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As intelligent driving vehicles came out of concept into people’s life, the combination of safe driving and artificial intelligence becomes the new direction of future transportation development. Autonomous driving technology is developing based on control algorithms and model recognitions. In this paper, a cloud-based interconnected multi-sensor fusion autonomous vehicle system is proposed that uses deep learning (YOLOv4) and improved ORB algorithms to identify pedestrians, vehicles, and various traffic signs. A cloud-based interactive system is built to enable vehicle owners to master the situation of their vehicles at any time. In order to meet multiple application of automatic driving vehicles, the environment perception technology of multi-sensor fusion processing has broadened the uses of automatic driving vehicles by being equipped with automatic speech recognition (ASR), vehicle following mode and road patrol mode. These functions enable automatic driving to be used in applications such as agricultural irrigation, road firefighting and contactless delivery under new coronavirus outbreaks. Finally, using the embedded system equipment, an intelligent car was built for experimental verification, and the overall recognition accuracy of the system was over 96%. Author
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Transportation problems have always been a global concern. The challenges in traffic congestion were easily observed during pre-pandemic times. However, traffic congestion still persists even during the COVID-19 pandemic (2020 and present) where there has been less number of vehicles because of travel restrictions. The emergence of wireless communication technologies and intelligent transportation systems (ITS) pave the way for solving some of the problems found in the transportation industry. Subsequently, traffic control systems are used at various intersections to manage the flow of traffic and reduce car collisions. However, some intersections are better off without these traffic control systems. The proposed study will analyze a T-junction road in five different setups using different types of traffic controllers. The simulation tool used is SUMO. The study found that an adaptive or vehicle-actuated traffic controller is the ideal method for regulating traffic flow in a T-junction with a one-way or two-way main road. It was observed in the simulation that it reduced the potential car collisions in the non-TL junction. However, the average speed and completion time of the road network was affected by the method. © 2022 IEEE.
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The global outbreak of coronavirus disease 2019 (COVID-19) has affected the urban mobility of nations around the world. The pandemic may even have a potentially lasting impact on travel behaviors during the post-pandemic stage. China has basically stopped the spread of COVID-19 and reopened the economy, providing an unprecedented environment for investigating post-pandemic travel behaviors. This study conducts multiple investigations to show the changes in travel behaviors in the post-pandemic stage, on the basis of empirical travel data in a variety of cities in China. Specifically, this study demonstrates the changes in road network travel speed in 57 case cities and the changes in subway ridership in 26 case cities. Comprehensive comparisons can indicate the potential modal share in the post-pandemic stage. Further, this study conducts a case analysis of Beijing, where the city has experienced two waves of COVID-19. The variations in travel speed in the road network of Beijing at different stages of the pandemic help reveal the public's responses towards the varying severity of the pandemic. Finally, a case study of the Yuhang district in Hangzhou is conducted to demonstrate the changes in traffic volume and vehicle travel distance amid the post-pandemic stage based on license plate recognition data. Results indicate a decline in subway trips in the post-pandemic stage among case cities. The vehicular traffic in cities with subways has recovered in peak hours on weekdays and has been even more congested than the pre-pandemic levels;whereas the vehicular traffic in cities without subways has not rebounded to pre-pandemic levels. This situation implies a potential modal shift from public transportation to private vehicular travel modes. Results also indicate that commuting traffic is sensitive to the severity of the pandemic. This may be because countermeasures, e.g., work-from-home and suspension of non-essential businesses, will be implemented if the pandemic restarts. The travel speed in non-peak hours and on non-workdays is higher than pre-pandemic levels, indicating that non-essential travel demand may be reduced and the public's vigilance towards the pandemic may continue to the post-pandemic stage. These findings can help improve policymaking strategies in the post-pandemic new normal. © 2023 American Society of Civil Engineers.
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As part of Mumbai Coastal Road Project-the connection between Nariman Point and Bandra Worli, a total length of 10.58 km-Package IV (MCRP4) includes submarine twin tube tunnels. Current Package's total length is 4,480 m, of which 2,008 m are excavated by means of one slurry shield and supported/lined by precast segments. Each tube will accommodate a three-lane carriageway, for an internal diameter of 11 m and an excavation diameter 12.19 m. To enable the launching and receiving of the TBM, two shafts were constructed at North end and South end of the package. The reception shaft is 42m long and 30m wide with a depth of 26m below the ground formation level at +3.0 msl. The intention was to disassemble the TBM after the first drive to reassemble and relaunch it from the original shaft – the "launch-ing shaft”. However, due to logistical constraints, given the project location in a dense urban setting, and due to time delays, because of stoppage of works during Covid lockdown, the Contractor of the project decided to relaunch the TBM from the reception shaft itself by rotating the TBM and save approx. 60-75 days. Due to this dynamic need of the project, reception shaft was repurposed for relaunching with additional ancillary structures (like Heavy weight modular gantry crane foundations, TBM reaction frame, Slurry treatment plant on surface etc.,) in and around the shaft which weren't foreseen during the excavation of shaft. This paper discusses design aspects with special focus on challenges which were needed for this repurposing of shaft. © 2023 The Author(s).
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During the COVID-19 pandemic, authorities in many places have implemented various countermeasures, including setting up a cordon sanitaire to restrict population movement. This paper proposes a bi-level programming model to deploy a limited number of parallel checkpoints at each entry link around the cordon sanitaire to achieve a minimum total waiting time for all travelers. At the lower level, it is a transportation network equilibrium with queuing for a fixed travel demand and given road network. The feedback process between trip distribution and trip assignment results in the predicted waiting time and traffic flow for each entry link. For the lower-level model, the method of successive averages is used to achieve a network equilibrium with queuing for any given allocation decision from the upper level, and the reduced gradient algorithm is used for traffic assignment with queuing. At the upper level, it is a queuing network optimization model. The objective is the minimization of the system's total waiting time, which can be derived from the predicted traffic flow and queuing delay time at each entry link from the lower-level model. Since it is a nonlinear integer programming problem that is hard to solve, a genetic algorithm with elite strategy is designed. An experimental study using the Nguyen-Dupuis road network shows that the proposed methods effectively find a good heuristic optimal solution. Together with the findings from two additional sensitivity tests, the proposed methods are beneficial for policymakers to determine the optimal deployment of cordon sanitaire given limited resources. © National Academy of Sciences: Transportation Research Board 2021.
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The Canadian Perspectives on Environmental Noise Survey was completed online by 6647 randomly selected Canadians 18 years of age and older between April 12 and May 25, 2021. The survey objective was to explore attitudes, perceptions, and expectations toward environmental noise in rural and non-rural Canada. The questionnaire assessed self-reported high sleep disturbance (HSD) in the previous year, at home. The prevalence of HSD was 7.8% overall. A list of potential sources of sleep disturbance was provided to the full sample, where 6.1%, 5.2%, and 3.0% reported HSD by noisy neighbors, road traffic noise and indoor noise, respectively. Stress/anxiety or worrying about something was selected most frequently at 12.9%. Finally, 7.6% and 5.5% reported pain/illness and partner's sleep disturbance, respectively, as sources of HSD. Reported HSD was significantly higher among respondents below 55 years of age, females, lower income groups, unemployed respondents, those on paid leave (sick, maternity, disability), and living in an urban area. Expectations of quiet, perceiving nighttime noise to have increased over time, high noise sensitivity, hearing and being highly annoyed by road traffic noise was also associated with an increased prevalence of reporting HSD. In contrast to hearing impairment and heart disease (including high blood pressure);rated physical health, mental health, anxiety/depression, and reporting a sleep disorder, were associated with increased HSD. The perceived affects of the COVID-19 pandemic on health and annoyance toward environmental and indoor noise also influenced HSD. In the fully adjusted multivariate logistic regression model, the effect of age, gender, changes in nighttime noise, road traffic noise annoyance, noise sensitivity and sleep disorder remained statistically significant. The univariate and multivariate models showed a similar prevalence of HSD between Indigenous Peoples and non-Indigenous Canadians. Results are discussed in relation to the provision of advice on sleep and health under Canada's Impact Assessment Act. © 2023
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This article explores the lived daily experiences of street vendors operating along the Main North 1 Road in the CBD of Maseru, Lesotho. This exploration considers how street vendors access and negotiate a claim for the right to the street. The challenges confronting these vendors in their daily hustling, including COVID-19 restrictions, are also examined. A narrative inquiry research design informs this article with data collected from interviews with purposively selected street vendors from Maseru. This primary data was triangulated with document analysis to increase the validity of the findings. The findings highlight strategies employed by vendors in Maseru that include integrating with the formal enterprises, diversifying their trades, resisting and frustrating certain decisions by the local authorities, and contributing to urban blight. A framework for interrogating and understanding street vending and its nuances is postulated based on the findings from Maseru. The article strongly appeals to the authorities to find more benign ways of integrating street vending into the production of cities. © 2023, The Author(s).
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This study aimed to map the accessibility of the existing isolation facilities in Cabagan, Isabela, and propose probable locations suitable for establishing isolation facilities using the Geographic Information System (GIS). Digital datasets of the current isolation facilities were used in the study, along with factors such as land uses, hazards, landfills, and road networks that should be taken into consideration when choosing potential locations for isolation facilities. These factors follow the guidelines set by the Department of Health (DOH). The processing and generation of layers related to the criteria were done using GIS techniques, specifically overlay analysis tools. In order to project an appropriate map of potential isolation facilities in Cabagan, Isabela, the layers were combined and overlaid. The existing isolation facilities are accessible to Milagros Albano District Hospital (MADH) since all of them are adjacent to national or barangay roads. More than half, or 65.38%, of the isolation facilities, belong to areas with low to moderate susceptibility to flooding, and 26.92% are in areas with high susceptibility to flooding. Furthermore, all isolation facilities are open to the public, with 53.85% of existing isolation facilities in residential areas, 7.69% in commercial areas, and 38.46% in agricultural areas. The suitability map of proposed isolation facilities was successfully generated, showing that 100% of the proposed isolation facilities are accessible from any road network in the municipality with low and moderate susceptibility to flooding and low susceptibility to landslides. © 2022 IEEE.
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The Philippines, as a fast-growing country, has had the highest road infrastructure investment to date for the past five years compared to the previous years. The infrastructure programs of the government as a solution to decongest Metro Manila and develop the countryside for economic growth are promising yet result in various risks and challenges. This research presents the road development issues from multiple sources;primary data from interviews of stakeholders of road development, secondary data from online news articles, social network services, government issuance, policies, and related literature. The Philippines is in a dire economic situation due to the Covid-19 outbreak that resulted in the country's worst economic performance since the Asian financial crisis in 1998. The country's economic managers pinned high hopes on the government infrastructure programs as a vital strategy to help pump-prime the economy towards recovery due to its job generation and multiplier effects. Hence, it implicates enormous risks and challenges such as low tax revenues, the trade-off with more urgent Covid-19 response measures, foreign and private companies support, unsolicited project proposals, inequitable distribution of infrastructures, and delays in construction activities. Various road development stakeholders also mentioned the need for strict road regulations, urban and regional planning, aesthetic improvement, urban renewal in aid of car-centric infrastructures, and routine maintenance on-road sections. The data are structured in various categories such as public involvement, environmental preservation, public policy, project planning, road design, road safety, economic recovery, and construction time. Lastly, the implications for future research directions are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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This study experimentally measured the ventilation efficiency in road vehicles. Two air circulation methods, air conditioning and opening windows, were considered and their ventilation efficiencies were measured for a sedan and a cutaway bus. The ventilation efficiencies have been evaluated by measuring the aerosol concentration parameter at different locations inside the vehicle. For both vehicles, any of the ventilation scenarios significantly increased the air exchange rate. The best performance was shown when all windows were open in a moving vehicle. As an illustration of using the obtained measurements, respiratory infection probability was calculated using the Wells-Riley model. Any of the ventilation cases significantly decreased the infection risk. The ventilation efficiency and infection probability were highly dependent on the air circulation method and vehicle type. © 2023 The Author(s)
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The Philippines, as a fast-growing country, has had the highest road infrastructure investment to date for the past five years compared to the previous years. The infrastructure programs of the government as a solution to decongest Metro Manila and develop the countryside for economic growth are promising yet result in various risks and challenges. This research presents the road development issues from multiple sources;primary data from interviews of stakeholders of road development, secondary data from online news articles, social network services, government issuance, policies, and related literature. The Philippines is in a dire economic situation due to the Covid-19 outbreak that resulted in the country's worst economic performance since the Asian financial crisis in 1998. The country's economic managers pinned high hopes on the government infrastructure programs as a vital strategy to help pump-prime the economy towards recovery due to its job generation and multiplier effects. Hence, it implicates enormous risks and challenges such as low tax revenues, the trade-off with more urgent Covid-19 response measures, foreign and private companies support, unsolicited project proposals, inequitable distribution of infrastructures, and delays in construction activities. Various road development stakeholders also mentioned the need for strict road regulations, urban and regional planning, aesthetic improvement, urban renewal in aid of car-centric infrastructures, and routine maintenance on-road sections. The data are structured in various categories such as public involvement, environmental preservation, public policy, project planning, road design, road safety, economic recovery, and construction time. Lastly, the implications for future research directions are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The rapid development in traffic density and the economic transformation since 1989 has brought new problems concerning road traffic noise in Slovakia. The aim is to follow the time trends of noise annoyance in monitored localities in Bratislava at time intervals of 10, 20, and 30 years. We used the validated methodology for subjective assessment of noise annoyance in young and healthy individuals, as well as a method of objectification by direct measurement of sound levels. Respondents (n=3,675) were university students, living in the exposed and control dormitories representing a homogenous sample. The sharp increase in traffic noise burden in the exposed area was found at the first 10-year interval (1989-1999) (LAeq=67.5 dB). A slight decrease occurred in 2019 up to LAeq=63.9 dB and during lockdown due to COVID-19 pandemic it dropped to LAeq =62.5 dB. A sharp increase in road traffic noise annoyance was observed in the first 10-year interval (ORMH=2.56 (95 % CI=1.93-3.42) vs 6.01 (95% CI=4.97-7.95) with a slightly decreasing trend in 2020-2021. An increase in noise annoyance from entertainment facilities was observed as well. Despite a slightly declining trend, road traffic noise annoyance is still an important issue and there is a need for preventive measures to reduce such exposure in residential areas. © 2022 Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. All rights reserved.
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The new "Internet+” teaching mode during the COVID-19 pandemic has guaranteed the smooth learning progress of university students in China. High-efficiency reconstruction of time and space for knowledge teaching and internalization based on informationalized teaching mean is an important approach to online learning. A flipped classroom is a teaching mode that is formed through bottom-up exploration. Combined with teaching practical situations, the flipped classroom realizes the transformation from the teacher-centered mode to the student-oriented mode successfully and has important value to the teaching of professional core courses, which are difficult to be learned. In this study, 80 freshmen majoring in Road and Bridge Engineering Technology at Yellow River Conservancy Technical Institute in Henan Province of China were selected as research objects, and Road Survey Design and Lofting was chosen as the teaching course. Under these circumstances, a teaching experiment comparison was designed. The experimental group used flipped classroom technology based on Attention, Relevance, Confidence, and Satisfaction (ARCS) motivation model theory, while the control group used the traditional teaching mode. Research results demonstrate that before the experiment, the learning outcomes of two groups in Road Survey Design and Lofting were basically consistent (P=0.908>0.05) without obvious differences. After finishing the experiment, the post-test results of the control group have not improved significantly compared with the pre-test results (P=0.0938>0.05). However, the post-test results of the experimental group have improved significantly compared with the pretest results (P < 0.001). The average scores of the experimental group are far higher than that of the control group, thus indicating the evident progress of the experimental group. Noticeable differences in the post-test results between the experimental group and the control group are observed (P < 0.001). The research results are of great significance to enriching the teaching mode of core application courses for engineering majors in university, as they provide evidence that the flipped classroom increases the learning interests and motivation of students and demonstrate the teaching effect of flipped classroom technology in universities © 2023, International Journal of Emerging Technologies in Learning.All Rights Reserved.
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The COVID-19 pandemic has led to an urgent need in emerging economies to quickly identify vulnerable populations that do not live within access of a health facility for testing and vaccination. This access information is critical to prioritize investments in mobile and temporary clinics. To meet this need, the World Bank team sought to develop an open-source methodology that could be quickly and easily implemented by government health departments, regardless of technical and data collection capacity. The team explored use of readily available open-source and licensable data, as well as non-intensive computational methodologies. By bringing together population data from Facebook's Data for Good program, travel-time calculations from Mapbox, road network and point-of-interest data from the OpenStreetMap (OSM), and the World Bank's open-source GOSTNets network routing tools, we created a computational framework that supports efficient and granular analysis of road-based access to health facilities in two pilot locations—Indonesia and the Philippines. Our findings align with observed health trends in these countries and support identification of high-density areas that lack sufficient road access to health facilities. Our framework is easy to replicate, allowing health officials and infrastructure planners to incorporate access analysis in pandemic response and future health access planning. © National Academy of Sciences: Transportation Research Board 2022.
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An inversion system that uses a Bayesian approach to combine measurements and ADMS-Urban modelled data by adjusting individual source emissions, subject to estimated uncertainty in the measurements and emissions, has previously been applied to optimising road traffic emissions in Cambridge. In this study the system has been applied specifically to the impact of interventions, in particular the impact of COVID-19 lockdowns on NOX emissions from road traffic and other sources in London. The ADMS-Urban model was used to calculate a priori hourly NOX concentrations at 195 receptors in London representing 115 reference monitors and 80 Breathe London Network AQMesh sensors. Input data included hourly meteorological measurements from Heathrow Airport, hourly NOX concentrations from 4 rural background monitoring sites and buildings road centreline data from Ordnance Survey. A priori emissions were obtained from the London Atmospheric Emissions Inventory (LAEI) for 35 point sources, approximately 70,000 major road sources and 2,500 1km grid cells representing minor road, heating and other sources. The analysis period was 1 January 2020 to 30 April 2021. Estimated uncertainties of 4 and 12 µg/m3 were applied to reference and sensor measurements respectively, while emissions uncertainties of 100%, 50%, 20% were applied to road traffic, fuels and other emissions respectively. Road traffic emissions were assumed to have error covariance of 40% of their emissions uncertainty. Measured NOX concentrations in London reduced significantly during lockdown, with the greatest reduction (around 60%) at kerbside and roadside sites in Central London. However, poor dispersal conditions led to increased concentrations at times when restrictions were tightest. In contrast, inversion system results demonstrate that NOX emissions from road traffic dropped by around 60% in London compared with pre-lockdown levels and that this reduction occurred when the strictest lockdown measures were in force. The results also show that NOX road traffic emissions were still approximately 30% lower than pre-lockdown levels at the end of April 2021. This analysis demonstrates that lower cost sensors such as AQMesh can provide valuable insight into the effects of policy measures (in this case lockdown restrictions), if their increased uncertainty compared with reference monitors is accounted for. © British Crown Copyright (2022)
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The road transport sector has a direct effect on fossil energy sources, cost, and consumption. Indeed, it has affected the environmental situation reversely with high carbon dioxide emissions. Due to this negative impact, the transition to electric vehicle (EV) technology must be a mandatory target for governments worldwide. To achieve this objective, many countries have developed various policies to promote EV technology buying or retrofitting. Thanks to the adopted policies, the electric technology market share has been growing. Meanwhile, research studies are involved also in this project by studying the benefit of EV technology low total cost of ownership (TCO) to motivate consumers of its utilization. For that purpose, the present paper aims to review the discussed policies, and methods to boost the diffusion of electric technology as a sustainable and reliable solution to overcome the global energy situation despite the different obstacles, barriers, and the pandemic situation (COVID-19), which has affected the consumer economic and social behavior. © 2022 IEEE.
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Traditionally, mobility problems and automobile traffic congestion have increased in cities around the world due to the urban development process, especially in the city of Metropolitan Lima. For this reason, the government of the Peruvian capital has established temporary detours in certain sections of the arterial roads of the network, to invite new cyclists, due to the effects of Covid-19. Today, Lima has a network of 294 km of bicycle lanes, which have been implemented without adequate planning. In view of this, we evaluated the risk of poor planning on the vulnerable user (the cyclist) at an intersection of this road network, with a high rate of motorized congestion. The main objective of this study has been to propose corrective actions to avoid the exposure to danger on the users of the bicycle lane (countermeasures);due to lack of safety at the intersection of La Marina Ave. and Universitaria Ave. In this sense, a risk matrix was developed with the most concurrent factors that occur at this intersection;to then obtain a risk level and take actions in each of them, to mitigate the impact. The result obtained in the analysis of this study for the intersection is classified as a level 2 risk: Important risk, which means that it presents several important danger factors. Finally, in addition to the analyses developed, a treatment scheme was proposed for the intersection to provide greater safety to the users of the bicycle lane, avoiding fatal and non-fatal accidents. © 2022 IEEE.
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Due to COVID-19, ordering food through online shopping increased. Accordingly, the use of logistics and delivery services is also increasing. As the number of parcels to be delivered gets bigger, the efficiency of the delivery mechanism and battery efficiency becomes important. The problem of finding the route traveling several destinations at once is called as Traveling Salesman Problem (TSP). There are several algorithms suggested to solve it in polynomial time. Among them, this paper experimented to compare the performance of two algorithms, the greedy algorithm, and the branch-and-bound algorithm. We used the Simulation of Urban Mobility (SUMO) program to test the vehicle running based on the calculated route by two algorithms. The average running time and charging time are recorded to evaluate the performance. Through this experiment, we found out that the branch-and-bound algorithm provides in a faster route selection and consumes less battery than the greedy algorithm. © 2022 IEEE.
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China's port investments in countries along the Belt and Road are growing, while the global investment environment has deteriorated due to the Sino-US trade friction and the COVID-19 epidemic. However, the recent quantitative research on overseas port investment risk has not considered the time weight, and the related research is less. Therefore, this paper proposes a dynamic evaluation method specially for port investment risk of countries along the B&R based on entropy weight-TOPSIS and BP neural network. First, we figure out the static comprehensive risk value by entropy weight-TOPSIS method, and get the dynamic comprehensive risk value by time weighting method. Second, select three-dimensional data of 32 indicators in 18 host countries from 2010 to 2019 for empirical analysis, and obtain the risk level of each country. Lastly, compared with multiple regression, ridge regression, partial least square, we find BP neural network is the most effective means to estimate the simulation weight of evaluation indicators. The experimental result shows that, the proposed dynamic risk assessment approach for overseas port investment is able to assess risk well and can be extended to other fields. © 2022 IEEE.
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Traffic operation has shown abnormal characteristics during COVID-19. This paper obtains traffic data from multiple fields in Beijing for the whole year of 2020, combines traffic operation data with the number of confirmed cases, and deeply explores the operating characteristics of road networks, public transportation, and intercity transportation at various stages during the major epidemic. The results showed that travel demand decreased significantly during the epidemic period. From the perspective of urban road network traffic pressure, the demand for rigid travel in peak hours during the epidemic recovery period is relatively large. Based on this research, it can provide decision support for the government to formulate relevant prevention and control measures and policies, thereby improving the ability of urban traffic to respond to public health emergencies. © ASCE.