Stretch Of Road Research Articles

Characterization of Classified Indian Reclaimed Asphalt Pavement RAP Aggregate Impact Value and Aggregate Abrasion Value of Rap Aggregates

Reuse of existing deteriorated bituminous pavement material in construction and maintenance of flexible pavement is called recycling of bituminous pavement. Removed and reprocessed deteriorated pavement material which is recycled is termed as Reclaimed asphalt pavement (RAP). In India during construction of flexible pavement different types of bituminous layers are in practice depending upon CBR of sub-grade and traffic count i.e. CVPD of the road stretch. Depending upon types of bituminous layer i.e. PC Seal Coat, Bituminous Macadam(BM), Dense grade bituminous Macadam (DBM), Semi Dense Bituminous Concrete (SDBC) or Bituminous Concrete(BC) Reclaimed Asphalt Pavement can classified in different groups These classified RAP groups materials will have different characteristics i.e. Rap aggregates and Recovered bitumen of different group of RAP will have different characteristics. In this study characterization of RAP limited to Aggregate Impact Value (AIV) and Aggregate Abrasion Value (AAV)of RAP aggregates of RAP classified in different groups. Results of this study will be compared to standard value of AIV and AAV required for bituminous construction to predict that RAP aggregates are suitable or not for use in bituminous mixes.

Prioritization of Black Spots in Hilly Road Segment using Road Engineering Data

Road accidents are one of the causes of disability, injury and death. As per the latest road accident data released by the Ministry of Road Transport & Highways (MoRTH), the total number of accidents increased by 2.5 percent from 4,89,400 in 2014 to 5,01,423 in 2015. The analysis reveals that about 1,374 accidents and 400 deaths take place every day. Every single year, it has been estimated that over three lakh persons die and 10-15 million persons are injured in road accidents throughout the world. According to the analyses, statistics of global accident indicate that in developing countries, the rate of fatality per licensed vehicle is very high as compared to that of industrialized countries. A road stretch of about 500 metres in length in which either ten fatalities or five road accidents (involving grievous injuries/fatalities) took place during last three calendar years, on National Highways is considered as a road accident black spot according to MoRTH, Government of India. In the present study the identified black spots of Haridwar and Dehradun city were included comprising of a total of 81 black spots out of which there were 49 black spots which were identified in Dehradun followed by 32 black spots in Haridwar. The present study was an attempt to carry out the prioritization of these identified blackspots with respect to the factors that were considered to evaluate accident prone locations on the road. The identified black spots were then prioritized using the classification scheme (ranking from low to high).The study reveals that the advantage of using this approach for prioritizing accident black spots on roads is that it requires very less additional data other than the road network maps.

A Model for Pavement Characteristic Deflection for Rural Roads in Himachal Pradesh

Structural Evaluation of pavements is essential to assess the structural strength of different layers of pavement. It also helps in determining the remaining life of a pavement and the thickness of overlay required. Surface Deflection is the structural response that is easy to measure and hence, commonly used parameter in structural evaluation. In the present study, an attempt has been made to develop a relationship between surface deflection and various structural parameters of pavements selected on low volume flexible rural roads in Himachal Pradesh. Benkelman Beam has been used to determine characteristic deflection on selected 12 rural road stretches in Shimla and Solan district of Himachal Pradesh. Because the conduction of Benkelman Beam Deflection (BBD) test is costly and difficult to carry out in the region of Himachal Pradesh due to hilly and narrow rural roads leading to disruption of traffic, hence, models have been developed to predict surface deflection value using Soaked CBR, Un-soaked CBR, Average Annual Daily Traffic (AADT) and Age of pavement from last overlay (in years). Another model has also been developed to estimate surface deflection using K-value, AADT and age of pavement. Multiple models have been developed using linear regression model. The various developed models have been studied, compared and best model is suggested supporting better coefficient of determination value and root mean square error (RMSE).

IRI Performance Models for Flexible Pavements in Two-Lane Roads until First Maintenance and/or Rehabilitation Work

Pavement performance models play a vital role in any pavement management system. The Regional Government of Biscay (RGB) (Spain) manages a 1200 km road network and conducts pavement data collections, including the International Roughness Index (IRI) values. The aim of the paper is to develop an IRI performance model for two-lane roads with flexible pavement until the first maintenance and/or rehabilitation activity is performed. Due to the huge amount of available information, a deterministic model was selected. A literature review of deterministic models showed that, apart from age and traffic volumes, the pavement structure is a key factor. Therefore, it was decided to analyze the only road stretches whose entire pavement section was known (surface layer + base + subbase). Various variables related to age, traffic volumes and employed materials were introduced as possible factors. The multiple linear regression model with the highest coefficient of determination and all the variables significant included the real pavement age, the cumulated heavy traffic and the total thickness of bituminous layers. As the material employed in the surface layer could affect roughness progression, a qualitative variable was introduced to consider various surface materials. The model improved its accuracy, indicating that the surface layer material is also an influencing factor on IRI evolution.

Roadkill of medium to large mammals along a Brazilian road (BR-262) in Southeastern Brazil: spatial distribution and seasonal variation

ABSTRACT Like all human action that changes ecosystems, roads contribute to habitat fragmentation, acting as barriers and, consequently, causing biodiversity loss. Given the need for studies related to roadkill of wild animals, especially in the Atlantic Forest, and the vulnerability of mammal species to roadkill on the roads, we analyzed roadkill data of medium and large mammals. The study was carried out in a 100 km stretch of the BR-262 road, Atlantic Forest biome, in the Espírito Santo state. We obtained roadkill mammals’ carcasses by 42 monitoring campaigns, between January 2017 and January 2018. We recorded 259 carcasses of 22 species, which resulted in a roadkill rate of 0.062 mammal/km/day. We found that roadkill rates are higher in rainy months and lower in dry ones. We found support that three variables best predicted roadkill occurrence in the BR-262 road (i.e. positive relationship with forest cover, and accumulated precipitation ‘rainfall’, and negative relationship with speed reducers). These results indicate an alarming impact on the mammalian fauna at the site and reinforce the need for management measures and actions to reduce the mortality of wild mammals on the roads.

A spatial model for the assessment of debris flow susceptibility along the Kodaikkanal-Palani traffic corridor

Debris flow is one of the most destructive water related mass movements that affects the development of mountain terrains. A reliable assessment of debris flow susceptibility requires adequate data, but in most developing countries like India, there is a dearth of such extensive scientific records. This study presents a novel approach for assessing debris flow using the analytical network process (ANP) in data insufficient regions. A stretch of hill road between Kumburvayal and Vadakaunchi along the Kodaikkanal-Palani Traffic Corridor (M171) was considered for this study. Five significant factors including the nature of slope forming materials, hydraulic conductivity, slope, vegetation, and drainage density were identified from intense field surveys and inspections in order to assess the susceptibility of the terrain to debris flow. This model endorsed the inter-dependencies between the selected factors. The resulting debris flow susceptibility map delineated regions highly prone to debris flow occurrences, which constituted nearly 23% of the selected road stretch.

Area Occupancy-Based Adaptive Density Estimation for Mixed Road Traffic

Managing congestion in mixed traffic conditions, characterized by heterogeneous and lane-less traffic, is a challenging task. Traditionally density, defined as the number of vehicles in a road stretch, is used to quantify congestion. However, direct measurement of density is difficult and hence is usually estimated from other variables. In this paper, a relationship is derived between traffic density and area occupancy, a variable that can incorporate heterogeneity and lane-less movement. Using the derived density-area occupancy relation, a non-continuum macroscopic single state linear time varying model was developed. Estimation of density was done by using the Kalman filtering technique and corroborated with simulated density. The need for dynamic estimation is motivated by evaluating the performance of two static estimation schemes in the presence of uncertainties. Performance was tested for different traffic scenarios such as congestion and non-recurrent traffic incidents. Further, to improve the estimation accuracy in scenarios involving transitions in traffic conditions, an adaptive estimator was developed. It was found that the adaptive estimator provided the best estimation accuracy.

Optimization-Based On-Road Path Planning for Articulated Vehicles

Maneuvering an articulated vehicle on narrow road stretches is often a challenging task for a human driver. Unless the vehicle is accurately steered, parts of the vehicle's bodies may exceed its assigned drive lane, resulting in an increased risk of collision with surrounding traffic. In this work, an optimization-based path-planning algorithm is proposed targeting on-road driving scenarios for articulated vehicles composed of a tractor and a trailer. To this end, we model the tractor-trailer vehicle in a road-aligned coordinate frame suited for on-road planning. Based on driving heuristics, a set of different optimization objectives is proposed, with the overall goal of designing a path planner that computes paths which minimize the off-track of the vehicle bodies swept area, while remaining on the road and avoiding collision with obstacles. The proposed optimization-based path-planning algorithm, together with the different optimization objectives, is evaluated and analyzed in simulations on a set of complicated and practically relevant on-road planning scenarios using the most challenging tractor-trailer dimensions.

Model Based Control of Mixed Traffic Based on Area Occupancy

Regulation of heterogeneous traffic is a challenging task on urban roads, particularly those where traffic congestion is routinely encountered. In this paper, a model based traffic signal control scheme via state feedback controller is presented. An original contribution of this study is the use of area occupancy as the measurement variable, which is apt for characterising heterogeneous and lane less traffic. An adaptive Kalman filter is used to estimate traffic density. The developed control scheme was implemented on a road stretch simulated in VISSIM, a commercial microscopic traffic simulation software, and interfaced with MATLAB using VISSIM COM interface. The implementation was shown to satisfy the objective of maintaining the desired density in the study stretch which demonstrated the effectiveness of the developed control scheme.

Effect of modes of transportation on commuters' exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in Chennai, India

Daily commuting increases level of contaminants inhaled by urban community and it is influenced by mode and time of commuting. In this study, the commuters’ exposure to ambient particulate matter (PM2.5) and nitrogen dioxide (NO2) was assessed during three modes of travel in six different road stretches of Chennai. The mean distance of road stretches was 25 km and the exposure to pollutants was assessed during peak hours and off-peak hours. The average travel duration was in the range of 39 to 91 min in motorbike, 83 to 140 min in car and 110 to 161 min in bus. Though there was variation on exposure to concentration in modes of transportation, the maximum exposure concentration of PM2.5 was observed as 709 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 29 μg/m<sup>3</sup> in closed car. Similarly, the maximum exposure concentration of NO2 was observed to be 312 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 21 μg/m<sup>3</sup> in car. The concentration of elements in PM2.5 was in the order of Si > Na > Ca > Al ≥ K > S ≥ Cd, with Si and Cd concentration as 60% and < 1% of the PM2.5 concentration.

What influences road mortality rates of eastern grey kangaroos in a semi-rural area?

BackgroundRoads have major ecological impacts on wildlife. Vehicle collisions most frequently impact large herbivores due to their larger home range compared to smaller animals, and higher population density compared to carnivores. Kangaroos (Macropus spp.) account for a large proportion of reported wildlife vehicle collisions that occur in N S W, Australia. We aimed to evaluate what influenced road mortality of eastern grey kangaroos (Macropus giganteus) in a temperate rural/suburban region. The location of roadkilled kangaroos found on or near two 1 km stretches of road in Richmond NSW was recorded throughout 2014 and 2015. Weather and moon phase data were recorded for the date of each roadkilled kangaroo. Transects were setup on both roads, and multiple road and landscape features, including the width of roadside, fence construction, habitat type, and distance from street lights measured at 50 m intervals. Data were analyzed to explore which landscape features and temporal factors influenced the occurrence of a roadkill hotspot.ResultsMore kangaroo road mortalities occurred during periods of low temperature and low rainfall, and these factors are likely to affect forage quality. Fewer mortalities occurred when rain was falling. A greater number of mortalities occurred during the waning gibbous phase of the lunar cycle. Significantly more road mortalities occurred a short distance from the end of a section of street lights.ConclusionsThe findings suggest that illumination influences the likelihood of kangaroo road mortalities. Large herbivores are particularly sensitive to habitat fragmentation because they need unrestricted access to large continuous habitat. Knowledge of factors that influence where and when kangaroos are most likely to cross roads can be used to inform more targeted management strategies and improve future road design and habitat connectivity to reduce the incidence of wildlife vehicle collisions.

Evaluating the Carbon Sequestration Performance of Three Selected Street Tree Species in Urban Setting: Colombo, Sri Lanka

Street trees are one of the most important components of urban green space in reducing the impacts of air pollution, providing shade, controlling noise pollution, arresting soil erosion and increasing aesthetics.With current interest of anthropogenic CO2 emissions through various activities in urban areas can be offset through increasing carbon sequestration by using appropriate street tree species.The role of urban street trees in CO2 sequestration potential is still remain uncertain in Sri Lanka due to absence of proper selection mechanism.The objective of this study is to derive and validate allometric equation to predict stem carbon accumulation by three selected street tree species; Madhuca longifolia (Mee), Cassia fistula (Ehala) and Pongamia pinnata (Karanda). Three species belong to different age groups with various characteristics of the tree crown, foliage, trunk, and roots within and between the species but the climatic condition is considered as similar in the sampling area due to the same meteorological station the area assigned. Tree parameters; dbh, total height, crown height and crown diameter were measured and C sequestration performance was tested in the laboratory using loss on ignition method for 60 individual trees from each three species. Streets were purposely sampled based on high abundance of species and trees were randomly sampled as 10 trees within 2 km road stretch. Stepwise regression model construction was carried out and validated with Model Bias (MB) and Modelling Efficiency (ME). Stem carbon content of M. longifolia is ln Cc=-4.59+3.471 ln dbh, C. fistula is ln Cc=-5.100+3.187 ln dbh and P. pinnata is ln Cc=-5.708+3.055 ln dbh with the reliability of 66%, 90% and 80% respectively. The model was fitted to the reserved data to be proved to use in the real world to predict carbon performance.Keywords: Carbon, Sequestration, Tree, Allometric equation

Spatio-Temporal Analysis of Road Accident Incidents and Delineation of Hotspots Using Geospatial Tools in Thrissur District, Kerala, India

Accidents are distressing experiences which affect physical, psychological, and social welfare of clans. Road accident fatalities are increasing in Kerala due to the traffic congestions and increase in both population and number of vehicles. The present study investigates the spatial and temporal patterns of the road accidents from 2013 to 2015 in Thrissur district, Kerala using geospatial technology. Assessment of spatio-temporal clustering of road accidents was carried out using Moran’s I method of spatial autocorrelation, Getis-Ord Gi* hotspot analysis, and Kernel density functions. The year wise total accidents show a clustered pattern, whereas the spatio-temporal breakup of events shows random and clustered distribution in certain classes. The continuous road stretches and isolated zones of hotspots and cold spots were delineated by the Kernel density surface using the results of Getis-Ord Gi* hotspots analysis. Four major road segments such as National highway near Kodungallur to Althara stretch, Thrissur town to Perumpilav stretch via Kunnamangalam, Thrissur town to Vadanappally segment, and Guruvayur to kunnamangalam stretch are identified as highly clustered accident hotspots. The results of this study can be effectively used by local self-governments, police departments, as well as national agencies for implementing better road safety policies in the accident hotspots stretches.

Recycled Asphalt as an Alternative to Natural Aggregates for Forest Road Reinforcement

The objective of the present paper is to confirm or reject the possible use of recycled asphalt to reinforce forest haul roads regarding the technical requirements set by the standards and directives relevant to the construction of forest road surfaces. The hypothesis is based on the presumption that recycled materials, if correctly used, can reach the same construction properties as standard materials, hence their application does not have a negative effect on reinforcement quality. On a selected stretch of forest road, three test sections were constructed with the use of recycled asphalt, however, each of them with a different technological solution. The first section was reinforced with unbound mixture – Type1 without added water, the second section was constructed using a version of vibrated macadam technology, and recycled asphalt was applied to the third section by the method of basic compacting. In each of the sections, tacheometric cross profile measurement was carried out at monthly intervals to monitor the changes in the cross profile shape, and the number of passages of fully loaded logging trucks was registered; static load tests were performed at pre-defined time intervals to determine the deformation moduli such as deformation characteristics of the road surface structural layers. In all three reinforcement versions, the values of deformation moduli observed during the static load tests were between 68–90 % of the values set by relevant standards for these technologies using natural aggregates. However, the tacheometric measurements did not reveal statistically significant changes in the shape of the reinforcement cross-section. Based on the obtained results, applying recycled asphalt to reinforce forest roads seems to be a suitable alternative to natural quarry aggregate used in unbound structural layers. Recycled material needs to meet the regulatory limits for foreign elements and pass ecotoxicity tests, which is evidenced by a certificate on material compliance issued by the test laboratory.

Factors Affecting Traffic Management using Two Step Cluster

The concept of traffic congestion and traffic management is ambiguous in nature. The traffic and congestion is dependent on a number of factors that might impact the stretch of road or the framework of the traffic management systems. As the evolution of internet in last one decade and its reach to the very last person on this planet, this provides the basket of new opportunity of managing the traffic and its patterns on the basis of live traffic data from the onsite cameras, sensors, and the google maps traffic forecast the situation of traffic congestion would be avoided, which directly helps in reducing the load on environment and saving some valuable time of the commuters, and indirectly having large savings on the countries resources. In this research paper the authors have identified the factors affecting the management, flow, and working of traffic on the toll roads, national highways, and dedicated fright corridors in specific from the literature. The identified factors have been analyzed using quantitative statistical tools such as: relative importance index, Cronbach’s alpha, and cluster analysis to know the predictor importance. For this study a total of 192 valid responses were received using structured questionnaire survey. On the basis of data analysis the recommendation have be drawn and shared with the government authorities to be implemented on the highways to facilitate the commuters and all the other stakeholders associated with the traffic and traffic management. The findings of the relative importance index conclude that the most significant attributes of traffic management are No tolling for e-vehicles, use of information boards to avoid any traffic situations, and savings on fuels. Furthermore the findings of the cluster analysis concludes that the most important predictor is no-tolling for e-vehicles, followed by savings on fuels.

Understanding the group process in the first year of psychotherapy: the walk, the basic assumptions and the challenges of young adults

This article aims to explore the dynamics of a small psychotherapy group, whose members, all young adults, began to wait for each other at the end of the sessions to walk down a stretch of road before going their separate ways. Clinical material selected from some sessions of the first year of the therapy is presented and commented on. From the possible meanings attributed to the walk, the authors highlight the group process characterized by the oscillation between the basic assumption of fight-flight and that of dependency. The work shows that the group’s walk becomes, from attack to clinician, to creation of a transitional area where it is possible to experience being a young adult.

Thermal Mapping in Flat Lowlands and Undulating Uplands – A Comparison of Results

Thermal mapping has been known as a reliable technique to analyse and even predict road surface temperature in a stretch of road, rather than just a single point (e.g. road weather station location). The method itself was developed in the 1980s, and as time progressed, the technique was improved and has become more applicable. Due to other methods, such as climate modelling, becoming widely accessible and more affordable to apply, thermal mapping started being pushed out to the background as an expensive alternative. The idea for this paper arose from thermal mapping applications to Lithuanian roads that produced inconclusive results in some research areas and raised the question of whether this technique applies to flatlands as effectively as to uplands. The Czech Republic was chosen as a country with an available database and environmentally different road network. Several stretches of road thermal mapping data were analysed and compared. It was concluded, that in flat landscapes altitude has lesser predictability value for road surface temperature than in undulating uplands. In addition, thermal mapping results appear to be more inconclusive in flatlands, compared to uplands. Nevertheless, thermal mapping is a good and reliable method for determining cold spots.

Reliable corridor level travel time estimation using probe vehicle data

ABSTRACT Travel time information assists road users in making informed travel decisions such as mode choice, route choice and/or time of travel. This study explores the use of GPS data from buses and Wi-Fi and Bluetooth data from a sample of vehicles, for accurate estimation of the travel time of all vehicles on the roadway. A 5.5 km road stretch in Chennai city was selected as study stretch and data were collected for a week’s period. The present study develops models using linear regression and artificial neural network (ANN) techniquesFto estimate stream travel time using bus travel time obtained from GPS. ANN performed better compared to the linear regression for all sizes of segments. Most of the Indian cities have an integrated network of buses traveling on most of the road segments with on-board tracking devices, making this a useful development for real-time travel time estimation.

Where will it cross next? Optimal management of road collision risk for otters in Italy

Collisions with vehicles represent the main conflict between infrastructures and wildlife, causing damages to both humans and animals. As to the latter, road mortality is a growing phenomenon and the largest single cause of death for many vertebrates. When focusing on endangered species, the Eurasian otter (Lutra lutra) is among the most vulnerable to road-kills, which represent the predominant cause of deaths recorded in Europe. We propose a large scale spatially-explicit assessment of road-kill risk for the Eurasian otter in Italy as a tool to identify road stretches at high collision risk, thus optimizing the location of mitigation measures. The modelling approach was produced for South Central Italy, hosting the only remnant viable population of otters in Italy. We used a maximum entropy approach including 56 road collision events recorded between 2004 and 2016 through a citizen science initiative, along with seven environmental predictors measured on 1 km grid cells. Four predictors were selected to describe roads characteristics, i.e. density of highways, and of state, regional and local roads. The remaining three variables referred to the quality of otter habitat in the surrounding of the collision sites, i.e. elevation, density of freshwater bodies, and a measure of landscape heterogeneity calculated on land-cover categories. The model achieved a good predictive accuracy (AUC > 0.8; Boyce index > 0.8). The collision probability was mostly affected by elevation, density of state roads, and density of freshwater bodies. Specifically, collision risk was higher in areas at low elevation and medium density of state roads located near rivers and wetlands. In addition, model predictions evidenced that implementing mitigation measures along 10% of road network in the study area could have potentially hampered ca. 50% of otter casualties recorded during the study period.

Bat (Mammalia: Chiroptera) road casualties in the Kresna Gorge, Bulgaria

The Kresna Gorge is a biodiversity hotspot with high conservation value not only for Bulgaria, but the Balkan Peninsula. In the gorge region, many rare, endemic, and protected species and habitats are found (Hubenov 2012). Since the beginning of the 21st century, several road and highway projects have threatened the ecological prosperity of this area. Intensive chiropterological research in the last 25 years (beginning in 1993) has revealed that the Kresna Gorge is an area of great importance for bats, providing habitats for more than 50% of the 33 species present in Bulgaria (Petrov 2001). There is growing evidence that roads negatively affect bats' populations (Altringham and Kerth 2016). Theoretical studies have shown that in some situations, collisions might lead to population decline (see references in Altringham and Kerth 2016). Identifying parts of the road where bats experience collisions more frequently can have strong conservation implications. Between 2013 and 2016 we recorded roadkilled bats on a weekly basis, from March to October. We monitored a 16 km section of a high-traffic intensity road passing through the Kresna Gorge. We recorded 78 dead bats on the road, belonging to 10 species. During our survey, we recorded Myotis brandtii (Eversmann, 1845), a new species for the bat fauna of the Kresna Gorge. The presence of two species, Nyctalus leisleri (Kuhl, 1817) and Miniopterus schreibersii (Kuhl, 1817), previously with single or doubtful records, were confirmed. Statistically significant hotspots of roadkill were modelled using Getis-Ord Gi statistic. We identified five road stretches as hotspots for bat accidents. They are all relatively close to bridges, tunnel exits, and/or bat roosts. Оur study adds new data on the bats' species composition in the gorge, as well as it demonstrates that road elements in this section of the Pan-European Corridor IV concentrate and increase road accidents with bats.