Recent Advancements in Sustainable and Safe Transportation Infrastructure - Vol. 2

Annually, road accidents kill thousands of children and youngsters. Road safety around the school proximity zones is a critical issue due to the high traffic volume combined with vulnerable pedestrians who cross the road. The current study aims to conduct a road safety evaluation of four different school zones located at sub-arterials and collector streets in Chandigarh city. The safety analysis and crossing risk assessment were evaluated using safety indices like the Crossing Opportunity Index and Star Rating. To identify the areas at risk, road sections in these zones were rated out of five stars using ViDa’s International Road Assessment Programme (iRAP). A star rating of ‘1’ was generated for one school and between ‘2 and 3’ for two schools under study, indicating a severe case of unsafe pedestrian crossings and high-risk zones. Headway distributions, time gap, pedestrian reaction time, and conflicting speed were used as predictors for the crossing index, which ranged between 35 and 45% for morning and evening school hours. The index suggested fewer opportunities for crossing and a lack of pedestrian-friendly infrastructure. Certain suggestive measures were proposed to increase the star rating, reduce the hazards, and make road crossing safer for children and other pedestrians.

Road safety has become an utmost concern in the Indian context, prompting a comprehensive investigation into the matter within the populous urban center of Nagpur. In the year 2022, Nagpur encountered an alarming tally of 3268 road accidents, tragically resulting in an excess of 1000 fatalities and over 2000 injuries. Of particular note, a significant portion of these incidents involved two-wheelers, accentuating the critical need for targeted interventions addressing this distinct class of road users. This research endeavors to meticulously analyze the multifaceted determinants underpinning road accidents and data analysis. To realize this objective, an intricate methodology was deployed, centered around geospatial analysis and the discerning technique of kernel density estimation for calculation of Road Safety Risk Index. By adopting this approach, the identification and cartographic delineation of precarious zones within the urban road network were facilitated, thereby illuminating the spatial dispersion of accidents. The strategic utilization of geo-mapping and spatial analytical methodologies culminated in a holistic comprehension of the unsafe road matrix, thereby affording pivotal insights into the epicenters where accidents were markedly concentrated. Moreover, the research ingeniously established a Road Safety Risk Index encompassing all links, achieved through a weighted severity analysis (crash rate, exposure, probability, and consequences of accidents). The ramifications of this research conspicuously underscore the relevance of spatial analysis in comprehending the intricate dynamics of road safety, particularly concerning two-wheeler accidents. In summation, this research substantially contributes to the discourse surrounding road safety in India, with a specific emphasis on the exigent challenge of two-wheeler accidents in Nagpur.

This study aimed to evaluate how different interactions among categories of vehicles affect critical values for near-crash events indicators under heterogeneous traffic. The authors used a semi-automatic tool to extract the trajectories and speeds of various vehicle types. This research thoroughly examined the interaction profiles using surrogate indicators, such as time-to-collision (TTC) and post-encroachment time (PET) within heterogeneous traffic conditions. It was discovered that critical values obtained from different vehicle combinations varied significantly. This research enhances the understanding of the complexities inherent in heterogeneous traffic and emphasizes the significance of considering vehicle types when evaluating infrastructure and establishing safety standards. Prominently, greater attention should be given to vehicles with higher risk factors.

This paper presents an investigation to assess the risks of road accidents due to visual field occlusions. The experimental arena considered ground-mounted traffic signs and various occluding agents, such as larger vehicles and median/roadside plants. Repeated field trials at horizontal curves and straight sections revealed that city buses/commercial vehicles in urban streets cause significant occlusions, resulting in a considerable deficit between the available and required legibility distances. The current investigation noted that such a deficit often exceeds 50% at curves, even if occluded vehicles move at operating speeds. However, the values are primarily on the lower sides of straight sections due to brevity in target signs and lesser occlusion in the visual field. Roadside plants often create vegetation shades, further exacerbating visual field occlusion. The study, thus, indicates the need for future research to comprehensively investigate such visual field occlusions, particularly on roads with mixed-mode traffic.

With growing pedestrian fatalities worldwide, the study highlights the necessity of implementing initiatives to enhance road user behaviour. The objective of the study is to explore the idea of the traffic safety culture of pedestrians. To systematically review the studies in the domain of traffic safety culture of pedestrians, this study follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Various databases, such as Google Scholar, Scopus, and TRID, were used to obtain a total of 22 articles. Type of study, types of data analysis methods, and factors associated with the traffic safety culture of pedestrians were addressed. In 64% of the studies conducted in the past five years, age, gender, and pedestrian behaviour were the key factors identified. The research advocated for a cultural shift to reduce pedestrian-related deaths. In conclusion, directions for future research have been discussed that can aid researchers working in the domain of pedestrian traffic safety culture.

The paper presents a comprehensive study on road traffic accidents (RTAs) in the Trivandrum district of Kerala, India, emphasizing the high incidence of fatalities and injuries, particularly on National and State Highways. The study utilizes Geographic Information System (GIS) technology to analyze spatial and temporal patterns of RTAs, employing Kernel Density Estimation (KDE) to identify accident as Blackspots, in the Thiruvananthapuram district. The study spans three years, from 2020 to 2022. It includes detailed crash data, including collision types, accident severity, weather conditions, road types, and junctions, revealing insights such as the prevalence of head-to-head collisions and the influence on accident rates. The Severity Index (SI) is introduced as a metric to quantify accident gravity. The research aims to identify blackspots for improving safety measures, ultimately contributing to the well-being of road users in Kerala. The findings underscore the urgent need for targeted road safety measures and infrastructure improvements to mitigate the risk of RTAs.

Mixed traffic flow observed in Indian conditions is characterized by diverse behavior exhibited by different categories of vehicles. This study focuses on analyzing the forced gap behavior of vehicles at unsignalized three-legged intersections under a mixed traffic scenario. A vehicle from a minor street entering a major street causes the major street vehicle to suddenly reduce its speed. This gap created in the higher-priority stream due to the aggressive behavior of the lower-priority stream is termed forced gap behavior. The objective of this study is to analyze the forced gap behavior of vehicles at unsignalized three-legged intersections for different conditions, such as T-intersection and intersections with speed hump, and at locations with different geometrics, such as intersections at a valley curve and a horizontal curve. The speed reduction threshold value to characterize forced gap behavior is also compared for each of these scenarios. This study also quantifies the influence of speed bumps on minor road approaches on the forced gap behavior.

Pedestrian-vehicle conflicts at signalized intersections are on the rise due to the swift expansion of road traffic in emerging nations like India. The present study assessed pedestrian conflicts with permissive right-turning vehicles at signalized intersections by analyzing the interaction between right-turning vehicles and pedestrians using the traffic conflict technique (TCT). The Surrogate Safety Measure (SSM) parameters, i.e., post-encroachment time (PET) and time to collision (TTC) were used to analyze the possible pedestrian-vehicle conflicts. In that context, data was acquired from five different three-legged and four-legged intersections of Nagpur and Indore cities. Threshold values of PET and TTC were proposed using clustering analysis and depending on those values, the crash severity levels were divided into critical, high, medium, and low. The proposed severity levels will be useful to rank the severity of conflicts at the crosswalks and hence access the safety of signalized intersections.

Urbanization is a global phenomenon propelled by economic growth and improved access to essential services such as education and healthcare. However, this trend often leads to increased road traffic and system inefficiencies, particularly in densely populated urban areas. Nagpur city in India faces significant challenges related to roadside friction, especially near hospitals and commercial areas where street parking is prevalent. This study aims to analyze the impact of roadside friction on traffic characteristics in Nagpur. Factors such as on-street parking, street vendors, pedestrians, and kerb-side bus stops contribute to reduced space for vehicles, slower speeds, and hindered traffic flow, resulting in longer travel times and decreased efficiency. Regression analysis reveals an inverse relationship between frictional elements and speed, with temporary bottlenecks and friction width identified as significant factors exacerbating the effects of roadside friction. Addressing this issue through measures such as expanding off-street parking, controlling the number of vendors, and improving bus stop laybys can enhance the accessibility and efficiency of Nagpur's road network. This study underscores the importance of mitigating roadside friction to optimize urban transportation systems and improve overall urban livability.

The study examines the pedestrian crossing facilities near urban roundabouts in Bhopal, Madhya Pradesh, India. Ordered logistic regression model results found that qualitative variables were more impactful in determining the difficulty of pedestrian crossings. With an 8.56% rise in the zebra crossing's directness, a 6.46% improvement in traffic volume safety, a 7.37% reduction in crossing latency, and a 10% reduction in pedestrian crossing difficulty were seen. The results also indicate that increasing pedestrian facilities would help with crossing challenges since pedestrians feel more at ease crossing when there is more space between cars and less traffic at roundabouts.

In India, diverse traffic flows are common with mixed vehicle types and no dedicated lanes. Urban areas suffer from poor lane discipline as vehicles interact both longitudinally and laterally, affecting traffic flow and service levels. This study in Nagpur city examined factors affecting lateral gap: velocity, road width, vehicle combination, and level of service (LOS). Peak-hour video graphics surveys on various roads were conducted, and regression analysis showed significant impacts of vehicle type, speed, road width, and traffic conditions on lateral gaps. The lateral gap increases with the speed and reduces with poor LOS. Mixed vehicle pair combinations had the smallest gap, while CAR-CAR had the largest. The gap increases with the road width.

Currently, traffic safety on urban roads is a global concern, heavily influenced by pedestrian behavior. Pedestrian safety is particularly pronounced in India due to mixed traffic conditions. Pedestrians, the most vulnerable road users, primarily encounter vehicles when crossing roads. Pedestrians must be able to accurately assess oncoming vehicle speed so that they can cross the road safely. So, the main objective is to study the various factors influencing pedestrian speed misestimation in mixed traffic conditions. We conducted a field study to collect pedestrian speed estimates at two midblock sections in Bhubaneswar city, India. The pedestrians are asked to estimate the vehicle speed before the vehicle passes them. The various factors, like pedestrian age, gender, and crossing from the kerb or median, were collected during the experiment. The results show that the pedestrians tended to underestimate speed rather than overestimate it or estimate it accurately. Approximately 62.33% of pedestrians underestimate vehicle speeds, while 36.46% overestimate them, with only a 1.21% accurate estimate. When the pedestrians estimated the speed of vehicles, they were more inclined to underestimate higher speeds (>35 kmph) and overestimate lower speeds (<20 kmph). Female pedestrians and pedestrians crossing from the median have a higher average under estimation of 9.95 and 7.68 kmph, respectively, compared to male pedestrians and pedestrians crossing from the kerb at 5.65 and 6.17 kmph, respectively. Pedestrians of age group ≤ 20 years are underestimating intensity (11.31 kmph), followed by 31–40, > 40, and 21–30 years as 9.10, 8.52, and 5.27 kmph, respectively.

The Indian transportation landscape is unique, characterized by its non-laned traffic, a diverse mix of vehicles ranging from Motorized Two-wheelers(M2W), Motorized Three-wheelers (Auto-rickshaws), Cars, Light Commercial Vehicles (LCV), Buses, Trucks and Multi-Axle Trucks (MAT), and the spontaneous behavior of drivers. In response to India's rapid socio-economic advancement and urbanization, the nation has seen a significant increase in vehicle capacity. Urbanization rose from 23.10% in 1980 to 35.87% in 2022 [10], which reflects India's status as one of the world's fastest-growing countries. This urban population surge has led to more complex traffic behaviors, presenting both challenges and opportunities for traffic management. Existing systems fall short in handling this diversity and dynamism, leading to exacerbated traffic congestion, heightened accident rates, and inefficiencies in traffic management. Therein lies the necessity for an innovative solution that can not only comprehend but also predict and streamline the flow of vehicles. The rapid advancements in computer vision and artificial intelligence technologies have paved the way for novel approaches to tackle these issues. Introducing a transformative approach that leverages Unmanned Aerial Vehicles (UAVs) and cutting-edge deep learning models to pioneer a real-time vehicle detection and classification system tailored to the idiosyncrasies of Indian traffic conditions. Our study leverages You Only Look Once 8 (YOLOv8) for enhancing vehicle detection and classification within Indian traffic contexts, using a UAV-captured dataset with over 400 thousand annotations to train the model. This paper proposes an accurate, efficient, and real-time vehicle detection network based on the successful YOLOv8 object detection model. YOLOv8 model to the UAV dataset resulted in a mean average precision (mAP@0.5) of 0.756 and an F1 score of 0.86 across all vehicle classes. Compared to its predecessors, YOLOv8 demonstrated superior performance, advancing precision, recall, and overall accuracy for vehicle detection in India's complex traffic scenarios.

Signalized Midblock crosswalk (SMC) is a location where pedestrian and vehicular flows are segregated by a traffic signal. The present paper aims to model the pedestrian crossing time at SMC under mixed traffic conditions. The proposed crossing time was developed by considering the bidirectional effect of pedestrians at SMC. Eight SMC from Hyderabad (India) were selected for the study. The delay that occurred due to the bidirectional effect is termed as frictional delay in this paper and the total crossing time of pedestrians was modeled as the sum of ideal crossing time (length of the crosswalk/15th percentile speed of pedestrians) and frictional delay. The final crossing time model was validated with the internal data and external data using Key Performance Indicators (KPI) like RMSE, MAPE, NSE, and RSR. Results revealed that the proposed model is accurate in estimating the pedestrians crossing time at SMC. The developed crossing time model can be a useful tool for designers and planners in estimating the crossing time at SMC and further designing the facilities.

The study investigates the influence of vehicle breakdowns on urban traffic flow, focusing specifically on incidents occurring mid-block on roads in New Delhi. Primary data were collected to assess traffic volume, vehicle composition, speed, delays, and other flow characteristics. This data was utilized to create a simulation model using VISSIM, which was then calibrated and validated to estimate the impact of vehicle breakdowns. The impact was measured in terms of changes in speed, traffic volume, and the extent of disruption in both distance and time. Simulation results indicate that breakdowns on a 2-lane road significantly affect speed more than those on a 3-lane road. Additionally, the percentage change in traffic volume is notably greater on 2-lane roads compared to 3-lane roads. This suggests that mid-block breakdowns on two-lane roads result in more severe traffic volume reductions, particularly at Location-2.

Headway between vehicles influences the traffic speed and capacity of highway. In a mixed traffic stream, slow, and fast-moving vehicles frequently interact even under low volume conditions which cause variation in the headway maintained by the vehicles. The aim of this study is to understand the different headway characteristics of mixed traffic stream on Indian highways. Further, the research work intends to determine accurate traffic capacity by analyzing the traffic flow characteristics such as dynamic passenger car units (DPCU), traffic speed, flow, and density for each class of vehicle. A set of field data from the National Highways (NH) in Tamil Nadu was collected using the Infra-red sensors. The results reveal that there is a strong association between the micro parameter of traffic flow, the headway, and the capacity of flow expressed in DPCUs. The results from this research work are useful in design, management, and control, of NHs and aid transport engineers, and other agencies to plan the highways.

This paper presents an adaptive traffic control system using dynamical system equations to optimize signal timings at traffic intersections. Its primary responsibility is to adjust traffic signal timings according to the prevailing traffic flow conditions. These adjustments typically occur in a cyclic manner. By MATLAB simulations, we are able to determine throughput and represent the output of a traffic control system by modeling the behavior and interactions of various components within the system.

Rapid Urbanization in developing countries is leading to increased congestion and degradation of the environment in metropolitan areas, and Two-wheelers (TW) are contributing substantially to this aspect. TW are becoming popular because they are compact and can weave through traffic easily. On the other hand, TW are more vulnerable because of their direct exposure to the traffic. As per the MoRTH (2022) report, nearly 50% of the accidents on the road are due to TW. In this context, the present study investigates the driving behaviour of TW under Naturalistic Driving conditions. The study aims to understand the impact of road features on TW driving behaviour by selecting 3 different stretches based on their geometric characteristics in Hyderabad City, India. Racelogic Performance Box has been used for the data collection. Various parameters like road geometrics and acceleration and deceleration profiles of the driver have been extracted. Later, the data was analyzed to understand the relationship between velocity and acceleration at various parts of the road sections like curved sections and intersections. In this process, different machine-learning models have been tested. Route 1 with a straight stretch, a linear relationship between velocity and acceleration has been observed with an R2 of 0.8. For Route 2 with curved sections and Route 3 with a combination of curved sections and intersections, the decision tree algorithm was performing well with an R2 of 0.9. As road geometrical elements have a substantial impact on TW driving behaviour and very limited work was reported in the literature the novelty of this study emphasizes on analyzing the impact of these geometrical elements on TW driving behaviour. By exploring the complex relationship between driver behaviour and road environment, the study outcomes can provide insights to policymakers and highway designers for safer design strategies.

Visibility and average velocity are interrelated aspects that impact safety, traffic flow, environmental impact, driver well-being, and regulatory compliance in driving and transportation. Optimizing road safety and efficiency requires skillfully balancing these aspects. We developed a new car-following model to study the impact of visibility and average velocity information on traffic flow. The “headway-sensitivity” phase analysis reveals that the stable zone continues to grow as visibility decreases and more attention is paid to the average velocity information of the transportation ahead. The “kink-antikink” solution of the “mKdV equation”, related to the visibility and driver’s attention effects, is derived by nonlinear analysis. Numerical simulation is conducted to validate the theoretical findings. As visibility decreases, traffic flow becomes increasingly stable. Low visibility negatively impacts traffic flow because traffic current becomes down with less visibility, but if the driver gets more information about the number of vehicles ahead, then the stability increases with less visibility.

Driver’s sensory-motor abilities, particularly in perceiving visual and audio signals, reaction and motor times, significantly impact road safety. Advanced Driver Assistance Systems (ADAS), powered by Artificial Intelligence (AI), emerging as a transformative tool in aiding drivers and enhancing safety. This study emphasizes the importance of understanding these abilities, advocating for a thorough investigation using the tools of Vienna Test System (VTS). Collected data from 51 professional drivers aged 29–42 years, with driving experience ranging from 0 to 11 years, the study rigorously analyzed the influence of driver’s demographic factors on sensory-motor proficiency. Positive significant correlations were observed between age and education level with sensory-motor skills, while driving experience exhibited an inverse significant relationship. A linear regression model was developed and validated, achieving an impressive accuracy rate of 96.3% in categorizing drivers based on their sensory-motor abilities. A significant proportion of drivers (72.55%) exhibited superior sensory perception, indicating potential for effective ADAS utilization and reduced collision risks. This study underscores the pivotal role of demographic attributes in shaping driver’s sensory-motor capabilities and influencing road safety. By leveraging these insights, policymakers and stakeholders can devise targeted interventions to promote safer driving behavior and mitigate risks associated with road crashes, ultimately fostering safer road environments for all road users.

Urban traffic congestion is a growing problem in cities worldwide, leading to significant economic losses, environmental impacts, and commuter frustration. This study investigates traffic flow dynamics at Palanpur Aroma Circle, a critical intersection in Palanpur, Gujarat, India, experiencing severe congestion. We employ data-driven microscopic simulation using SUMO (Simulation of Urban Mobility) to analyze the relationships between traffic volume, road geometry, and speed, and their combined effects on congestion. Real-world traffic data for volume, speed, and road geometry is collected and integrated into the SUMO model. The calibrated model is then used to assess traffic flow efficiency under various scenarios, including baseline conditions and those with modified traffic volumes, road geometry changes, and speed limit adjustments. Statistical analysis and scenario comparisons are conducted to identify the root causes of congestion and evaluate the effectiveness of potential mitigation strategies. This study aims to provide valuable insights for developing data-driven solutions to improve traffic flow and alleviate congestion at Palanpur Aroma Circle and similar intersections in urban areas.

Microscopic traffic simulation models are high accuracy techniques as they simulate individual vehicle movement to evaluate different traffic management strategies effectively and efficiently. The present study attempted to propose traffic management plans that maximizes the use of existing infrastructure to address traffic congestion at Connaught Place, New Delhi. The relevant data has been collected, namely traffic volume at intersections, signal timings, road network details with lane configuration, and speed and delay to develop microscopic traffic simulation model. This comprehensive data set was used to build simulation model using VISSIM 5.40 software. From the validation, it was found that developed simulation model is able to predict the vehicular movements with a Mean Absolute Percentage (MAP) Error of about 6% in traffic volume and about 0.21% in travel time, thus demonstrating the appropriateness of developed simulation model. Utilizing the developed simulation model, two short-term traffic management plans (TMPs) targeting signal-free control at intersections, namely with pedestrian signal and without pedestrian signal (installation of FOBs) along with road geometric improvements. The estimated results show that TMP incorporating pedestrian signal plan, reduced average stopped delay by 74%, travel time by 36%, and journey speed increased by 57%. Whereas, the signal-free circulation plan without pedestrian signal option yielded a reduction in average stopped delay by 93%, travel time by 50%, and journey speed increased by 102%. These results suggest traffic management plans (TMPs) with signal-free control at intersections would yield substantial benefits for overall traffic flow at Connaught Place, New Delhi area.

The key parameters influencing the performance of heterogeneous traffic flow in urban environments. Heterogeneous traffic, characterized by the simultaneous presence of diverse vehicle types, presents unique challenges that require a nuanced understanding of various performance metrics. The study explores microscopic and macroscopic factors affecting the efficiency, safety, and overall functionality of heterogeneous traffic. From the perspective of different vehicles, including traditional automobiles, bicycles, pedestrians, and emerging technologies, this review delves into the critical parameters shaping the dynamics of heterogeneous traffic. By synthesizing current research findings and methodologies, the paper aims to contribute to a deeper comprehension of the performance parameters that are instrumental in enhancing the effectiveness and sustainability of urban mobility systems.

In India, traffic conditions are complex in nature as mixed traffic condition prevails with lane indiscipline. Thus, the behavior of a driver is highly unpredictable and depends on the vehicle condition, passenger, and road condition. The lateral movement of vehicles is a very common phenomenon due to lane indiscipline. Vertical curves of the road are mainly designed to accommodate variations in the alignment’s grade. On vertical curves due to frequent acceleration and deceleration of the vehicles, it becomes difficult to estimate the lateral movement and speed characteristics of the vehicle. Thus, the study of driver’s behavior on vertical curves is necessary for enhancing the geometry of the curve and reducing the number of accidents. The present study seeks to determine the speed and lateral movement characteristics of vehicles and analyze the driver’s behavior on a vertical curve road geometry having a combination of both summit and valley curves. Also, the variation in lateral shift and heading angle for different vehicle category and their relation with longitudinal speed was explored. For the same, videographic data was collected using drones at two sites in Nagpur, Maharashtra. The result showed that the side friction has an impact on lateral movement and speed reduction. Thus, the study suggests that while designing vertical curves, the lateral movement of vehicles and the impact of side friction along with speed reduction needs to be taken into consideration. This will lead to improvement in the capacity and lane discipline of the vehicles on roads.

In order to carry out economic analysis to assess the operating conditions of existing or upgradation of road infrastructure, the fundamental speed, flow and density relationships are essentially required to estimate roadway capacity. In this direction, the simulation models would help in assessing these fundamental characteristics under different traffic conditions, but calibration and validation is essentially required using observed data. In view of this, the objectives have been conceived to develop microscopic traffic simulation model to estimate heterogeneous vehicle movements on different types of roads varying from single lane to eight lane divided. Further, development of speed, flow and density relationships also proposed. Accordingly, FLoMiTSiM, a microscopic traffic simulation which was developed for homogeneous traffic conditions on urban roads is considered in the present study to customize to analyze vehicular movements under heterogeneous traffic conditions on inter-city roads. The validation results from the comparison of simulation and observed data revealed that developed simulation model is able to predict the vehicle movements realistically. Using the simulation data, the speed-flow-density equations have been developed for different types of roads. The roadway capacity and jam density values have also been estimated which very close to Indo HCM study. The outcome of the study is going to be useful for the authorities who plan and execute the road construction works to take appropriate decision while improving travel operations on the inter-city roads.

Lane changing behavior is one of the fundamental driving behaviors seen in heterogeneous traffic conditions. The present study aims to analyze and model the path changing behavior of drivers, which is the microscopic version of lane changing behavior, at signalized intersections under the influence of access flows. For this, video-graphic survey was done for data collection from five four-legged intersection approaches in Kerala, followed by data extraction and analysis. Factors influencing the path change were identified by performing descriptive and inferential statistical analysis after the quantification of path change and included in the model. The choice of path change was modelled using binary logistic regression with clearance available, access type of vehicle and through type of vehicle as independent variables. The outcome of this study has potential application in microsimulation, intersection safety improvement and infrastructure planning.

The current study examines the impact of primary influencing variables, such as traffic volume, speed, and distance of receiver from the noise source, on the traffic noise level in the vicinity of road intersections in a mid-sized city. For the study objectives, separate arm analysis is conducted utilizing 342 h of data collected at nineteen intersections in Kanpur, India. For this study, signalized and unsignalized intersections in Kanpur were selected for data collection. However, non-compliance with rules at signalized intersections results in traffic flow characteristics similar to those at unsignalized intersections. The study finds that the entrance arm equivalent noise level and exit arm equivalent noise level increase by 0.306 dBA and 0.210 dBA, respectively, with 1-unit increase in entrance traffic volume. However, the 1-unit increase in exit arm traffic volume causes 0.458 dBA, and 0.488 dBA increments in entrance and exit arm equivalent noise levels, respectively. The speed has a negative impact and causes 0.735 and 0.995 dBA reduction in entrance and exit arm equivalent noise levels, respectively, with a 5 km/h increase in the exit arm stream speed. Distance of receiver from the source is found to have a negative impact on the noise level. The study illustrates that a 1 m increase in the distance between the source and receiver causes 0.423 dBA and 0.439 dBA reduction in entrance and exit arm equivalent noise levels, respectively.

The biggest source of noise pollution nowadays is traffic noise. The noise from traffic has an impact on the people who live close to the highway. Given the speed at which things are developing, it is imperative to investigate the highway traffic noise concerning the primary causes. Determining the passenger car noise equivalent (PCNE) for each class of vehicle concerning the highway design speed on Indian highways is the primary goal of this study. The term PCNE refers to the number of reference vehicles with noise emission characteristics that are equivalent to a particular vehicle type. Furthermore, the reference energy mean emission level (REMEL) equation has been developed for every vehicle category. Data for four distinct vehicle classes—high commercial vehicles, light commercial vehicles, motorcycles, and automobiles with bituminous pavement—were gathered at four different highways. According to the study, the passenger car noise equivalent (PCNE) value should be used to analyze the traffic noise since it may convert the diverging traffic volume into passenger cars.

This study investigates the start-up loss time at signalized intersections in mixed traffic conditions. Start-up loss time is the delay during the initial phase when the signal turns green, caused by driver reaction time and vehicle acceleration. Analyzing start-up loss time helps understand how different vehicle types affect traffic flow, enabling targeted strategies for reducing delays. This study aims to analyze and understand the factors influencing start-up loss time at signalized intersections in mixed traffic conditions, comparing the differences between three-legged and four-legged intersections. To achieve the aim, the sites were selected in Nagpur city. To analyze the effect of variation in the geometry on start-up loss time, three-legged and four-legged intersections were chosen. Further, the data was collected using a video graphic survey and processed using Kinovea software and pivot tables in Excel. Vehicle movements were tracked in the video using Kinovea software, and the recorded frames were analyzed in Excel. The outcome of the study indicates that while crossing the four-legged intersections, vehicles experience lower start-up loss times than the three-legged intersections due to more direct turning routes.

Pedestrians play a vital role in enhancing safety, health, accessibility, and the liveliness of urban areas, simultaneously diminishing environmental impact and boosting economic growth. Emphasizing pedestrian-friendly infrastructure is key to elevating the overall well-being of communities and nurturing sustainable, inclusive city environments. The objective of this paper is to assess the pedestrian level of service (PLOS) for the intersection link and segment using the methodology outlined in the US Highway Capacity Manual 2016 (HCM 2016) and examine its applicability in India. The PLOS calculated by the IRC 103 and Indo-HCM for sidewalk and crosswalk are also calculated for comparison. To achieve this goal, a site located in Nagpur, Maharashtra, has been chosen as the study location. Considering that other methodologies typically focus on calculating the PLOS for individual components such as sidewalk crosswalks, the US Highway Capacity Manual (US-HCM) provides a comprehensive methodology for evaluating the entire facility, encompassing intersection links and segments. The findings of the study shed light relevance and applicability of US-HCM’s PLOS methodology in the case study area. Further, the findings also highlight the limitations and discuss a way forward for a holistic improvement in the Indian PLOS methodologies for wider acceptability and application.

The capacity of exclusive two-wheeler lanes in India has become a critical topic of interest in recent years as these lanes are gaining popularity as a solution to traffic congestion and accidents. The purpose of this study is to study the capacity of exclusive two-wheeler lanes in Nagpur and identify those factors that affect their capacity. The study employs a combination of field observations, traffic counts, and surveys to determine the capacity of exclusive two-wheeler lanes. It also analyses the factors that affect capacity, such as lane width, and traffic flow characteristics. This study aimed to investigate the capacity of exclusive two-wheeler lanes with varying widths of 2, 2.5, and 3 m in Nagpur city and find that the capacity of exclusive two-wheeler lanes is influenced by various factors, including the width of the lane, the speed of two-wheelers, and the presence of obstacles on the lane. The Kinovea, K-lite Codec, and Excel software were used for data extraction and VISSIM software for microscopic simulation to analyse the capacity. Additionally, the speed limits and design speed were calculated using the cumulative frequency distribution method to find the 15th, 85th, and 98th percentile speeds. The study also identifies the need for proper signage and markings to enhance the capacity of these lanes.