High Road Research Articles

Organizing planning knowledge for automated vehicles and intelligent transportation systems

AbstractIntelligent Transportation Systems (ITS) are crucial for developing fully automated vehicles. While significant progress has been made with advanced driver assistance systems and automation technology, challenges remain, such as improving traffic information, enhancing planning and control systems, and developing better decision‐making capabilities. Despite these hurdles, the potential benefits of ITS are so many that its challenges have attracted substantial industrial investment and research groups interested in the automated driving field. In this work, a methodology based on state space search for planning knowledge integration is proposed. The main goal of the proposal is to provide a planning system with the necessary information to perform properly any task related to lateral and longitudinal control, path following, trajectory generation, arbitration and behavior execution by localizing the vehicle with respect to a high‐level road plan. To this end, this research compares cutting‐edge methods for rapidly finding the K nearest neighbor in relatively high dimensional road plans constructed from the traffic information stored in a high definition map. During the experimentation phase, promising real‐time results have been obtained for fast KNN algorithms, leading to a robust tree index‐based methodology for decision making in self‐driving vehicles combining path planning, trajectory tracking, trajectory creation, knowledge aggregation and precise vehicle control.

Washable oil-coated structured support for passive outdoor particulate matters trapping

Direct outdoor air depollution represents an interesting path for preventing indirect disease. In the present work, a simple and efficient PMs trapping media based on the use of an oil-coated structured polymer media was developed for passive trapping of various PMs, ranging from coarse (PM10), to fine (PM2.5) and ultra-fine (PM1) dimension in outdoor environment. The device can be easily regenerated by a simple washing with a mixture of water and detergent followed by a new oil coating cycle. The total PM loading mass of the passive trap and the recovered PMs are analyzed through different techniques and confirm the great efficiency of such filter to trap various PMs when exposed to a high traffic road. The spent filter can be regenerated through a simple washing step and can be repeatedly re-used with similar PM loading mass. The high and long-lasting total PM loading mass were also supported by numerical simulations based on computational fluid dynamics, also used to propose an optimization implementation of such system for future deployment at scale.

Recycling steel slag as aggregate in developing an ultra-thin friction course with high comprehensive road performance

The demand for skid-resistant and wear-resistant alternative aggregates in the preparation of ultra-thin friction course (UTFC) asphalt mixtures is a key direction for achieving high durability and low-carbon development in pavement maintenance. As a typical industrial waste, steel slag with high alkalinity and strong adhesion can facilitate the mechanical property of asphalt mixtures. However, few researches focused on the impact of steel slag on the comprehensive road performance of UTFC mixtures. Hence, the issue merits systematic exploration. In this study, the chemical components, microstructure and morphological characteristics of three steel slags (GXSS, HBSS and IMSS) obtained from different sources were surveyed. Then the stone matrix asphalt (SMA)-5 and open-grade friction courses (OGFC)-5 mixtures with different steel slags were fabricated. And their comprehensive road performances were quantitatively explored via the improved radar chart. The results indicate that steel slag with approximately 40 % Ca content, about 20 % Fe content, irregular shapes and tiny pores endows its wear resistance and strong adhesion. IMSS demonstrates the largest average angularity and form 2D values of 3850 and 7.28, respectively, representing its significant crowding function and interlocking structure. Incorporating steel slag remarkably reinforces the rutting resistance, skid resistance and anti-interlayer shear performance of UTFC. While the effect of water stability and crack resistance of UTFC depend on the category of steel slag. All three steel slags manifest the improvement function on the comprehensive assessment indexes (CAI) of OGFC-UTFC. IMSS-OGFC reveals the optimal comprehensive road performance, achieving the highest CAI of 0.9909. It is inferred that steel slag is more suitable for OGFC-UTFC than SMA-UTFC due to its relatively high CAI and consistent performance regardless of the steel slag type.

Fisher activity patterns show potential for behavioral adaptations to human modified landscapes

Animals alter their diel activity in response to physiological constraints and ecological conditions. Fisher (Pekania pennanti) activity is known to vary through the diel cycle and change in response to cold stress and generally through both the climatic and biological seasons. However, less is known whether thermoregulatory effects impact fisher activity in milder climates and in areas of high human disturbance. We focused on two distinct research objectives to understand the 1) physiological constraints, and 2) ecological components of fisher activity in a highly disturbed landscape with a relatively mild climate. We used accelerometer data from 34 individual live-captured fisher in Rhode Island, USA from 2021 to 2023. We found that fisher activity patterns were primarily driven by diel cycle with higher activity levels at night than during the day. We did not observe any physiological influence of ambient temperature on fisher activity; daily minimum temperatures did not constrain fisher activity in the colder months, nor did daily maximum temperatures in warmer months. We did find that female activity levels differed by breeding status with non-pregnant females having higher activity levels than pregnant females. Considering ecological components, we found fisher decreased activity levels in higher road density areas during warmer months that coincide with higher traffic volumes. For fisher living in areas with lower road densities, we saw higher activity in the breeding season and summer than in winter. In contrast, fisher living in areas with high road densities had lower activity in the breeding season and summer than in winter. We conclude that fisher largely do not shift their activity to mitigate thermoregulatory costs in areas where temperatures do not reach extremes for extended periods of time. However, our findings suggest that behavioral shifts in activity are impacted by human disturbance and fisher minimize activity in risky areas.

The Mediating Role of Traffic Safety Awareness on Road Safety Attitude and Behavior of Drivers

This research study aimed to determine the mediating role of traffic safety awareness on the relationship between road safety attitude and behavior of drivers. The researcher surveyed 378 licensed drivers selected using a stratified random sampling technique. The study utilized Mean, Pearson Product Moment Correlation, Medgraph using Sobel z-test and Regression. The study found a very high level of Traffic Safety Awareness, a moderate level of Driving behavior, and high Road Safety Attitudes among licensed drivers. A significant correlation was observed between road safety attitude and drivers’ behavior. There is also a high significance on the relationship between road safety attitude and traffic safety awareness, as well as between traffic safety awareness and drivers’ driving behavior. The mediation analysis examined the role of traffic safety awareness as a mediator in the relationship between road safety attitude and driver behavior. The results point towards partial mediation, where the mediator variable partially explains the relationship between the independent and dependent variables.

High Traffic Roads and Adverse Birth Outcomes: Comparing Births Upwind and Downwind of the Same Road.

Traffic related air pollution is a major concern for perinatal health. Determining causal associations, however, is difficult since high-traffic areas tend to correspond with lower socioeconomic neighborhoods and other environmental exposures. To overcome confounding, we compared pregnant individuals living downwind and upwind of the same high-traffic road. We leveraged vital statistics data for Texas from 2007-2016 (n=3,570,272 births) and computed hourly wind estimates for residential addresses within 500 m of high-traffic roads (i.e., annual average daily traffic greater than 25,000) (10.9% of births). We matched pregnant individuals predominantly upwind to pregnant neighbors downwind of the same road segment (n=37,631 pairs). Living downwind was associated with an 11.6 gram (95% CI: -18.01, -5.21) decrease in term birth weight. No associations were observed with low term birth weight, preterm birth, or very preterm birth. In distance-stratified models, living downwind within 50 m was associated with a -36.3 gram (95% CI: -67.74, -4.93) decrease in term birth weight and living 51-100m downwind was associated with an odds ratio of 3.68 (95% CI: 1.71, 7.90) for very preterm birth. These results suggest traffic air pollution is associated with adverse birth outcomes, with steep distance decay gradients around major roads.

Drive-by bridge mode shape identification using novel reference-based component scaling method

This article proposes a novel method, entitled Reference-based Component Scaling (RCS) method, for estimation of bridge mode shapes using vehicle scanning methods. The proposed method uses two instrumented vehicles to measure the accelerations on the bridge. While one vehicle remains stationary on a pre-determined location, the other one travels over the bridge with a constant speed both exciting the bridge and recording its response. The accelerations recorded on both vehicles are then processed using variational mode decomposition method and Hilbert transform to obtain their modal components. Leveraging its comprehensive framework that incorporates modal components derived from both vehicles, the RCS method effectively tackles the primary challenges encountered by vehicle scanning methods. These challenges include: i) shifting and shrinking effects of bridge damping on mode shapes, ii) distortions in modal components due to incomplete elimination of the roughness effect and iii) distortions in modal components caused by acceleration peaks during the vehicle´s transition from a rigid platform to the bridge. To this end, the RCS method addresses adverse effects of bridge damping without a priori knowledge of the modal damping ratios. To assess the accuracy of the proposed method, numerical analyses were carried out on three different bridges with different number of spans and boundary conditions. The effect of crucial parameters such as road roughness, bridge damping, uncertainties in measurements, and existing traffic on the accuracy of the proposed method was investigated. The results of the numerical study show that the RCS method stands alone in providing accurate estimates of mode shapes of bridges that are seated on elastic bearings, that have realistic damping ratios and relatively high road roughness profiles.

Prediction of Radio Signal Failures of Communication Based Train Operating Systems by Machine Learning Methods

The use of rail systems in urban public transportation has become a necessity for reasons such as time saving, travel comfort and operating costs, especially in cities with high population and road traffic. Communication based train operating systems (CBTC) are used for the safe use of urban rail systems and the maximum capacity of the railway line. In this study, in line with the data collected from the trains on a railway line operated with CBTC, the status of the radio signals that enable the wireless communication of the trains with the trackside signaling equipment was evaluated by machine learning methods, and the situations that may have negative effects on the train operations of the problems at the signal level were evaluate. The problems on the antennas which receives signals from trackside above trains, the poor connection related with fiber optical and LAN cables, the trackside transmitter antenna orientation problems causes decrease on signal levels. It is aimed that to take actions about the problematic signal levels without any negative impact on the passenger comfort and the operation yet. The radio signal losses cause unexpected trains stops and delays. A decision support model has been developed that will offer early solution suggestions to system maintainers in order to intervene first. In conclusion, since it is the first study related with failure prediction by using radio signal levels data on railway signaling system, this study presents an important innovation in terms of literature.

Road Extraction from Remote Sensing Imagery with Spatial Attention Based on Swin Transformer

Road extraction is a crucial aspect of remote sensing imagery processing that plays a significant role in various remote sensing applications, including automatic driving, urban planning, and path navigation. However, accurate road extraction is a challenging task due to factors such as high road density, building occlusion, and complex traffic environments. In this study, a Spatial Attention Swin Transformer (SASwin Transformer) architecture is proposed to create a robust encoder capable of extracting roads from remote sensing imagery. In this architecture, we have developed a spatial self-attention (SSA) module that captures efficient and rich spatial information through spatial self-attention to reconstruct the feature map. Following this, the module performs residual connections with the input, which helps reduce interference from unrelated regions. Additionally, we designed a Spatial MLP (SMLP) module to aggregate spatial feature information from multiple branches while simultaneously reducing computational complexity. Two public road datasets, the Massachusetts dataset and the DeepGlobe dataset, were used for extensive experiments. The results show that our proposed model has an improved overall performance compared to several state-of-the-art algorithms. In particular, on the two datasets, our model outperforms D-LinkNet with an increase in Intersection over Union (IoU) metrics of 1.88% and 1.84%, respectively.

Unveiling transportation disparities: investigating accessibility gaps in metropolitan cities using GIS—a case study of Alexandria, Egypt

IntroductionPublic transportation is essential to reduce pollution and traffic congestion in urban areas. However, in densely populated regions like Alexandria, characterized by high population density and limited road infrastructure, accessibility to diverse transportation options is crucial.MethodsThis study investigates the accessibility of public transportation modes, including railways and buses, and their interaction with informal transit. Questioning if public transportation alone will be sufficient for pedestrians or if the presence of informal transit is crucial, and whether all residents of Alexandria have their rightful accessibility for different transport modes, the goal was to establish an efficient and interconnected transportation network. A survey was conducted in cooperation with Transport for Cairo to investigate all transport routes throughout Alexandria, further using ArcGIS Pro to identify gaps in public transportation coverage.ResultsFindings revealed that public transportation alone is insufficient due to limited bus and railway coverage because of their fixed linear routes. Informal transit, like microbuses, plays a vital role in filling these gaps.DiscussionThe study emphasizes the need for a comprehensive and sustainable transportation network that considers both formal and informal transit. These insights can guide policymakers and urban planners in improving public transportation in Alexandria and similar cities worldwide.

Manifestations of Criminal Professionalism in the Activities of Robber Gangs of Pre-Revolutionary Russia

Relevance. Professional crime is one of the most dangerous, relatively independent types of crime, which poses a serious threat to modern society and the state. Currently, there is no unified approach to assessing the state, dynamics and trends of this dangerous criminal phenomenon. Mechanisms to combat this type of criminal activity that are adequate to the level of danger have not been identified. In this regard, special studies of professional crime in all its complexity and ambiguity are becoming particularly relevant, including those affecting certain issues of the evolution of this dangerous criminal phenomenon in time and space.The purpose. He purpose of the study is a theoretical analysis and definition of the socio-legal essence of professional crime in pre-revolutionary Russia (using the example of the analysis of socially dangerous activities of robber gangs).Objectives: to analyze the domestic legislation of the pre-revolutionary period, providing for accountability for repeated robbery; to determine the specifics of committing crimes on a professional basis by robber gangs in prerevolutionary Russia; to identify elements of the criminal subculture supported by the community of professional robbers in the period under study in Russia.Methodology. To achieve this goal, such general scientific and private scientific research methods as the method of analysis, synthesis, generalization, comparative legal and chronological methods were used.Results. It was determined that many robbers who traded on the «high roads» during the studied period possessed all the signs of criminal professionalism: the presence of criminal specialization, qualifications, perception of criminal activity as a source of income, connections with the criminal world, including those expressed in the perception and multiplication of values and norms of the emerging criminal subculture.Conclusion. By the end of the nineteenth and early twentieth centuries, a monolithic, well–structured consolidated and criminal world had formed in Russia, in which the professional criminal «core» played a special role. Professional robbers occupied not the least place in the criminal hierarchy, causing significant harm to economic relations in society and the national security of the country.

Wildlife mortality risk posed by high and low traffic roads.

Wildlife mortality due to collisions with vehicles (roadkill) is one of the predominant negative effects exerted by roads on many wildlife species. Reducing roadkill is therefore a major component of wildlife conservation. Roadkill is affected by various factors, including road attributes and traffic volume. It is theorized that the effect of traffic volume on roadkill probability should be unimodal. However, empirical evidence for this theory is lacking. Using a large-scale roadkill database of 18 wildlife species in Israel, encompassing 2846km of roads over 10years, we explored the effects of traffic volume and road attributes (e.g., road lighting, verge vegetation) on roadkill probability with a multivariate generalized linear mixed model. A unimodal effect of traffic volume was identified for the striped hyena (Hyaena hyaena), whereas 5 species demonstrated a novel quadratic U-shaped effect (e.g., golden jackal [Canis aureus]). Four species showed a negative linear effect (e.g., wild boar [Sus scrofa]). We also identified varying effects of road attributes on roadkill. For instance, road lighting and roadside trees decreased roadkill for several species, whereas bus stops and concrete guardrails led to increased roadkill. The theorized unimodal effect of traffic volume may only apply to large, agile species, and the U-shaped effect could be related to intraspecies variability in traffic avoidance behavior. In general, we found that both high-traffic and low-traffic roads can pose a high mortality risk for wildlife. It is therefore important to monitor roadkill on low-traffic roads and adapt road attributes to mitigate roadkill. Road design for effective roadkill mitigation includes reducing the use of concrete guardrails and median barriers where possible and avoiding dense bushes in verge landscaping. These measures are complemented by employing wildlife detection systems, driver warnings, and seasonal speed reduction measures on low-traffic roads identified as roadkill hotspots.

I’ll take the high road: Paths to goal pursuit and identity-based interpretations of difficulty

ABSTRACT When imagining their futures, people can prioritize getting there the easy way, prefer more demanding paths, or be indifferent to means and focus only on making progress. Identity-based motivation theory predicts and mixed effect regressions reveal that what people infer about themselves when facing unchosen life difficulties and when thinking about or working on goals feels hard shapes action (N = 537 undergraduates, three studies). To varying degrees, they can infer that unchosen life difficulties build character (difficulty-as-improvement), that chosen goals are really not for them (difficulty-as-impossibility), and that chosen goals are valuable for them (difficulty-as-importance). The more people endorse difficulty-as-impossibility, the more they choose ease. The more they endorse difficulty-as-improvement the more they disdain ease and prefer the effortful way.

Vehicle routing problem with time windows and carbon emissions: a case study in logistics distribution.

Logistics and transportation industry is not only a major energy consumer, but also a major carbon emitter. Developing green logistics is the only way for the sustainable development of the logistics industry. One of the main factors of environmental pollution is caused by carbon emissions in the process of vehicle transportation, and carbon emissions of vehicle transportation are closely related to routing, road conditions, vehicle speed, and speed fluctuations. The low-carbon vehicle routing problem with high granularity time-dependent speeds, speed fluctuations, road conditions, and time windows is proposed and formally described. In order to finely evaluate the effects of vehicle speed and speed fluctuations on carbon emissions, a graph convolutional network (GCN) is used to predict the high granularity time-dependent traffic speeds. To solve this complicated low-carbon vehicle routing problem, a hybrid genetic algorithm with adaptive variable neighborhood search is proposed to obtain vehicle routing with low carbon emissions. Finally, this method is validated using a case study with the logistics and traffic data in Jingzhou, China, and also the results show the effectiveness of this proposed method.

Traffic Exposure and Breast Cancer Mortality by Area of Residence: Incorporating Clinical and Socioeconomic Data.

Incorporating clinical and environmental data holds promise for monitoring vulnerable populations at the community level. This spatial epidemiology study explores the link between traffic-related air pollution and breast cancer mortality in Seoul, using public socioeconomic and clinical data from Samsung Medical Center's registry (N=6,089). Traffic and socioeconomic status were collected from official sources and integrated for spatial analysis. The findings revealed a significant association between adult breast cancer mortality and districts with high road density, NO2 emissions, and family income (p<0.05). Significant spatial autocorrelation of residuals was observed (Moran's I test p<0.001).

Shifting Modes of Labor Regulation in Global Supply Chains

executive summary: This essay outlines the changing modes of regulation of labor conditions in global apparel supply chains, which are mostly concentrated in Asia; assesses the effectiveness of 25 years of private voluntary regulation by global firms; and examines critically the implications of new European regulation now mandating what was previously a voluntary corporate activity. main argumentAsia is the global center of apparel production, with Bangladesh, Cambodia, China, India, Indonesia, Pakistan, and Vietnam all being major exporters. Since the 1990s, activist pressure in developed country markets has forced global apparel and footwear companies to adopt voluntary methods to ensure that their products are not made under sweatshop conditions. Companies developed codes of conduct for the first-tier factories in their supply chains and found ways to audit whether supplier factories were in compliance. However, this voluntary private-regulation model has not been adequate to alleviate labor and workplace concerns in global apparel supply chains. A shift from private regulation to public regulation—the beginning of which may be currently underway in the European Union with the recent introduction of mandatory due diligence legislation—may prove to be a more effective means of bettering labor rights and conditions. policy implications• If the recent EU legislation allows global companies to be legally liable for violations of mandatory due diligence requirements regarding labor rights and conditions in supply chains, a sea change in worker rights and labor practices could occur. • The new legislation would require global companies to adopt more responsible purchasing practices so that their practices are not responsible for labor violations. • The EU legislation could have an impact on sourcing locations, as companies compete for locations that are more likely to provide institutional environments with lower risk of violations. Global suppliers would have a greater incentive to take the high road in terms of employment practices to obtain more business from European buyers. National governments in apparel-exporting countries may be motivated to improve enforcement of labor regulations.

연료 품질에 따른 증발가스 배출 및 고온과 실도로 조건에서의 차량 퍼지 특성 분석

연료 품질에 따른 증발가스 배출 및 고온과 실도로 조건에서의 차량 퍼지 특성 분석

Farm Access Roads: The Low Cost Convergence Model for Doubling Farmers’ Income in India

"In agricultural sector, many policy reforms in India are introduced to achieve the target of doubling farmers’ income. Most of the recent studies and policy focuses on rural roads, while the critical part, which is still unaddressed, is the farm access roads (Pandan or Dhuri roads). We did a study in Amravati district of the Maharashtra state on the farm access roads. Farms are becoming inaccessible because of absence of proper road. Farmer are not able to take high value crops, scheduled farm operations are getting distorted and sometimes bringing the harvest from farms to home or market becomes difficult. In addition, owing to accessibility issues, farmers are not able to cultivate land, which result in low productivity and low income, especially small and marginal farmers, who are the majority, have no capacity to pay for or build farm roads. We recommend a convergence “farm road access model” implemented in Amravati district, dovetailing schemes of the Mahatma Gandhi National Rural Employment Guarantee (MGNREGA), state funds and farmer’s contribution or Corporate Social Responsibility (CSR) funds. The two types of roads under this model are as, low cost farm access road of ` 1,50,000 per kilometre and high cost road of ` 17,00,000 per kilometre. The impact of farm access roads is that farmers are able to get access to their land throughout the year and are able to do farm operations timely. Overall, it resulted in increase in farmers’ income by one third. Therefore, we strongly suggest replicating the Amravati farm access road (Har Khet ko Rasta) model across the nation."

Start of dawn singing as related to physical environmental variables in an alpine environment

Birds often have a peak of singing activity at dawn, and the timing of dawn song is species-specific. However, the start of singing at dawn may also depend on environmental factors. We investigated the effects of different environmental variables on the start of dawn singing in six common songbird species in the woodlands of the Swiss National Park. Moon phase, aspect, temperature and road noise had the most consistent effects across species: dawn singing started earlier after brighter and warmer nights, on more east-exposed slopes, and in areas with more road noise. On average, birds started to sing 2.8 min earlier in areas with high road noise level compared to areas without road noise, and 4.7 min earlier in east-exposed slopes compared to west-exposed slopes. Further, birds started to sing on average 5.0 min earlier after full moon compared to new moon nights, 1.2 min earlier after warmer compared to colder nights, and 2.5 min earlier at 2200 m than at 1500 m a.s.l. The effects of date were more species-specific: Alpine Tits started to sing on average 4.9 min later at the end compared to the beginning of the study period, whilst Song Thrushes started to sing 9.0 min earlier. Our findings are in line with the results of previous studies on the effects of road noise, nocturnal light, and partly on temperature. Our study shows that variation in environmental variables may influence the start of dawn singing in different ways, and that anthropogenic factors like road noise can affect bird behaviour even in a highly protected area.

Transportation Disaster Risk Analysis on The Road Segment Tapan (South Pesisir, West Sumatera) – Sungai Penuh (Kerinci, Jambi)

Road segments ranging from local roads to national roads are the most urgent arteries in the mobilization of goods and people and determine the progress of economic development. Therefore the road must be constructed in accordance with the standards set out in the laws and regulations, including here the national road that has high economic value that connects the two regions of the two provinces namely Tapan Pesisir Selatan in the West Sumatra province and the Sungai Penuh Kerinci in Jambi province the two regions is closely related in economic and trade relations and the distance is only close to 64 km, but the terrain conditions have the potential to cause traffic accidents because natural factors penetrate row hills that have high geographical and national road standardization factors that do not have the attributes of road safety equipment complete. In this regard, it is necessary to examine how much the level of potential hazards caused by roads through disaster risk analysis in the transportation sector using the disaster risk analysis model. The results of the analysis using the disaster risk analysis model of the Tapan Sumbar - Sungai Penuh Kerinci Jambi road have a high hazard vulnerability level of 8.05 or above 5 means that this road needs to be improved both its construction and road safety equipment.