Main Road Research Articles

Comprehending particulate matter dynamics in transit-oriented developments: Traffic as a generator and design as a captivator

In Transit-Oriented Development (TOD), the close integration of residential structures with community activities and traffic heightens residents' exposure to traffic-related pollutants. Despite traffic being a primary source of particulate matter (PM), the compact design of TODs, together with the impact of urban heat island (UHI), increases the likelihood of trapping emitted PM from traffic, leading to heightened exposure of TOD residents to PM. Although PM originates from two distinct sources in road traffic, exhaust and non-exhaust emissions (NEE), current legislation addressing traffic-related PM from non-exhaust emissions sources remains limited. This paper focuses on two TOD typologies in Manchester City—Manchester Piccadilly and East Didsbury—to understand the roles of TOD traffic as a PM generator and TOD place design as a PM container and trapper. The investigation aims to establish correlations between street design canyon ratios, vehicular Speed, and PM10/PM2.5, providing design guidance and effective traffic management strategies to control PM emissions within TODs. Through mapping the canyon ratio and utilising the Breezometer API for PM monitoring, the paper revealed elevated PM levels in both TOD areas, exceeding World Health Organization (WHO) recommendations, particularly for PM2.5. Correlation analysis between canyon configuration and PM2.5/PM10 highlighted the importance of considering building heights and avoiding the creation of deep canyons in TOD design to minimise the limited dispersion of PM. Leveraging UK road statistics and the PTV Group API for vehicle speed calculations, the paper studied the average speeds on the TOD roads concerning PM. Contrary to conventional assumption, the correlation analyses have revealed a noteworthy association shift between vehicular speed and PM concentrations. A positive correlation existed between speed increase and PM increases on arterial roads. However, a negative correlation emerged on main, collector, and local streets, indicating that PM levels rise for both PM10 and PM2.5 as Speed decreases. These findings challenge the traditional assumption that higher Speed leads to increased emissions, highlighting the potential impact of NEE on PM concentrations. This paper calls for thorough design considerations and traffic management strategies in TOD, especially in dense areas, considering building height, optimising traffic flow, and enhancing compromised air quality associated with vehicular emissions.

Tech-Enabled Financial Data Access, Retail Investors, and Gambling-Like Behavior in the Stock Market

Advancements in technology have reduced information acquisition costs, creating an improved information environment for retail investors. Specifically, new technologies, such as application programming interface (API), deliver high-volume, institutional-like raw data directly to Main Street investors. Although greater availability of information can be beneficial, it may also exacerbate retail investors’ existing trading deficiencies. Exploiting the sudden shutdown of Yahoo! Finance API, the largest free API for retail investors, this study examines how access to tech-enabled raw financial data affects retail investment. We find that retail trading volumes in stocks favored by active retail investors dropped by 8.6%–10.5% within one month of the API shutdown. The remaining retail trades collectively became more predictive of future returns, suggesting less gambling-like behavior after the API shutdown. Moreover, our randomized controlled experiment affirms the underlying mechanism: tech-enabled access to high-volume historical price data increases individuals’ overconfidence, which further leads them to engage in excessive trading. The study reveals an unintended consequence of technology-led, wider data access for retail investors. This paper was accepted by D. J. Wu, information systems. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01379 .

Money Supply, Reaction Functions, Financial Markets and Macroeconomic Conditions

Money Supply, Reaction Functions, Financial Markets and Macroeconomic Conditions

Predicting vehicle travel time on city streets for trip preplanning and predicting heavy traffic for proactive control of street congestion

We investigate if the vehicle travel time after 6 h on a given street can be predicted, provided the hourly vehicle travel time on the street in the last 19 h. Likewise, we examine if the traffic status (i.e., low, mild, or high) after 6 h on a given street can be predicted, provided the hourly traffic status of the street in the last 19 h. To pursue our objectives, we exploited historical hourly traffic data from Google Maps for a main street in the capital city of Jordan, Amman. We employ several machine learning algorithms to construct our predictive models: neural networks, gradient boosting, support vector machines, AdaBoost, and nearest neighbors. Our experimental results confirm our investigations positively, such that our models have an accuracy of around 98–99% in predicting vehicle travel time and traffic status on our study’s street for the target hour (i.e., after 6 h from a specific point in time). Moreover, given our time series traffic data and our constructed predictive models, we inspect the most critical indicators of street traffic status and vehicle travel time after 6 h on our study’s street. However, as we elaborate in the article, our predictive models do not agree on the degree of importance of our data features.

Sistema de gestión y operación de la red semafórica de la ciudad de Lima

The research problem arose from the need to implement a system to remotely manage the traffic operations of the network of traffic lights to reduce vehicular congestion. The procedure involved designing the placement of electronic sensors to track the number of vehicles in the area. This allowed for the testing of different operational strategies for modifying the timing of the traffic light signals. A simulation model was used to test these strategies in seven intersections on Av. Petit Thouars in Lima, between Av. Alejandro Tirado and Av. 28 de Julio. Detectors were installed at the access points of secondary access streets to the main road (Av. Petit Thouars) which yielded cumulative positive results. Alternatives 1 and 2 produced a 59% reduction in queues, thus demonstrating the validity of the general hypothesis.

Transformative resilience of Wuhan’s city-center main streets in the post-COVID era

Transformative resilience of Wuhan’s city-center main streets in the post-COVID era

Patterns of retail gentrification on inner-city main streets in Stockholm: the role of privatized property ownership

ABSTRACT This study aims to investigate the connection between property owners and shopfront retail changes on main streets, exploring the role of private property ownership in retail gentrification. Examining four inner-city streets in Stockholm between 2009 and 2018, a commercial gentrification index reveals patterns of retail gentrification. Privatization in Stockholm (1990–2010) resulted in cooperative housing associations (CHAs) becoming the dominant property owners. Retail gentrification is slightly more pronounced among CHA-owned properties. Interviews with 122 small-business owners renting from CHAs indicate that their short-term economic interests limit efforts to counteract retail gentrification, favouring its exacerbation over preserving independent retailers on main streets.

Bushranger Re-Enactments: Legend And Landscape

The re-enactment of events from Australia’s history as popular entertainment has dropped away in the twenty-first century. Whilst Old Sydney Town attracted crowds from 1973 through to 2003 with its daily parades of British red coats who marched down to an artificially constructed ‘Old Sydney Cove’, Australians today often have a more conflicted view of Australia’s colonial history. If national identity is maintained through acts of ‘remembering’, as suggested by Ian McBride (2001), the past can be a contested issue that impacts on what is accepted as popular representation. Yet the persistence of bushranger escapade re-enactments, though set in colonial times, suggests that issues beyond Australian national identity are at work in maintaining the popularity of such events. Bushrangers in Australia have fuelled imaginative representations in theatre and then later cinema since the early 1800s, with Andrew James Couzens (2019) stating that the Australian “bushranger legend … responds to the historic and mythic characteristics of outlawry” with “the outlaw as heroes”. This paper investigates three specific bushranger re-enactments. In Braidwood, south-eastern New South Wales, from 1865-1867 the Clark Gang, Tom and John Clark terrorized citizens and were known as ‘the bloodiest of bushrangers’. In 2017, the 150-year anniversary re-enactment of the Clark Gangs’ shooting up of the small country town of Braidwood attracted crowds keen to witness, as well as take part in the drama. The second re-enactment occurs regularly through performances by the Gympie Historical Re-enactment Society. Opting to entertain tourists, the group have staged a ‘Bushranger Show’ at numerous sites throughout inland regional Queensland. The third re-enactment occurred annually, until Covid struck, at Canowindra in northern New South Wales. In 1863 the notorious bushrangers, Ben Hall and Johnny Gilbert locked a group of villagers in the Canowindra pub, the re-enactment takes place at the site of these events, the now named Royal Hotel in the main street of Canowindra. These re-enactments are investigated through multiple lenses of performance, place, and politics. The site-specific nature of these performances positions them as specifically different than performances depicting Australian bushrangers in the cinema or theatre.

Driver Familiarity with Nonverbal Signs of Traffic and its Connection with the Role of Television Programs

The study entitled “Driver Familiarity with Nonverbal Signs of Traffic and its Connection with the Role of Television Programs”. Itis a descriptive study, with using both analytical and survey methods. The main objectives of it is to identify the roles and consequences of television programs on the identification of traffic nonverbal signs among drivers, then to analyze the meanings of traffic icon signs in Kalar district. The sample of the study consists of all traffic signs in Garmian administration, including (26) signs in the main streets of Kalar that were taken through boards sampling, and (506) drivers who have (private and public licenses)formthe both (maleand female)genders in Kalar district who were randomly selected. In conclusion, several scientific results are found such as that each nonverbal traffic in terms of color, shape and content has its own linguistic meaning and direct a specific message for the drivers’ safety in the different areas. The research also shows that the specific traffic television programs have high positive impact in familiarizing drivers with the various content of the traffic signs. it also clarifies that there are some other nonverbal signs that the television programs have paid little attention to introducetheir contentswhich the majority of drivers do not understand the messages behind them.

Examining the optimum panel pillar dimension in longwall mining considering stress distribution

Longwall mining method is widely used for underground coal production in the world. Additional stresses occur surrounding the longwall during underground mining. Stresses occurring surrounding the longwall are investigated by many researchers for years. How these stresses affect longwall production, gob, main gate, tailgate and main haulage road has been always an important issue. In this study, the effect of the safety pillar left at the end of the panel on the main haulage road is investigated. For this purpose, 6 models with different pillar distances are created and the stresses occurring in the main haulage road, tailgate and main gate at different pillar distances are examined. It has been demonstrated with numerical models that the optimum pillar distance according to these stress conditions does not damage the main haulage road, tailgate and main gate. In addition, the pillar distance of 10 m gives maximum coal recovery efficiency, and it has been shown by numerical models that the stresses occurring in the main haulage road, main gate and tailgate are not damaging to these galleries.

Investigation of Emission Inventory for Non-Road Mobile Machinery in Shandong Province: An Analysis Grounded in Real-World Activity Levels

In tandem with the advancement of urban intelligent technology, the construction of remote monitoring platforms and databases for non-road mobile machinery is gradually improving in various provinces and cities. Employing the remote monitoring platform for non-road mobile machinery enables a detailed big data analysis of the actual operational state of the machinery. This method yields precise data on the activity levels of various machinery types. Importantly, it addresses the issue of reduced accuracy in emission inventories, which often arises from the conventional practice of using standard recommended values from the Guide to determine machinery activity levels during the compilation of non-road mobile machinery emission inventories. Based on the remote monitoring and management system of non-road mobile machinery, the actual value of the activity level of non-road mobile machinery was obtained, and the emission inventory of non-road mobile machinery in Shandong Province was established. The emission levels of PM, HC, NOx, and CO from main non-road mobile machinery, including forklifts, excavators, loaders, off-road trucks, and road rollers, were measured. The findings indicate that the operational activity levels of non-road mobile machinery in Shandong Province typically exceeded the guideline’s recommended values. Among them, the annual use time of port terminal ground handling equipment was the longest, with an average annual working time of 4321.5 h per equipment, more than six times the recommended value. Among all types of non-road mobile machinery, loader emissions accounted for the highest proportion, reaching 43.13% of the total emissions of various pollutants. With the tightening of the national standard for non-road mobile machinery from Stage II to Stage III, a significant reduction in actual mechanical emissions was observed, primarily manifested as a 91% decrease in NOx emissions. Based on the data from the remote monitoring platform, a new method for compiling the emission inventory of non-road mobile machinery is proposed in this paper. The calculated emission inventory can reflect more real emission situations and provide a reference and basis for emission control and sustainable emission reduction policy measures for non-road mobile machinery.

INTEGRATION OF DEEP LEARNING MODELS FOR VEHICLE COUNTING: TOWARDS OPTIMIZED PLANNING OF URBAN CHARGING INFRASTRUCTURES

Abstract. Amidst the rising prevalence of electric vehicles (EV) and the corresponding need for adequate charging infrastructures, this study presents an innovative application of deep learning models to analyze urban traffic. Utilizing the YOLO v3 model, our research focuses on developing a prototype for counting vehicles at an urban roundabout connecting three main roads, providing essential data for planning EV charging infrastructures. This work involves adapting and optimizing the YOLO v3 model to accurately identify and count vehicles passing through the roundabout. The aim is to measure traffic volume and identify circulation trends, which are crucial for understanding the spatial and temporal distribution of vehicles. The collected data not only estimate the number of EVs likely to traverse this area but also predict the needs for charging infrastructure in and around this specific roundabout. Our prototype demonstrated high accuracy in vehicle counting, allowing detailed analysis of traffic patterns at different times of the day. This analysis reveals significant variations in traffic flows, providing valuable insights into the most suitable times and locations for installing EV charging stations. While this study focuses on a single roundabout, it establishes a precedent for using advanced deep learning techniques in assessing EV charging infrastructure needs in broader urban contexts. The results suggest that such methods can be extended to other urban areas for more comprehensive and effective planning of EV charging infrastructures, thus contributing to more sustainable and intelligent urban mobility management.

Influence of Strong Directional Sources in Ambient Seismic Imaging using Traffic-induced Noise

Continuously moving seismic sources, such as vehicles and train cars, play a crucial role as passive sources for non-destructive exploration in urban areas. Seismic interferometry is commonly employed in field data acquisition and processing, using linear arrays. However, the simultaneous recording of high energy noise, excited by buildings and factories, cannot be overlooked. We simulate moving-source seismic records with strong noises using orthogonal arrays. When strong noise originates from specific angles, the energy-phase velocity curves of arrays in different directions significantly diverge. We demonstrate that an L-shaped array, formed by orthogonal arrays, can effectively mitigate this effect, yielding more consistent results. Nonetheless, spatial constraints often preclude the deployment of L-shaped arrays. To mitigate this issue, we propose a new parallel observation system in this paper. Field tests conducted on a main road validate that the new array is comparable to the L-shaped array in terms of dispersion extraction. Similar to synthetic data, the phase velocity extracted from the linear array field data is found to be unreliable. Drilling data aligns well with the inversion results of the parallel observation system. Given the challenges of urban traffic-induced signal acquisition, deploying multi-azimuth arrays to minimize noise impact is essential. Considering spatial limitations, the convenient parallel observation system emerges as a good choice.

SUITABILITY ANALYSIS FOR URBAN BICYCLE TOURISM OF ILOILO CITY USING GIS

Abstract. Urban bicycle tourism refers to the recreational and enjoyable use of bicycles in navigating urban cities like Iloilo City. The city has already established an 11-kilometer cycling infrastructure within its boundaries. It is imperative to maximize its use to combat the negative impacts of rapid urbanization and promote safe and sustainable transportation. This paper shows the use of Geographic Information Systems (GIS) to assess the bike lanes network's suitability and accessibility for building a bike-sharing system that also caters to drop-off and ride-on points at each station. Deletion of duplicates and cleaning of road network data and tourist attraction point data was performed prior to any analysis. Service areas were generated to determine the number of tourist attractions catered by each potential bike share station – defined by main road intersections. Point distance analysis was performed to reduce the number of road intersections to just thirty-nine (39). Bicycle route maps and itineraries were produced to visualize the optimal routes tourists can use for exploring the city based on preferred sites category. From here, Route Analysis was conducted to create four (4) itineraries based on tourism categories: Top 10 Most Rated Tourist Attractions, Food and Dining, Museums and Churches, and Shopping and Leisure. The output maps and itineraries can be presented to the City Tourism Office of Iloilo City as a decision support tool for its programs and policies regarding bike lanes.

The effect of female leadership on contracting from Capitol Hill to Main Street

This paper provides novel evidence that female politicians increase the proportion of US government procurement contracts allocated to women-owned firms. For identification, we use a regression discontinuity design on a sample of mixed-gender elections in the US House of Representatives. The effect grows over a female representative's tenure and concentrates in female representatives who are on powerful congressional committees. Changes in the pool of and behavior by government contractors cannot explain the result. The more gender-balanced representation in government contracting is not associated with economic costs.

Design of mixed fixed-flexible bus public transport networks by tracking the paths of on-demand vehicles

On-demand ridepooling (ODRP) vehicles follow routes that are fully flexible. However, when the system does not provide door-to-door service and users can be asked to walk, their paths tend to concentrate, particularly along main streets that connect highly demanded areas of the city. These frequently travelled segments are hence useful to multiple passengers, which can be used as an indicator that it would be efficient to allocate a fixed public transport line there.In this paper, we formalise this idea and propose a novel method to design a public transport network, where bus fixed lines are combined with ODRP. Given a network and a transport demand, we first simulate how to serve it using only ODRP with walking. For this, we employ a state-of-the-art assignment algorithm, and take as output the resulting users’ paths. These paths are then processed by a tailored algorithm to create fixed lines where the paths accumulate the most. Users who do not have an available fixed line (i.e., those whose paths were barely shared) are served by ODRP in the mixed system. Simulations using real-life data from Utrecht, The Netherlands, and the Sunshine Coast, Australia, reveal the merits of our method compared to several benchmarks. Crucially, our method builds a small number of fixed lines while still serving the majority of the demand through them.This study contributes not only to the design of public transport networks, but also to the understanding of the patterns that naturally appear in intrinsically flexible mobility systems.

GIS-Enabled Multi-Criteria Assessment for Hospital Site Suitability: A Case Study of Tehran

In developing countries, the interaction between rapid urban expansion and population growth brings forth a host of challenges, particularly concerning essential services like healthcare. While interest in site suitability analysis for identifying optimal hospital locations to ensure equitable and secure healthcare access is on the rise, the absence of a holistic study that encompasses social and environmental aspects in the assessment of hospital site suitability is evident. The objective of this research is to introduce a hybrid methodology that combines Geographic Information Systems (GIS) with Multi-Criteria Decision-Making (MCDM) weighting methods. This methodology aims to create hospital site suitability maps for districts 21 and 22 in Tehran, taking into account socio-environmental factors. In addition to the conventional Analytical Hierarchical Process (AHP) weighting method, this study employs two relatively less-explored methods, the Best-Worst Method (BWM) and Step-wise Weight Assessment Ratio Analysis (SWARA), to enhance the analysis of hospital site suitability. In the SWARA method, there are minimal variations in weights among criteria, indicating that all socio-environmental factors (e.g., distance from existing hospitals, distance from main roads, distance from green spaces) hold significant importance in the decision-making process. Additionally, the findings indicate that the western part of the study area is the most suitable location for the construction of a new hospital. To achieve the average hospital bed availability in Tehran, an additional 2206 beds are required in the studied area, in addition to the existing facilities. Considering the ongoing urban development, population growth, and the potential for natural disasters and epidemics, it becomes essential to enhance the healthcare system by increasing the number of hospitals and available hospital beds. The sensitivity analysis showed that GIS-based SWARA-WLC was the most suitable and stable model for determining hospital site suitability in the study area. This methodology can be adapted for use in other regions and further improved by incorporating additional criteria. In conclusion, the study recommended three specific alternative sites for establishing a new hospital in the study area.

Road Traffic Noise Annoyance and Cardiovascular Disease Risk in Population: A Case Series Study in Kota Bharu, Malaysia

Noise pollution can cause annoyance, significantly threatening the population’s health and well-being. This study aimed to find an association between road traffic noise exposure and cardiovascular disease (CVD) risk among residents in Kota Bharu, Malaysia. This descriptive study used a case series approach and surveyed 34 residents in selected residential areas near main roads. An adapted questionnaire was distributed to residents using a purposive sampling method. Questions related to sociodemographic information, self-reporting about CVD, and road traffic noise assessment were asked to investigate the underlying risk factors for CVD. The average score of CVD assessment was classified as moderate risk. No significant association between noise annoyance and CVD was found using multiple linear regression. However, the association between cardiovascular risk and sociodemographic variables, particularly the length of residency at the current address, was statistically significant. Although noise annoyance was not associated with CVD, the length of residency could mediate CVD risk as those living longer in residence might be less vulnerable to the noise. Future longitudinal studies are recommended, which include a noise exposure assessment with a larger sample.

Study of medium and long-term free flow capacity and queue discharge rates on roads.

With the rise in vehicle ownership, traffic congestion has emerged as a major barrier to urban progress, making the study and optimization of urban road capacity exceedingly crucial. The research on the medium and long-term free-flowing capacity and queue emission rate of roads takes an in-depth exploration of this issue from a cutting-edge perspective, aiming to find solutions adaptable to the progression of the times. The purpose of this study is to understand and predict the road capacity and queue emission rate more accurately, thus improving the urban traffic condition. Existing literature primarily focuses on short-term forecasts of road capacity, leaving a notable void in the research of medium and long-term road capacity and queue emission rate. This gap often results in a lack of sufficient foresight when urban traffic planning faces practical issues. To fill this void, this study undertook an in-depth examination of the road capacity and queue emission rate over the medium and long term (10 years) based on big data analysis and artificial intelligence theories. This paper employs a Radial Basis Function (RBF) neural network, combined with twelve other parameters that could potentially impact road capacity, such as traffic volume, road width, number of lanes, traffic signal control methods, etc., to analyze the relationship between each parameter and free-flow traffic and queue emission rate. These analyses are grounded in extensive road data, encompassing not only the city's main roads but also secondary roads and community roads. The study results show a continuous downward trend in the free-flowing capacity of roads and a slight upward trend in the queue emission rate over the past decade. Further analysis reveals the extent of impact each factor has on the free-flow traffic and queue emission rate, providing a scientific basis for future urban traffic planning.

Effects of neighborhood built environment on cognitive function in older adults: a systematic review

BackgroundIn the background of an aging population, the risk of cognitive impairment in the older population is prominent. Exposure to complex neighborhood built environments may be beneficial to the cognitive health of older adults, and the purpose of this study was to systematically review the scientific evidence on the effects of neighborhood built environments on cognitive function in older adults.MethodsKeywords and references were searched in Web of Science, Pubmed, PsycINFO, and MEDLINE. Studies examining the relationship between the built environment and cognitive function in older adults were included. The neighborhood built environment as an independent variable was classified according to seven aspects: density, design, diversity, destination accessibility, public transportation distance, blue/green space, and built environment quality. The cognitive function as the dependent variable was classified according to overall cognitive function, domain-specific cognitive function, and incidence of dementia. The quality of the included literature was assessed using the National Institutes of Health's Observational Cohort and Cross-Sectional Study Quality Assessment Tool.ResultsA total of 56 studies were included that met the inclusion criteria, including 31 cross-sectional studies, 23 longitudinal studies, 1 cross-sectional study design combined with a case-control design, and 1 longitudinal study design combined with a case-control design. Most of the studies reviewed indicate that the built environment factors that were positively associated with cognitive function in older adults were population density, street connectivity, walkability, number of public transportation stops around the residence, land use mix, neighborhood resources, green space, and quality of the neighborhood built environment. Built environment factors that were negatively associated with cognitive function in older adults were street integration, distance from residence to main road. The relationship between residential density, destination accessibility, and blue space with cognitive function in older adults needs to be further explored.ConclusionPreliminary evidence suggests an association between the neighborhood built environment and cognitive function in older adults. The causal relationship between the built environment and cognitive function can be further explored in the future using standardized and combined subjective and objective assessment methods, and longitudinal or quasi-experimental study designs. For public health interventions on the cognitive health of older adults, it is recommended that relevant authorities include the neighborhood built environment in their intervention programs.