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Climate control in a pixel non-uniformity metro system includes regulating the air, humidity, and temperature quality within metro trains and stations to ensure passenger comfort and safety. The climate control system in a PNU metro system combines intelligent algorithms, energy-efficient practices, and advanced technologies to make a healthy and comfortable environment for passengers while reducing energy consumption. The proposed an automated climate control using an improved salp swarm algorithm with an optimal ensemble learning technique examines the underlying factors, including indoor air temperature, wind direction, indoor air relative humidity, light sensor 1 (wavelength), return air relative humidity, supply air temperature, wind speed, supply air relative humidity, airflow rate, and return air temperature. Moreover, this new proposed technique applies ISSA to elect an optimal set of features. Then, the climate control process takes place using an ensemble learning approach comprising long short-term memory, gated recurrent unit, and recurrent neural network. Lastly, the Harris hawks optimization algorithm can be employed to adjust the hyperparameters related to the ensemble learning models. The extensive results demonstrated the supremacy of the proposed algorithms over other approaches to the climate control process on PNU metro systems. [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia (KSA) is known for its high car ownership and usage and its high GDP per capita. This, combined with a low provision of public transportation (PT) systems, has resulted in perceptual attitudes of high dependency on private car travel. The level of awareness of the benefits of reducing car use and increasing travel by more sustainable options has a great impact on social change and behaviour. The Kingdom is currently progressing towards a new phase of "national reform" through implementation of strategic sustainable programs. Riyadh city is constructing a massive metro-system, which is nearing completion and operation. The public is aware of the national agenda, the construction of transportation projects, and of the social changes needed to realize the new vision of the country. This paper aims to assess travel behaviours and attitudes of Saudi nationals towards public transportation. A discrete choice model of the intent to use public transportation is calibrated as a function of social and attitudinal factors, using online survey data. The analysis was carried out using an ordered logit model (OLR) which is derived from the theory of random utility. The results show that, overall, a higher support for public transportation modes was stated by young females, lower income groups, and university graduates. The level of awareness of the national agenda appears to be increasing the level of support for public transportation. The paper is the first investigation of willingness to use public transportation in Riyadh, at a crucial time of national reform; the choice of mode of travel appears to be determined by the travellers' social and economic characteristics and the level of awareness of the country's agenda. [ABSTRACT FROM AUTHOR]

Car ownership and use in the Kingdom of Saudi Arabia (KSA) are very high due to the high income, the low fuel prices and the near absence of public transportation in the Kingdom. Currently, the Kingdom is going through a massive transformation and entering a new era of national reforms. One of the main aims of the national reforms is to reduce car dependency and enhance more sustainable options of travel such as public transportation in the KSA. In order to achieve such an aim, there are two hurdles: Firstly, there must be a provision of decent public transportation options, and secondly, there is a need to influence travel behaviour and encourage the shift from private cars to public transportation. For example, in Riyadh city, an impressive metro system is being constructed and will start operation in 2023. To influence travel behaviour, travel demand management measures (TDM), in particular pricing measures, can be adopted and implemented, in order to help and support achieving the target. The main aim of this paper, therefore, is to assess the attitudes of Saudi nationals towards—and willingness to accept—pricing measures and their possible impacts on their travel behaviour in the city of Riyadh. The methodology includes collecting data using an online survey on travel behaviour and attitudes in Riyadh and calibrating multinomial logit modal choice models. The participants in the survey were asked to report their support of the pricing measures for the objective of reducing congestion in the city, improving road safety or reducing travel time. The results show the highest support towards pricing measures for improving road safety, reducing travel times and, lastly, reducing congestion in the city. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have become popular in reducing the negative impact of ICE automobiles on the environment. EVs have been predicted to be an important mode of mass transit around the globe in recent years. Several charging stations in island and remote areas are dependent on off-grid power sources and renewable energy. Solar energy is used in the daytime as it is based on several environmental components. The creation of efficient power trackers is necessary for solar arrays to produce power at their peak efficiency. To deliver energy during emergencies and store it in case there is an excess, energy storage systems are required. It has long been known that reliable battery management technology is essential for maintaining precise battery charge levels and avoiding overcharging. This study suggests an ideal deep-learning-assisted solar-operated off-board smart charging station (ODL-SOOSCS) design method as a result. The development of on-board smart charging for mass transit EVs is the main goal of the ODL-SOOSCS technique that is being described. In the ODL-SOOSCS approach described here, a perovskite solar film serves as the generating module, and the energy it generates is stored in a module with a hybrid ultracapacitor and a lithium-ion battery. Broad bridge converters and solar panels are incorporated into the deep belief network (DBN) controller, which doubles as an EV charging station. An oppositional bird swarm optimization (OBSO) algorithm is used as a hyperparameter optimizer to improve the performance of the DBN model. Moreover, an MPPT device is exploited for monitoring and providing maximal output of the solar panel if the power sources are PV arrays. The proposed system combines the power of metaheuristic optimization algorithms with deep learning techniques to create an efficient and smart charging station for mass transport passenger vehicles. This integration of two powerful technologies is a novel approach toward solving the complex problem of charging electric vehicles in mass transportation systems. The experimental validation of the ODL-SOOSCS technique is tested on distinct converter topologies. A widespread experimental analysis assures the promising performance of the ODL-SOOSCS method over other current methodologies. [ABSTRACT FROM AUTHOR]

The background of this study is relevant to parking facilities at shopping malls in the Kingdom of Saudi Arabia (KSA), where all parking services are mostly free, with very few exceptions. Demand on parking places at shopping malls and recreational areas in Saudi cities are generally very high. This is partly because most of the entertaining, shopping, and recreational areas are indoors and are typically located at shopping malls with huge parking provision. With the vast increase in car ownership and use in the country over the past few decades, a consequent increase in demand on roads and parking facilities has been observed, which has no doubt resulted in further congestion. This study aims to investigate the willingness to pay to save time searching for a parking place at shopping malls in Riyadh city in the KSA. The methodology includes interviewing shoppers in shopping mall car parks and asking about their search time for a parking space and their willingness to pay to save search time, as well as to report on their socio-economic characteristics including age, gender, employment, education, car ownership, and income. The outcome of this study shows that on average, shoppers spend about 9 min searching for a parking place for their shopping and recreational trips. The results also show that, on average, shoppers reported that they go shopping, eating out, etc., about three times per week, and the average willingness to pay to save time searching for parking space is about 10 Saudi Riyal (about 2.7 USD) per visit. The modelling results show that there is a higher willingness to pay from the middle income and car-ownership categories of the population than from the highest income and car ownership groups. This might reflect the fact that the middle-income groups are much more dependent on themselves to drive their cars and search for a parking space every time, while those of higher incomes could possibly rely on their private drivers most of the times to drive them and park their cars. This paper contributes to the literature by providing a first understanding on how demand for parking facilities is affected by various socio-economic factors and the willingness to pay to save search time at these parking locations. The implications of the outcome of this research will be of use for decision makers and city authorities in planning travel demand management policies and programs that aim at reducing demand on private cars and achieving sustainability. [ABSTRACT FROM AUTHOR]

Attitudes and feelings towards food waste and positions on management policies have been vastly increased over the past few decades. Most of the available research on the analysis of attitudes towards food waste have been carried out using conventional statistical methods. This paper aims to assess and analyse attitudes and preferences of young Saudi females towards a number of policies and plans that are designed to meeting sustainable targets, using fuzzy logic analysis. This is a very important aim, especially since Vision 2030 in Saudi Arabia puts a major emphasis on sustainability, setting many resources to tackle environmental problems and achieving better social standards. The Methodology includes designing and collecting data from 199 participants using a questionnaire that includes 23 questions. Data were obtained from students at Princess Nourah bint Abdulrahman University (PNU). The analysis includes utilising artificial intelligence (AI) techniques. Fuzzy logic analysis has been widely used in many fields, but has not seen many applications on food waste analysis and attitudes. Fuzzy logic analysis has the advantage of producing efficient results from smaller sample sizes and, in particular, with qualitative characteristics of the used indicators. The participants expressed positive preferences and attitudes towards the programs and policies that are designed to achieve sustainability and manage food waste. The results show that over 25% of them prefer the option of "storage for reuse" of food waste, over 35% prefer the option of distribute it to needed families and over 30% opted to the option of recycling to fertilisers. The study also reveals a very good level of awareness and appreciation of food waste and plans associated with it. The implications from this study suggest that despite the positive attitudes, there still is more research needed to obtain full understanding of attitudes towards food waste from the whole range of the population in order to gain knowledge and build specific programs to reduce food waste and achieve sustainability in the country. [ABSTRACT FROM AUTHOR]

In this study, we investigated the current Saudi traffic safety policies and how they are perceived by Saudi women in the Kingdom of Saudi Arabia. The study was based on using a survey to define and calculate two sets of specific indicators, namely the Perceived Effectiveness Index (PEI) and the Commendation Index (CI), representing, respectively, the perception and acceptance of road traffic safety. The survey, which was conducted on a sample of Saudi women in Riyadh, demonstrated a high level of support for the ongoing road safety policies amongst the respondents, bringing to the fore some country-specific indications such as the low relevance of pedestrian crossing policies. The study aimed to contribute to an understanding of the specific gender aspects of transportation policies and their perception amongst the female population in Saudi Arabia to enable an understanding of the entire context of ongoing reforms in the Kingdom at various political, cultural, and societal levels. Our study, therefore, reveals potential strengths and provides an interdisciplinary contribution by drawing on the relevant literature in the field of travel behaviour and traffic safety policies and their perception amongst women. Saudi women's attitudes towards 17 safety policies, including engineering, enforcement, education, and legislation policies, were examined. The policies were carefully designated to be practical and possible to implement. The analysis and assessment of the results obtained by the two indicators shed light on the participants' acceptance, and hence their willingness, to cope with road safety policies, should they be implemented. The findings of this study showed that Saudi women's attitudes to road safety policies were very positive; in particular, they showed sound support for enforcement policies. [ABSTRACT FROM AUTHOR]

Perceptions, attitudes and anticipated behavior represent very useful information for decision and policy makers before they implement proposed new policies. Road safety is one of the most critical fields in the built environment. In the Kingdom of Saudi Arabia, women started driving in 2019. There is a huge shortage of studies that investigate users' attitudes and behavior, particularly women, in Saudi Arabia. It is very timely therefore, to assess their perceptions, attitudes and raise their awareness towards road safety. In this paper, the perceptions and attitudes towards road safety and relevant policies and programs were assessed and compared using two approaches: analytical and a fuzzy logic system. By means of a questionnaire, a total of 17 road safety policies, including engineering, enforcement programs, education programs and legislation programs, were presented to the participants and assessed. These policies were assessed from the viewpoint of Saudi women. The engineering policies included the use of road signs and marking, improving road network alignment, monitoring driver speed and engineering speed reduction measures. The assessment was in terms of the usefulness of the policies to reduce traffic accidents and improve road safety in Riyadh. A total of 375 participants were surveyed. Using a Likert scale response system to report the Saudi female participants' opinions, two sets of indices were calibrated to evaluate the perceived usefulness and acceptability of the safety policies. A MATLAB simulation of a fuzzy logic system was utilized to assess, investigate and compare travel attitudes and perceptions of road safety. The results indicate overall encouragement for the safety programs and policies by the participants. Most of the support seems to be for the engineering program. The physical presence of traffic police was observed to have scored the highest. This is an interesting result that shows that enforcement policies are still perceived to be the most effective. In this category, the policy of enforcing speed limits showed high support, amongst the other policies. While a fuzzy logic analysis is typically used in hard engineering assessments and investigations, such as mechanical engineering and system design applications, the results obtained in this investigation show that the efficacy and adequacy of the proposed fuzzy logic control system in assessing attitudinal data was sufficiently good to be recommended for future research. The outcomes from both sets of approaches, the analytical and the fuzzy logic, showed comparable results, which also demonstrates the potential benefits of using the fuzzy system in many attitudinal and behavioral studies. [ABSTRACT FROM AUTHOR]

Investigations of attitudes towards food waste and preferences of policies that affect sustainability has increased rapidly over the past few decades. Most research on food waste, however, has been undertaken mainly in the developed countries with very few in the developing countries. It is very important therefore to investigate food waste and attitudes towards sustainability in developing countries, especially since a huge amount of carbon emissions and other pollutants occur in the developing countries. Saudi Arabia is a rich developing country that sets its 2030 visions to tackle issues related to sustainability. Many strong policies and programs are set in place to fulfil these visions. Such attitudes towards food waste diverges between cultures as a result of differences in background, income, family structure, age, etc. The contribution of this study is that it intends to investigate attitudes and preferences on policies and programs that aim at achieving sustainability and reducing food waste for young university females in Saudi Arabia. The methodology that is adopted in this study is to design a questionnaire, arranged in 5 sections and 23 questions, to collect data from 199 students at Princess Norah Bint Abdulrahman University. The aim of the questionnaire was to evaluate attitudes and preferences of female students towards food waste in Saudi Arabia, and in particular in the city of Riyadh. A number of policies were selected for the investigation, including three categories of policies: hospitality policies, education and raising awareness, and legislation policies. The participants expressed their opinions towards policies and programs that aim at improving sustainability and reducing food waste. Each policy was assessed in terms of its level of importance and its effectiveness in achieving sustainability. Two indices were calculated to compare and assess the perception of the suggested policies: the Perceived Effectiveness Index (PEI) and the Endorsement Index (EI). The results show that while some policies are perceived as both effective and supported for implementation, some policies are perceived as most effective; however, participants were not very supportive of their implementation. Hospitality policies, such as encouraging food waste recycling and providing the option to take away leftover food, were ranked highest in terms of effectiveness to achieve the target. These findings seem to echo the Saudi society's attitudes of sustainable behaviour and positive attitudes towards food waste recycling. It should also be noted here that while the Saudi society is still a growing and developing society, it does care significantly about food waste and sustainability. The results are encouraging, and further investigations are urgently needed to better understand determinants of food waste at a household level in developing countries. [ABSTRACT FROM AUTHOR]

Within the objectives of the H2020 DIAMOND project, the paper investigates women's needs and expectations as users of the bike-sharing service managed by Syndicat Mixte Autolib et Velib Métropole in the territory of Paris Region-Petite Couronne (France). The paper presents a thematic literature review focused on gender inclusion in bike-sharing schemes. The proposed methodological approach is based on (i) Geographic Information Systems for the analysis of geolocated open datasets related to land, sociodemographic and mobility characteristics of the areas surrounding each docking stations. This was aimed at identifying a short list of suitable bike-sharing docking stations, which were further characterized through: (ii) structured proprietary data focused on travel demand; (iii) onsite observations focused on universal design indicators; (iv) survey questionnaires focused on women's concerns, needs and expectations; and (v) social media data from Twitter focused on the opinion of the end-users. Results showed that women use the VELIB's bike-sharing service much less than men (about 30% of the total number of users), since they are more concerned about the following issues: accessibility (e.g., availability of bikes at the docking stations, distance to the nearest station, type and quality of the cycle paths); safety and security (e.g., perception of danger and insecurity while cycling and using the current bicycle infrastructures); social constraints (e.g., perceptions and cultural stigmatization associated with cycling and bike-sharing); weather and topography (e.g., impact of weather and the urban terrain on cycling and bike-sharing). The final aim of the H2020 DIAMOND project is to support the definition of guidelines and policies for the inclusion of women's needs in the design of future bike-sharing services. [ABSTRACT FROM AUTHOR]

The study investigates the behaviour of pedestrians crossing a road with a refuge island in an urban area to assess whether refuge islands deliver their expected benefit. This type of pedestrian crossings aims at providing a half-way shelter and protection while pedestrians are crossing a road with two-traffic streams. Data has been collected using two video cameras from an urban location in Edinburgh on gaps in traffic flow, rejected and accepted gaps, and critical gaps of pedestrians while crossing from the curb or the median. Data have also been examined to estimate and assess vehicle and pedestrians' speeds, vehicle type, waiting time, group size and other demographic characteristics of pedestrians. The statistical modelling techniques used include Multiple Linear Regression and Generalised Estimating Equations (GEE). The results show that the critical gap for crossing from the median to the curb is much shorter than that from the curb to the median. Pedestrians appear to be less cautious when crossing from the median to the curb as they are more likely to accept a shorter gap in traffic. This could indicate a shortfall in the design and/or operation of this type of crossing. Further considerations and investigation of what measures could be implemented to enhance safety and reduce risky behaviour at this type of crossing are recommended and certainly encouraged. [ABSTRACT FROM AUTHOR]

At non-signalized marked crosswalks, pedestrian priority is neither well-defined nor well acknowledged by drivers. This paper presents the findings of an investigation on both driver and pedestrian behavior at non-signalized marked crosswalks located on channelized right-turn lanes at intersections in the State of Qatar. Five crosswalks in Doha city were video recorded from discrete locations on a typical working day. The results from the data analysis of 1620 pedestrians' behavior indicated that waiting behavior, gap acceptance, and crossing speed are complex phenomena and depend upon both pedestrians' characteristics as well as their crossing characteristics. The drivers' yielding behavior was mainly linked to pedestrians' gender and adjacent land use. Low driver yielding rates indicated that significant improvements are required to enhance pedestrian safety. Among pedestrian attributes, gender had the most significant effect on crossing behavior followed by distractions, crossing in a group or alone, and dressing style. Findings of this research will be useful for planners when designing crosswalks at new intersections and during simulations of pedestrian and driver behavior at marked crosswalks on exclusive right-turn lanes. The results of this study will also be directly applicable to the Arabian Gulf countries as they exhibit similar conditions as the State of Qatar. [ABSTRACT FROM AUTHOR]