Intersections In City Research Articles

ASSESSMENT OF BLACK SPOTS IN URBAN BHOPAL WITH THE AID OF WEIGHTED SEVERITY INDEX AND KERNAL DENSITY ESTIMATION METHODS

One step toward lowering traffic accidents is identifying the locations of road accident hotspots and the appropriate assessment technique. This study evaluated the effectiveness of kernel density estimation (KDE) and the weighted severity index (WSI) in locating blackspots using the ArcGIS tool. Finding out accident severity levels is necessary to identify the accident-related blackspots. The formula for the WSI method was applied. This study examines five-year traffic accidents in the Bhopal, Madhya Pradesh, city intersection zone of the roads to envisage the appropriateness for the given technique on the basis of availability, consistency, and type of the data. This study designates five typical road network intersection zones as blackspot sites based on the criterion. This study's general conclusion is that, during the years 2017 to 2019, Govindpura Turning in Bhopal is a highly accident-prone area, and point density estimation is preferable to kernel density estimation for this purpose. Additionally, this study found that between 2015 and 2017, high-traffic accidents in Sukhisewaniya's Balampur Ghati were more likely to occur in intersection zones with a large number of legs. This study suggests that point density estimation be used to investigate high number of traffic accident areas by looking into blackspot locations at the macroscopic level of road networks. Furthermore, it is necessary to evaluate the effectiveness of the designated blackspot site and suggest corrective measures that reduce the number of accidents and their consequences.

Assessment of index-based traffic noise annoyance level at major road intersections in a tourist city: A case study towards environmental sustainability

Urban noise pollution poses significant challenges to public health and environmental sustainability, particularly in rapidly developing tourist destinations. Noise pollution and associated annoyance level in five major intersections of Cox's Bazar City, Bangladesh, was assessed in this study during the peak tourist season. Noise measurements were conducted using various indices (L10, Leq, and TNI) across morning, midday, and afternoon time slots. TNI scores were compared with Mean Dissatisfaction Score (MDS) standards to assess traffic-induced noise annoyance levels. Additionally, a survey of 675 respondents was conducted to assess their perceptions of noise pollution. Statistical analyses included linear regression for noise indices, multinomial logistic regression for TNI-related dissatisfaction, and ordinal logistic regression for respondents' perceived annoyances. Results revealed significant noise pollution issues, with Leq scores consistently exceeding national guidelines across all intersections and time periods, particularly on weekends during afternoon timeslots. TNI values frequently surpassed standard dissatisfaction regulations, with 19 out of 105 time slots exhibiting extreme dissatisfaction levels. Link Road and Kolatoli Circle intersections consistently showed higher noise levels and dissatisfaction. Over 95% of survey respondents perceived increased noise pollution during peak tourist seasons, with 87.11% describing it as "extremely" or "very" noisy. Longer exposure duration and awareness of health risks were significantly associated with reported perceived annoyance levels. Respondents reported various health impacts, including annoyance (84.44%), headaches (62.37%), and cognitive impairment (44.44%). This comprehensive study provides valuable insights for policymakers, city planners, and environmentalists to develop sustainable urban strategies that balance the acoustic environment with the well-being of residents and tourists alike.

Exploring the Intersection of Film, City, and Tourism

Exploring the Intersection of Film, City, and Tourism

A LiDAR-Based Digital Twinning Workflow for Traffic Monitoring and Simulation

Abstract. The process of ensuring efficient and safe urban transportation is closely linked to urban planning, particularly through the aspects of transportation planning. Transportation planning is a pivotal concern for urban regions worldwide, reflecting the growing need to increase mobility while ensuring safety and sustainability in densely populated areas. This research focuses on developing a novel digital-twin-based approach for micro-traffic simulation to support data-driven decision-making for increasing traffic safety through scenario planning. Leveraging the traffic data obtained through monitoring one of the busiest intersections in Sofia city, this research workflow shows the effective integration of LiDAR data and the urban digital twin concept in intelligent transportation systems (ITS). The research addresses problems related to moving object classification, trajectory analysis, and reclassification of unrecognised objects by processing the LiDAR data, pre-processed in a .osef format, thereby transforming it to make it suitable for simulation. The proposed solution for the monitoring of urban traffic is demonstrated by the usage of SUMO (Simulation of Urban MObility) for performing simulations and a Random Forest model for unrecognized object reclassification to pre-existing vehicles and pedestrian classes. The architecture of the proposed workflow can possibly be applied in other similar urban settings, providing a scalable solution for both traffic management and urban planning. The study’s results support the wider use of urban digital twin principles in ITS by highlighting the value of advanced modelling tools and high-quality data in addressing today's urban transportation challenges.

Assessing and Implementing Efficient Queuing Methods to Address Traffic Congestion at Shekhi-Choli Intersection in Erbil City

Queuing theory is the best way for estimating waiting lines for many phenomena in different fields. Queuing models are used to make decisions on determining the traffic flow in order to avoid congestions in the streets; therefore, it is a useful tool for resolving these issues, which is the objective of this paper. The intersection of Shekhi-Choli in Erbil was undertaken to determine the appropriate queuing models for incoming street lines at the intersection, as well as to solve the problem of a constrained queuing line with excessive wait durations. This intersection is important because it connects three roads that provide access to and from Erbil's big bazaar. Data were obtained from the chosen intersection for 12 days from 3 to 5 PM daily. EasyFit software version 5.4 and TORA software version 2 were used to analyze the data. The primary performance metrics were identified, and optimal queuing models were chosen to service drivers. The empirical distribution of automobile arrivals and departures is a Poisson distribution, with traffic intensities of 92%, 88%, and 80% for the first line (Barzani Namr str.), second line (Shekhi Choli str.), and last line (Sultan Muzaffar str.), respectively. Queuing models involve key features, such as population size, queuing discipline (SIRO, LCFS, FCFS, GD), arrival process, waiting process, and service channels. The Shekhi-Choli Intersection's current queuing scheme to service drivers is (M/M/1):(FCFS/∞/∞) model. As a result, the Erbil traffic police division must decide to provide suitable instruction for the first and second lines in order to minimize driver waiting time. To obtain more reliable information and findings, new studies should be conducted on the same site for three periods of time (morning, afternoon, and evening), in addition to other crowded intersections in Erbil city.

Adaptive and dynamic smart traffic light system for efficient management of regular and emergency vehicles at city intersection

Adaptive and dynamic smart traffic light system for efficient management of regular and emergency vehicles at city intersection

Optimizing Traffic Management at Batam City Intersections: Analysis of Congestion Causes and Mitigation Strategies

Kota Batam merupakan salah satu pusat kegiatan ekonomi dan perdagangan di Indonesia yang terus mengalami pertumbuhan pesat, menyebabkan peningkatan lalu lintas yang signifikan di persimpangan kota. Kemacetan lalu lintas menjadi masalah yang meresahkan bagi penduduk dan pengunjung kota tersebut. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor utama yang menyebabkan kemacetan lalu lintas di persimpangan kota Batam serta mengusulkan strategi penanggulangan yang efektif. Metode penelitian yang digunakan meliputi survei lapangan, analisis data lalu lintas, dan wawancara dengan stakeholder terkait. Hasil penelitian menunjukkan bahwa faktor-faktor seperti volume kendaraan yang tinggi, kurangnya koordinasi antara lampu lalu lintas, dan infrastruktur jalan yang kurang memadai menjadi penyebab utama kemacetan lalu lintas di persimpangan kota Batam. Berdasarkan temuan ini, beberapa strategi penanggulangan diusulkan, termasuk peningkatan koordinasi antara pihak terkait, penyesuaian pola lampu lalu lintas, dan pengembangan infrastruktur jalan yang lebih efisien. Implementasi strategi ini diharapkan dapat mengurangi kemacetan lalu lintas dan meningkatkan mobilitas di Kota Batam.

Traffic simulation-emission modelling to evaluate impact of signal cycle on automobile emissions

Vehicular traffic comprises different types of vehicles with varying static and dynamic characteristics, under heterogeneous traffic conditions in India. The continuous growth of vehicles results in high congestion and becoming the main source of air pollution. The reduction in emissions is directly linked to the reduction in traffic congestion. At urban corridors, higher concentration of pollutants is observed near the traffic signals because of the influence of traffic signal operations on vehicular speed. The present research is carried out with the principal objective as the study of the effect of intersection control on emissions in the urban intersection of a metropolitan city. Microscopic traffic simulation models have been used to simulate real traffic conditions, and effectively represent the extensive performance of vehicles associated with speed and acceleration states. The simulation model is revised with optimum signal cycle time considering the signal phase system shows a substantial reduction in automobile emissions.

Research on optimization method for traffic signal control at intersections in smart cities based on adaptive artificial fish swarm algorithm

The transportation environment of smart cities is complex and ever-changing, and traffic flow is influenced by various factors. With the increase of traffic flow in smart cities, optimizing traffic intersection signal control has become an important method to improve traffic efficiency and reduce congestion. To this end, a smart city traffic intersection(SCTI) signal control optimization method based on adaptive artificial fish swarm algorithm was studied. Establish the Equation of state of traffic flow at SCTIs to understand the actual traffic flow at SCTIs. On this basis, design SCTI signal control parameters, with the minimum average delay and average number of stops as objective functions, and construct an optimization model for SCTI signal control. By combining chaotic search theory and adaptively improving the artificial fish swarm algorithm, based on the adaptive artificial fish swarm algorithm, the intelligent city traffic intersection signal control optimization model is solved to achieve intelligent city traffic intersection signal control optimization. The experimental results show that the average delay of this method is 7.8 ms, the average number of stops is 2, and the travel time is 68.4 s s. Thus, it is proved that the method in this paper has a good optimization effect of traffic signal control at smart city intersections, which can improve the optimization efficiency of traffic signal control at smart city intersections and reduce traffic congestion at smart city intersections.

Accidental Survey of Different Intersection of Junagadh City

Abstract: Intersections are known to be high-risk areas for traffic accidents due to the convergence of different streams of traffic. By conducting an accidental survey, identify patterns and common causes of accidents. This study attempts investigation and analysis to prevent accidents at intersection which have high number of accidents. To get an insight into the trend of road accidents we collect last 3 years of accident data of different intersection of Junagadh city from District Traffic Office of Junagadh by taking permission from SP office Junagadh. And selected intersection is “Majevadi gate” Because in last 3 years, maximum number of accidents have occurred at this intersection. To reduce accidents at this intersection, we design a rotary intersection at the Intersection.

A methodology of cooperative driving based on microscopic traffic prediction

We present a methodology of cooperative driving in vehicular traffic, in which for short-time traffic prediction rather than one of the statistical approaches of artificial intelligence (AI), we follow a qualitative different microscopic traffic prediction approach developed recently (Kerner and Klenov, 2022). In the microscopic traffic prediction approach used for the planning of the subject vehicle trajectory, no learning algorithms of AI are applied; instead, microscopic traffic modeling based on the physics of vehicle motion is used. The presented methodology of cooperative driving is devoted to application cases in which microscopic traffic prediction without cooperative driving cannot lead to a successful vehicle control and trajectory planning. For the understanding of the physical features of the methodology of cooperative driving, a traffic city scenario has been numerically studied, in which a subject vehicle, which requires cooperative driving, is an automated vehicle. Based on microscopic traffic prediction, in the methodology first a cooperating vehicle(s) is found; then, motion requirements for the cooperating vehicle(s) and characteristics of automated vehicle control are predicted and used for vehicle motion; to update predicted characteristics of vehicle motion, calculations of the predictions of motion requirements for the cooperating vehicle and automated vehicle control are repeated for each next time instant at which new measured data for current microscopic traffic situation are available. With the use of microscopic traffic simulations, the evaluation of the applicability of this methodology is illustrated for a simple case of unsignalized city intersection, when the automated vehicle wants to turn right from a secondary road onto the priority road.

Signalized intersections and mid-blocks autonomous wireless systems based on level of service (LoS) determination IoT

The study tries to evaluate the effectiveness of different mid-blocks and signalized intersections using Level of Service (LOS) and v/c ratio. The present study attempts to determine the Level of Service (LOS) and v/c ratio at different mid-blocks and signalized intersections. The analysis of the field data collected is done using the empirical formulae provided in INDO HCM 2017 for determination of LOS for mid-blocks and signalized intersections.The study also focuses on computing V/c ratio for mid-block sections chosen in the study to understand the intensity of congestion on the roads. If the v/c ratio is greater than 1, it represents that the demand of the traffic on that road exceeds its capacity.The present study acts as an empirical guide to understand the effectiveness of important mid-blocks and signalized intersections in Hyderabad city as autonomous wireless systems.

ВЛИЯНИЕ ОСТАТОЧНОЙ АВТОТРАНСПОРТНОЙ ОЧЕРЕДИ НА ПРОЦЕСС ДВИЖЕНИЯ АВТОМОБИЛЕЙ НА ГОРОДСКИХ РЕГУЛИРУЕМЫХ ПЕРЕСЕЧЕНИЯХ

This paper continues to investigate methods for separating turning vehicle flows at urban light-controlled intersections. The authors carried out mathematical modelling of the process of left-turn transport queue formation on the basis of existing dependencies, as well as the indicator of "residual motor transport queue". After studying the processes and existing mathematical models describing the formation of a vehicle queue at a light-controlled intersection, as well as modelling of the process depending on the "residual vehicle queue" parameter, we made an assumption about the type of mathematical model describing the process. To confirm the assumptions, we carried out studies of urban light-controlled intersections in Russian cities. Based on passive experiment, it was found that the value of the residual vehicle queue obeyed the exponential distribution law of a random variable. The length of the vehicle queue formed at the intersection depends on the residual vehicle queue parameter. A linear mathematical model describes the dependence. It was found that for an average urban regulated intersection, the required rotary-accumulative lane capacity was 9 and 5 automobiles with loading factor more than and less than 1, respectively. When the residual vehicle queue increases from 5 to 50 vehicles, the size of the vehicle queue at the regulated intersection in the left-turn direction increases in 5 times. The results of the study can be used to adjust the modes of operation of urban light-controlled intersections, as well as to estimate the length of turn-accumulative lanes.

Traffic noise modelling at intersections in mid-sized cities: an artificial neural network approach.

Traffic noise has emerged as one major environmental concern, which is causing a severe impact on the health of urban dwellers. This issue becomes more critical near intersections in mid-sized cities due to poor planning and a lack of noise mitigation strategies. Therefore, the current study develops a precise intersection-specific traffic noise model for mid-sized cities to assess the traffic noise level and to investigate the effect of different noise-influencing variables. This study employs artificial neural network (ANN) approach and utilizes 342h of field data collected at nineteen intersections of Kanpur, India, for model development. The sensitivity analysis illustrates that traffic volume, median width, carriageway width, honking, and receiver distance from the intersection stop line have a prominent effect on the traffic noise level. The study reveals that role of noise-influencing variables varies in the proximity of intersections. For instance, a wider median reduces the noise level at intersections, while the noise level increases within a 50-m distance from intersection stop line. In summary, the present study findings offer valuable insights, providing a foundation for developing an effective managerial action plan to combat traffic noise at intersections in mid-sized cities.

МАТЕМАТИЧЕСКОЕ ОБЕСПЕЧЕНИЕ МОНИТОРИНГА ВЫБРОСОВ ЗАГРЯЗНЯЮЩИХ ВЕЩЕСТВ ОТ АВТОТРАНСПОРТА В ЗОНЕ РЕГУЛИРУЕМОГО ПЕРЕСЕЧЕНИЯ НА ОСНОВЕ НЕЙРОСЕТЕВЫХ АЛГОРИТМОВ

Abstract. In modern cities, environmental issues related to motor transport occupy an increasingly important place in the management system of urban transport flows. Vehicles emit the greatest amount of exhaust gases during sudden changes in traffic modes, which is typical of signalized intersections. Traffic congestion situations also occur more often at intersections, when a large concentration of traffic creates an unfavorable environmental background. To obtain operational information about the parameters of the intensity of traffic flows, the authors used neural network algorithms for recognizing vehicles from video streams received from stationary street surveillance cameras at city intersections. An optimized algorithm for the operation of a trained neural network (YOLOv4) allows for extracting and interpreting data on traffic flow parameters in real time. As part of the study, the developed mathematical models made it possible to implement real-time monitoring of the amount and concentration of pollutants from vehicles in the controlled intersection zone. The calculation of the amount of pollutants released into the atmosphere from transport is carried out taking into account the average speed, type of vehicle and idle time in the measurement area. An appropriate software system can serve as a basis for predicting the difficulty levels and environmental risks of various atypical traffic situations.

Application of graph theory and webster method in traffic light settings at the tulip intersection in kefamenanu city

Application of graph theory and webster method in traffic light settings at the tulip intersection in kefamenanu city

Reducing Data Requirements for Simple and Effective Noise Mapping: A Case Study of Noise Mapping Using Computational Methods and GIS for the Raebareli City Intersection

The accurate prediction of noise levels at outdoor locations requires detailed data of the noise sources and terrain parameters and an efficient model for prediction. However, the possibility of predicting noise with reasonable accuracy using less input data is a challenge and needs to be studied scientifically. The qualities of the noise data, terrain parameters, and prediction model can impact the accuracy of the prediction significantly. This study primarily focuses on the dependency of noise data for efficient noise prediction and mapping. This research article proposes a detailed methodology to predict and map the noise and exposure levels in Ratapur, Uttar Pradesh, India, with various granularities of noise data inputs. The noise levels were measured at various places and at different times of the day at 10 min intervals. Different data input proportions and qualities were used for noise prediction, namely, (1) a large data-based method, (2) a small data-based method, (3) a source point average data-based method, (4) a Google navigation data-based method, and (5) accurate modelling using an ANN-based method, integrating accurate noise data with a sophisticated modelling algorithm for noise prediction. The analysis of the variation between the predicted and measured noise levels was conducted for all five of the methods using the ANOVA technique. Various methods based on less noise data methods predicted the noise levels with accuracies within the ±4–10 dB(A) range, while the ANN-based technique predicted it with an accuracy of ±0.5–2.5 dB(A). Interestingly, the estimation of the noise exposure levels (>85 dB(A)) and the identification of hazard zones around the studied road intersection could also be performed efficiently even when using the data-deficient models. This paper also showcased the possibility of predicting an accurate 3D map for an area by extracting vehicles and terrain features from satellite images without any direct recording of noise data. This paper thus demonstrated approaches to reduce the noise data dependency for noise prediction and mapping and to enable accurate noise-hazard zonation mapping.

Construction stability analysis of intersection tunnel in city under CRD method

The construction of city intersection tunnels cause multiple redistribution of surrounding rock stress, resulting in the engineering disasters such as instability in existing tunnels and collapses of ground buildings. To mitigate formation disturbances effectively, the Center Cross Diagram (CRD) method is employed in city tunnel construction. In this study, a numerical model for a city intersection tunnel is developed based on an underground circular roads project in Chongqing, China, to analyze the safety of the tunnel structure and the stability of ground buildings under the CRD method. The numerical simulation results obtain that the excavation of pilot-tunnel ➃ will reduce the surrounding rock stress and control the rock strata subsidence, and reveal that the excavation of pilot-tunnel ➃ is the key step of CRD method. The maximum compressive stress and tensile stress of surrounding rock first increase and then decrease during the excavation of pilot-tunnels ➀, ➁, ➂, and ➃. Simultaneously, the deformation of the ground building experiences a slow initial increase followed by a rapid rise before stabilizing. Furthermore, the excavation of the main tunnel leads to an increase of 0.73, 0.35, and 0.52 times in the vault subsidence value, left haunch convergence value, and right haunch convergence value of branch tunnel #1, respectively. Finally, the convergence process of branch tunnel #1 is discussed through the in-situ monitoring, which is divided into three stages: rapid deformation, deceleration deformation, and stable deformation. The final horizontal convergence value and subsidence value of cross-section K0+360 are respectively 84% and 78% of those at cross-section K0+395.

Analysis of the economic benefits of an appraisal of an intersection

AbstractEthiopia's government proposes paving existing roads or building modern intersections in cities to reduce maintenance costs. An unimproved signalized intersection at 6° 51′ 47.9″ N and 37° 45′ 50.1″ E is selected for this research. Cost-benefit analysis is used to evaluate the proposed innovative approach to designing and implementing an intersection and to compare whether the new road projects will have an adequate return. This research suggests converting the current intersection into a signalized roundabout to calm traffic. Signalized roundabouts have a higher net present value and a modified internal rate of return than improved signalized crossing intersections. Considering the country's high inflation rate, three scenarios recommend using a signalized roundabout.

Examining traffic crash scene using density estimation and its relevance to determine intersection zone road network blackspot location

Identifying road traffic crash blackspot locations and the proper method of assessment is a step towards reducing traffic crashes. The objective of this study was assessing the pertinence of the point density estimation and kernel density estimation in identifying blackspot locations using the ArcGIS tool. Based on the availability, consistency, and nature of the data this study considers five-year traffic crashes of Budapest city intersection zone of the road network to envision the aptness of the stated method. To address the goal, this study considers the minimum spacing between intersection to define the radius of output cell size (0.001093 degree) and its neighborhood radius (0.002 degree). Based on the above parameter this study identifies five common intersection zones of the road network as blackspot locations. The overall inference of this study; point density estimation is more desirable than kernel density estimation for identifying highly extreme dense blackspot locations. Furthermore, this study discovered that intersection zones with an enormous number of legs are more likely to experience high traffic crashes. This study recommends that point density estimation is capable of investigating blackspot location at macroscopic level of road network to analyze highly extreme dense traffic crash location. In addition to that, it is advisable to assess the performance of the stated blackspot location and propose remedial action to minimize the rate of road traffic crashes and its outcome.