Sub-arterial Roads Research Articles

Assessing indoor and outdoor noise quality and associated health impacts at selected schools in Surat, India

An optimal ambient environment is crucial for healthy development, yet the excess of vehicles and inadequately planned educational infrastructures compromise cognitive growth in children. This study evaluates the impact of ambient noise on student cognition in five schools situated along city arterial and sub-arterial roads. A total of 717 students from grades 7, 8, 9, and 11 participated. Noise levels were measured in prevailing noisy conditions (PC) and controlled silence conditions (SC) within classrooms using the Kimo dB300 sound level meter. The observed differences in noise levels between PC and SC varied across grades, showing reductions of 4.7 ± 3.5 dB, 6.1 ± 0.7 dB, 6.7 ± 1.3 dB, and 4.4 ± 3.46 dB for grades 7, 8, 9, and 11, respectively. Statistical analyses revealed significant differences in the average noise levels under both conditions. Furthermore, cognitive task performance in PC and SC was significantly different, as evidenced by paired t-tests in tasks such as multiplication, word formation, reasoning, and sentence construction. Dimension reduction techniques identified room acoustics, task difficulty, speech intelligibility, mental deficiency, and annoyance as critical factors affecting learning abilities. Teachers reported that major impacts of noise include annoyance, sleeplessness, headache, and hearing impairment.

Measuring the age-friendliness of streets' walking environment using multi-source big data: A case study in Shanghai, China

The rapidly aging population demands more public and academic attention to both the physical and psychological needs of older adults. Walking is one of the most favored forms of transportation and exercise for older adults. Hence, the conditions of walkways and the built environment are critical for the development of an older adults-friendly society. In this research, considering six indicators of greenness, walkability, safety, imageability, enclosure, and complexity, a novel quantitative evaluation model based on multi-source geospatial big datasets is proposed for assessing the age-friendliness of streets' walking environment from both the older adults' and experts' perspectives and has also been successfully applied in the case study of Xuhui District in Shanghai, China. Based on the survey with both groups of older adults and experts, the age-friendliness of the streets' walking environment from both perspectives was obtained, analyzed, and compared. The results show that among all sub-districts in Xuhui District, Tianping Road Sub-district and Hunan Road Sub-district have the best walking environment; and the roads surrounding expressways or arterial roads typically have lower levels of age-friendliness, while sub-arterial roads and access roads generally exhibit higher levels of age-friendliness according to both older adults and experts. It is also noted that streets with high age-friendliness for older adults tend to be outstanding in walkability and greenness, whereas experts prefer streets with high safety and walkability. In addition, the comprehensive analysis of the impact factors on age-friendliness further reveals a series of hidden significant influencing factors associated with the different preferences between older adults and experts. It is believed that our findings are useful for supporting policy-makers on how to improve the age-friendliness of streets and build age-friendly cities.

Development of a Methodology for Estimating the Availability of ADAS-Dependent Road Infrastructure

Advanced driver assist systems are being promoted with the expectation that enhanced driver support will mitigate road trauma. While these technologies are optimised for certain road and traffic conditions, not all roads across Australasia are equipped with ADAS-supportive infrastructure. This study developed a desk-top methodology for using road classes (disaggregated by remoteness levels) to estimate the presence of quality roads, road delineation and speed signage in Victoria, Australia. Aerial imagery and mapping data were used to assess a number of random locations based on a developed protocol. The methodology demonstrated that in Victoria, major and arterial roads across all remoteness levels had high-quality sealed surfaces but 42% of all remote roads were unsealed. Delineation (crucial for lane support systems) were absent across 73% of sub-arterial roads independent of remoteness, and absent across 96% of sub-arterial roads in regional and remote areas. Speed sign availability across remote and regional areas was sparse, with only 65% of all roads assessed having signage. Results are reflective of Victoria’s road funding model and consistent with on-road audits conducted by other researchers. This methodology enables the proportion ADAS-ready roads to be estimated so the benefits of ADAS technologies can be quantified and investments into ADAS-supportive infrastructure be readily allocated.

Exploring coupling effect between urban heat island effect and PM2.5 concentrations from the perspective of spatial environment

The coupling effect between urban PM2.5 concentrations and urban heat island effect has been paid more and more attention to. Previous studies mostly focused on the analysis of data correlations, lacking the interpretation of the formation texture. Taking Hefei as the subject, this study combined the spatial statistical model with the coupling coordination degree model to explore the influence of spatial environment-related indicators on the coupling effect of cities. In addition, at the micro level, the paper used grid unit to verify the relevance and made a comprehensive analysis on the formation texture of coupling effect. The results indicated that: (1) there is a significant coupling effect between the urban heat island intensity and PM2.5 concentrations in the main urban area of Hefei with significant spatial heterogeneity. (2) to some extent, the indicators of urban spatial environment, including vegetated areas, buildings, residential land, commercial land, industrial land, building density, floor area ratio, building form ratio, the densities of road junctions and sub-arterial roads, have different effects on the coupling effect. In general, the higher the degree of human activity, the higher the degree of coupling effect. (3) the coupling effect may be influenced by a variety of spatial environment factors.

Use of Spatial Analysis Techniques to Identify Statistically Significant Crash Hot Spots in Metropolitan Melbourne

Understanding where, when, what type and why crashes are occurring can help determine the most appropriate initiatives to reduce road trauma. Spatial statistical analysis techniques are better suited to analysing crashes than traditional statistical techniques as they allow for spatial dependency and non-stationarity. For example, crashes tend to cluster at specific locations (spatial dependency) and vary from one location to another (non-stationarity). Several spatial statistical methods were used to examine crash clustering in metropolitan Melbourne, including Global Moran’s I statistic, Kernel Density Estimation and Getis-Ord Gi* statistic. The Global Moran’s I statistic identified statistically significant clustering on a global level. The Kernel Density Estimation method showed clustering but could not identify the statistical significance. The Getis-Ord Gi* method identified local crash clustering and found that 15.7 per cent of casualty crash locations in metropolitan Melbourne were statistically significant hot spots at the 95 per cent confidence level. The degree, location and extent of clustering was found to vary for different crash categories, with fatal crashes exhibiting the lowest level of clustering and bicycle crashes exhibiting the highest level of clustering. Temporal variations in clustering were also observed. Overlaying the results with land use and road classification data found that hot spot clusters were in areas with a higher proportion of commercial land use and with a higher proportion of arterial and sub-arterial roads. Further work should investigate network based hot spot analysis and explore the relationship between crash clusters and influencing factors using spatial techniques such as Geographically Weighted Regression.

Upgradation of pavement deterioration models for urban roads by non-hierarchical clustering

Pavements, being a significant component of urban infrastructure, their maintenance and rehabilitation to the desired serviceability level is a challenging problem faced by engineers. The development of a reliable pavement deterioration model is essential to devise proper maintenance policies. This exploratory paper presents the development of network-level pavement performance prediction models for the selected arterial and sub-arterial roads of Tiruchirappalli city, India. Road inventory, traffic volume, maintenance history, pavement condition, and roughness data of the study area are collected periodically for seven years. The Pavement Condition Index (PCI) is determined from the data collected through visual evaluation of the type, severity, and amount of pavement distress. Roughometer is deployed to obtain the International Roughness Index. The parameters which influence pavement deterioration vary widely for different roads within the same network. The pavement sections are assembled into three homogeneous clusters using k-means clustering, which is a nonhierarchical clustering algorithm, so that they can be modeled with better acceptability. Pavement performance prediction models are generated for different clusters using multiple linear regression analysis, and comparison is made with that developed for non-clustered data. The error in prediction is found to be less for clustered models. While the pavement sections in cluster 2, when left unmaintained, deteriorates from a PCI value of 100 to 77 in 5 years, those belonging to cluster 3 are found to deteriorate from 100 to 13. The variation in the deterioration process and the significance of clustering pavement sections for efficient pavement maintenance management is established.

PAHs in road dust of Nanjing Chemical Industry Park, China: chemical composition, sources, and risk assessment

The objectives of the present study were to research the chemical composition of PAHs in PM2.5 of road dust, explore potential sources of PAHs, and assess their carcinogenic risk. Fifty-six road dust samples were collected on the arterial and sub-arterial roads at Nanjing Chemical Industry Park during the sampling periods of autumn and winter. A resuspension system in the laboratory was used to simulate the naturally suspended road dust in the environment and collect PM2.5. Ace was not detected, but other PAHs were found. The pollution level of PAHs was 43.66 ± 15.79 mg kg−1; and 4-ring PAHs, which accounted for 35.14% of PAHs, were the main pollutants. The contents of BeP and BghiP were the highest, accounting for 12.23% and 12.06% of PAHs, respectively. The PAHs concentrations were found to be higher in winter due to the physicochemical characteristics of PAHs and the meteorological conditions. The sequence of PAHs concentrations was: sub-arterial road in winter > arterial road in winter > arterial road in autumn > sub-arterial road in autumn. Traffic emission and industrial sources led to higher PAHs concentrations on the arterial roads in autumn. Meteorological conditions and road characteristics, such as vehicular speed, frequency of road dust sweeping, and road width, led to higher PAHs concentrations on the sub-arterial roads in winter. Principal component analysis (PCA) and the ratios of Ant/(Ant + Phe), Flu/(Flu + Pyr), InP/(InP + BP), and BaA/(BaA + Chr) were used to distinguish the PAHs sources, which indicated fossil fuel combustion, traffic emissions, and petroleum exhaust as the main PAHs sources. The application of the ILCR model for PAHs in road dust showed a higher carcinogenic risk for children and adults (6.01 × 10−5 and 5.80 × 10−5, respectively) on the sub-arterial roads in winter, indicating a high potential carcinogenic risk at the Chemical Industrial Park.

Study on Design Parameters Setting for the Jug-handle-type Far-leading Intersection

The left-turn traffic on the sub-arterial road at the intersection has a greater impact on the intersection traffic, the collision of vehicles can be reduced and the efficiency of the intersection will be improved by setting the Jug-handle-type far-leading (JHTFL) on the left-turn traffic flow through the sub-arterial road. In this paper, the applicable conditions and traffic flow organization method of the horizontal JHTFL intersection is analysed. Taking the minimum delay as the goal, several calculation models of the key geometric parameters are built, such as the length of the speed-change lane in front the ramp entrance, the distance between the ramp entrance and the main intersection, the queue length of the far-leading vehicles on the ramp and the length of the ramp, etc. The calculation methods for the delay and capacity of the JHTFL intersection are also presented. The feasibility of the above methods is verified by an example. Under certain conditions, we can find the left-turning traffic flow at the intersections can effectively reduce the number of signal phases and the average delay of the vehicle through the simulation. The results indicate the horizontal JHTFL intersection method has a good application value for optimizing the design of urban intersections.

PAEs occurrence and sources in road dust and soil in/around parks in May in Tianjin, China

This is the first study reporting the presence of six phthalic acid esters (PAEs) in 45 composite soil and road dust samples collected in the urban zone of Tianjin, China. Three sample types (one soil and two road dust) were collected from the city parks. Soil samples (SI) were obtained from inside the park, road dust samples (RDI) were gathered from inside the park roads and the others (RDA) from roads surrounding parks. The range of concentrations of ∑6PAEs in SI, RDI and RDA were 0.07–0.92μgg−1, 0.42–6.32μgg−1 and 0.40–7.54μgg−1, respectively. The highest SI ∑6PAEs concentration (0.92μgg−1 in The People's Park) was 13 times higher than that of the lowest content (0.07μgg−1 in XiLiu Park). Furthermore, the spatial distribution of PAEs in RDI showed higher contents in the Nankai and Hexi districts. PAEs concentrations in different types of roads displayed significant differences (P < 0.05). The RDA PAEs distribution expressed decreasing order for different types of roads such as arterial road > sub-arterial road > branch road. The results of nonparametric tests on ∑6PAEs revealed significant differences between every two different sample types (P < 0.05). The analysis of the six PAEs types indicated DnBP and DEHP were the primary contaminating compounds in all sample types. The PCA results showed cosmetics and personal care products were important sources of PAEs in SI, and plasticizers were the key sources of PAEs in RDI and RDA.

Traffic Congestion Modelling Based on Origin and Destination

This study attempts to make use of traffic behaviour on the aggregate level to estimate congestion on urban arterial and sub-arterial roads of a city exhibiting heterogeneous traffic conditions by breaking the route into independent segments and approximating the origin-destination based traffic flow behaviour of the segments. The expected travel time in making a trip is modelled against sectional traffic characteristics (flow and speed) at origin and destination points of road segments, and roadway and segment traffic characteristics such as diversion routes are also tried in accounting for travel time. Predicted travel time is then used along with free flow time to determine the state of congestion on the segments using a congestion index (CI). A development of this kind may help in understanding traffic and congestion behaviour practically using easily accessible inputs, limited only to the nodes, and help in improving road network planning and management.

Why do three-wheelers carrying schoolchildren suffer very low fatal crashes?

This paper investigates the possible causes of low fatalities in three-wheelers (autorickshaw) carrying schoolchildren in India. The data was collected in the form of First Information Report (FIR) from local police stations from 2007 to 2012 and video-graphic surveys were done on four arterial roads running through Ludhiana, Punjab, India. Surveys were also done on one subarterial road near school zone which was used by three-wheelers carrying schoolchildren. The objective of the study was to investigate the hypothesis that drivers behave differently while following or overtaking three-wheelers carrying children. Many researchers have investigated the effect of passengers on the driver of the same vehicle, but there was no evidence of any study which investigated the effect of child passengers on nearby vehicles. It was found that heavy vehicles maintain more gaps while following or overtaking three-wheelers carrying children as compared to those not carrying children. It was also found that this effect is more prominent at speeds higher than 40km/h. On the other hand lighter vehicles keep the highest lateral and longitudinal gaps to heavy vehicles and three-wheelers without children respectively.

Solutions to Traffic Jam on East Road of Beijing Jiaotong University in Rush Hours Based on Analogue Simulation

Based on the simulation theory and method, this paper establishes a status analogue simulation model in peak hours, realizes an effective assessment on the road, finds out bottlenecks to improve the level of road services and puts forward the corresponding road improvement program. This paper simulates the im- provement program by the use of VISSIM simulation model, and verifies the improvement effect of four pro- grams and carries out promotion. The research obtains an effective method of solving the problem of jam on the sub-arterial road: It needs to set up by-pass and control over traffic flow of the by-pass, and give full play to the role of by-pass in city.

Efficiency differences of roadside greenbelts with three configurations in removing coarse particles (PM10): A street scale investigation in Wuhan, China

While vegetation in street canyons may improve air quality by removing pollutants, it may also worsen air quality by inhibiting street ventilation. In this study, the isolated effects of roadside greenbelts on footpath air quality were investigated by measuring the coarse particles (PM10) removal efficiency of roadside greenbelts with three different vegetation structures in different grade roads. Results indicated that the three kinds of greenbelts can improve footpath air quality to a certain degree (7–15%). Interestingly, the vegetation structure of shrubs and small trees (about 2–4.5m in height) with small crown diameter shows the highest PM10 removal efficiency along major or heavy traffic roads. The stratified vegetation structure with trees, shrubs and grass is optimal for sub-arterial road or medium traffic roads as these plants can produce multiple ecological effects and create esthetic pleasant landscapes. For branch roads, a parallel tree stand can bring a cost-effective effect. Results of linear regression analysis and gray relational analysis (GRA) show that the removal percentage has significant negative correlation with the shelterbelt porosity (R2=0.83), and relative humidity has a more significant effect (γ=0.68) on the PM10 removal percentage than temperature (γ=0.51) or wind speed (γ=0.63).

Koala mortality on roads in south-east Queensland: the koala speed-zone trial

In 1995, the Queensland Parks and Wildlife Service, the Queensland Department of Main Roads and Redland Shire Council initiated the Koala Speed Zone Trial in the Koala Coast, south-east Queensland. The aim of the trial was to assess the effect of differential speed signs on the number of koalas (Phascolarctos cinereus) hit by vehicles in the Koala Coast from 1995 to 1999. On the basis of information collected by the Queensland Parks and Wildlife Service 1407 koalas were hit by vehicles in the Koala Coast during the five-year study (mean 281 koalas per year, range 251–315). Monitoring of vehicle speeds by the Queensland Department of Main Roads suggested that there was no significant reduction in vehicle speed during the trial period from August to December. Consequently, there was no evidence to suggest that a reduction in the number of koalas hit by vehicles occurred during the trial. Approximately 70% of koalas were hit on arterial and sub-arterial roads and approximately 83% did not survive. The location of each koala hit was recorded and the signed speed limit of the road was noted. Most koalas that were hit by vehicles were young healthy males. Pooling of data on koala collisions and road speed limits suggested that the proportion of koalas that survived being hit by vehicles was slightly higher on roads with lower speed limits. However, vehicle speed was not the only factor that affected the number of koalas hit by vehicles. It is suggested that habitat destruction, koala density and traffic volume also contribute to road-associated koala mortality in the Koala Coast.