽  
Xinrui Zhang ◽  
Brandon J. Pitts
Keyword(s):  
Autonomous Vehicles ◽  
Response Times ◽  
Autonomous Driving ◽  
Multimodal Signals ◽  
Road Sign ◽  
Sign Detection ◽  
Level 3 ◽  
Perceived Workload ◽  
Tactile Cues ◽  
Vehicle Automation

The rapid growth of autonomous vehicles is expected to improve roadway safety. However, certain levels of vehicle automation will still require drivers to ‘takeover’ during abnormal situations, which may lead to breakdowns in driver-vehicle interactions. To date, there is no agreement on how to best support drivers in accomplishing a takeover task. Therefore, the goal of this study was to investigate the effectiveness of multimodal alerts as a feasible approach. In particular, we examined the effects of uni-, bi-, and trimodal combinations of visual, auditory, and tactile cues on response times to takeover alerts. Sixteen participants were asked to detect 7 multimodal signals (i.e., visual, auditory, tactile, visual-auditory, visual-tactile, auditory-tactile, and visual-auditory-tactile) while driving under two conditions: with SAE Level 3 automation only or with SAE Level 3 automation in addition to performing a road sign detection task. Performance on the signal and road sign detection tasks, pupil size, and perceived workload were measured. Findings indicate that trimodal combinations result in the shortest response time. Also, response times were longer and perceived workload was higher when participants were engaged in a secondary task. Findings may contribute to the development of theory regarding the design of takeover request alert systems within (semi) autonomous vehicles.

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