Total Number Of Vehicles Research Articles

Multi-level traffic-responsive tilt camera surveillance through predictive correlated online learning

In urban traffic management, the primary challenge of dynamically and efficiently monitoring traffic conditions is compounded by the insufficient utilization of thousands of surveillance cameras along the intelligent transportation system. This paper introduces the multi-level Traffic-responsive Tilt Camera surveillance system (TTC-X), a novel framework designed for dynamic and efficient monitoring and management of traffic in urban networks. By leveraging widely deployed pan–tilt-cameras (PTCs), TTC-X overcomes the limitations of a fixed field of view in traditional surveillance systems by providing mobilized and 360-degree coverage. The innovation of TTC-X lies in the integration of advanced machine learning modules, including a detector–predictor–controller structure, with a novel Predictive Correlated Online Learning (PiCOL) methodology and the Spatial–Temporal Graph Predictor (STGP) for real-time traffic estimation and PTC control. The TTC-X is tested and evaluated under three experimental scenarios (e.g., maximum traffic flow capture, dynamic route planning, traffic state estimation) based on a simulation environment calibrated using real-world traffic data in Brooklyn, New York. The experimental results showed that TTC-X captured over 60% total number of vehicles at the network level, dynamically adjusted its route recommendation in reaction to unexpected full-lane closure events, and reconstructed link-level traffic states with best MAE less than 1.25 vehicle/hour. Demonstrating scalability, cost-efficiency, and adaptability, TTC-X emerges as a powerful solution for urban traffic management in both cyber–physical and real-world environments.

Transportation Arrangement as a Basic Plan for Politeknik Negeri Medan to Become an Environmentally Friendly Campus

A green campus becomes one of the approaches to overcoming global warming. The green campus evaluation program currently being conducted by Universitas Indonesia is the UI GreenMetric World University Rankings, and one of the categories is transportation. One of the main contributors to pollution levels and carbon emissions is the transportation sector and is potentially to continue to rise unless sustainable prevention efforts are made. With its limited area, Politeknik Negeri Medan needs a more effective transportation arrangement to make it an environmentally friendly campus. Greenmetric assessments are conducted on existing conditions referring to the UI GreenMetric World University Rankings 2023 Guidelines with several criteria, namely the total number of vehicles (cars and motorcycles) divided by total campus population, shuttle services, zero emission vehicles (ZEV) policy on campus, the total number of zero emission vehicles (ZEV) divided by total campus population, ratio of ground parking area to total campus area, program to limit or decrease the parking area on campus for the last 3 years (from 2020 to 2022), number of initiatives to decrease private vehicles on campus, and pedestrian path on campus. The scoring result in the existing conditions is 725, or only about 40.3% of the total maximum value. GreenMetric scoring will increase to 1250 or 69.4% by implementing solutions for transportation arrangements in Politeknik Negeri Medan. The solutions are the use of access cards to filter unauthorized vehicles into the campus area, providing official vehicles electric cars and bicycles for use in the campus area, reducing the ground parking by making a vertical parking, utilizing buses as shuttle facilities for the academic community around the campus with a certain radius to reduce the use of private vehicles and supplementing existing pedestrian paths according to standards of safety, comfort and disability-friendly aspects by adding handrails, roof covers, directions, ramps for disabilities.

Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forcasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran)

Air pollution is one of the major concerns for the population and the environment due to its hazardous effects. PM10 has affected significant scientific and regulatory interest because of its strong correlation with chronic health such as respiratory illnesses, lung cancer, and asthma. Forcasting air quality and assessing the health impacts of the air pollutants like particulate matter is crucial for protecting public health.This study incorporated weather, traffic, green space information, and time parameters, to forcst the AQI and PM10. Traffic data plays a critical role in predicting air pollution, as it significantly influences them. Therefore, including traffic data in the ANN model is necessary and valuable. Green spaces also affect air quality, and their inclusion in neural network models can improve predictive accuracy. The key factors influencing the AQI are the two-day lag time, the proximity of a park to the AQI monitoring station, the average distance between each park and AQI monitoring stations, and the air temperature. In addition, the average distance between each park, the number of parks, seasonal variations, and the total number of vehicles are the primary determinants affecting PM10.The straightforward effective Multilayer Perceptron Artificial Neural Network (MLP-ANN) demonstrated correlation coefficients (R) of 0.82 and 0.93 when forcasting AQI and PM10, respectively. This study also used the forcasted PM10 values from the ANN model to assess the health effects of elevated air pollution. The results indicate that elevated levels of PM10 can increase the likelihood of respiratory symptoms. Among children, there is a higher prevalence of bronchitis, while among adults, the incidence of chronic bronchitis is higher. It was estimated that the attributable proportions for children and adults were 6.87% and 9.72%, respectively. These results underscore the importance of monitoring air quality and taking action to reduce pollution to safeguard public health.

Optimization of scheduling scheme for self-driving vehicles by simulation algorithm.

As a new logistics technology, self-driving electric vehicles not only improve freight efficiency but also promote energy saving and emissions reductions. Aiming at logistics technologies based on self-driving electric vehicles, planning the vehicle scheduling scheme as a whole reduces energy consumption and improves economic and environmental benefits. Targeting an actual freight problem based on a two-way single-lane road connecting the pickup and delivery points and including electric charging stations, this paper proposes a method for optimizing the scheduling scenario and parameters of self-driving vehicles through computer simulations. An optimization model based on dynamic programming is established, and an optimization simulation algorithm is designed to solve the model, effectively solving the overall planning problem of vehicle scheduling. The experimental results show that the model and algorithm have good universality. After specifying an appropriate road length, total number of vehicles, number of spare vehicle batteries, duration of freight transportation, and other necessary information, the simulation algorithm is executed and the optimal scheduling scheme and the total amount of freight transported are output. The efficiency of the algorithm is extremely high, requiring only 1.5 s to complete the whole simulation process of scheduling 150 vehicles for 1000 h over a road with a length of 10 km.

Accident Detection Using Raspberry Pi

Abstract: It is observed that, the major hindrance on road is due to heavy traffic flow during peak hours especially when people commute to work. The total number of vehicles or objects exceeds its capacity by causing a blockage for emergency vehicles such as fire fighter and rescue vehicles, furthermore wastage of fuels adds more to the environmental pollution which is not adoptable for a country’s economic growth. In order to develop an efficient, reliable, cleaner and safer mode of transportation,it is necessary to make the road transportation system automated as much as pos- sible.To track the vehicle, we need to send the message to GSM device, so that it gets activated. It also gets activated by detecting the accident on the vibration sensor connected to the raspberry pi controller. Once the GSM is activated it receives the last latitude and longitude position value and send message to the emergency serverwhich is predefined in the program. The process of image processing it detect the face of person and by using alarm it give the indication of that person

Perencanaan Geometrik Dan Perkerasan Lentur Jalan Wisata Lut Atas Waq Pondok Sayur Kabupaten Bener Meriah, Aceh

Jalan Wisata Lut Atas Bener Meriah Aceh is a road leading to the tourist attraction of the lake, located at 2,100 meters above sea level. The lake called Lut Atas located in Bener Meriah, Aceh, exactly in Waq Pondok Sayur Village, Bukit District. The current status of the Lut Atas Tourist Road is still in the form of a rock and gravel cover, making it difficult to access the tourist area. The purpose of this study is to calculate the throughput capacity and road age plan on the Lut Atas Tourism section, knowing the required soft pavement thickness on the Lut Atas Tourism section with the manual road design method. 2017, knows how to climb slopes and bends to ensure safety and comfort for road users. Based on the results of the 4-day LHR survey, the total number of vehicles is 125 vehicles. Calculation results of pavement thickness of Upper Lut tourist road Waq Pondok Sayur village from STA 0+000 - 3+000, with pavement thickness AC-WC 40 mm, AC-BC 60 mm, aggregate layer 400mm material (LFA) and optional 100mm backfill. The Lut Atas Tourist Trail has a geometric road plan to guide the route according to the plan of 3 bends, namely PI1 Spiral Curve (SCS), PI2 Turn Spiral Circle (SCS), Turn PI3 Spiral bend (SS). The section of Thuong Lut Tourist Road has an expected longitudinal profile of 4 vertical curves with the following details: PPV1 (vertical intersection centre) vertical convex type, PPV2 (vertical intersection centre) concave longitudinal type, PPV3 (vertical intersection centre) concave longitudinal type, PPV4 (vertical intersection centre) convex longitudinal type

Research on Influencing Factors of Traffic Conflicts in Freeway Diverging Area during the Maintenance Period

Based on the traffic conflict techniques, a microscopic safety analysis framework is presented to study traffic conflicts in the freeway exit ramp diverging area (FERDA) during the maintenance period. A manual–software combination data processing approach was used to extract trajectory data from aerial videos and identify actual conflicts. Simulation conflicts were obtained from the VISSIM simulation model. Firstly, the conflict features of maintenance and normal operation periods were compared. Subsequently, conflicts were classified as lane-change conflicts or rear-end conflicts to investigate their spatiotemporal characteristics during the maintenance period. Finally, a random parameters multinomial logit model was developed to study the influencing factors and heterogeneity of conflicts. The results revealed that the FERDA has a higher collision risk during the maintenance period compared with the normal operation period. Additionally, lane-change conflicts have a higher occurrence probability than rear-end conflicts, but a shorter duration. Besides, the conflict density heat map showed that the lane-change conflicts and rear-end conflicts are densely distributed at 0–150 m and the middle lane of the FERDA, respectively. The model results indicated that the factors that significantly influence conflicts include velocity, acceleration, type, position, and destination of vehicle, the heavy vehicle percentage, total number of vehicles in the FERDA, and the velocity and destination difference between vehicles. Among these factors, the type of vehicle, destination difference, and the position of vehicles (at 150–270 m of the FERDA) were found that have significantly heterogeneous impacts on the two types of conflicts. This study is expected to provide safety analysts with an effective analysis method for evaluating the risk of the FERDA during the maintenance period. Additionally, the concluded influencing factors can potentially help develop different and effective safety countermeasures for different types of conflicts.

A Secure and Traceable Vehicles and Parts System Based on Blockchain and Smart Contract.

As society advances, so does the total number of vehicles on the road, creating a massive consumer market for automobiles. According to statistics, a major portion of today’s traffic difficulties are caused by accidents caused by subpar cars and auto parts. As a result, each country has, over time, enacted equivalent rules and regulations to prevent such tragedies. However, in the face of profit, some people are desperate enough to employ illegal parts and illegally modified cars, and auto fraud is rampant. As a result, we employ the blockchain of the symmetrical Blockchain’s digital ledger and smart contract technology to build a decentralized supply chain system that can identify specific parts. In this study, we design and discuss the proposed system framework by user functions and the flow of parts based on blockchain, and we discuss communication protocols that use the symmetry and asymmetry cryptography, algorithms, properties, and security of the mechanism while providing related analysis and comparing the properties and costs of the system with other studies. Overall, the proposed method has the potential to successfully address the issue of automobile fraud.

Analysis of Decision Parameters for Route Plans and Their Importance for Sustainability: An Exploratory Study Using the TOPSIS Technique

Background: This study aimed to identify the most widespread performance objectives for the vehicle routing problem, the degree of comparative importance attributed to each of these performance objectives in the opinion of professionals in the logistics area working in Brazil and also relate them to aspects of sustainability considering environmental, economic and social issues. Methods: To this end, a literature review was carried out in the area and a survey was developed with professionals through a structured questionnaire. The collected data were treated using the TOPSIS multi-criteria technique. Results: The results indicate that the performance objectives in route plans “level of service”, “total number of vehicles” and “total distance travelled” are the ones that, in the opinion of the professionals participating in the research, have greater importance in the planning and elaboration of plan routes and that such objectives directly impact the sustainable results of a given organization. Conclusions: The results can serve as a basis for researchers in the area who aim to broaden the debates on this topic and for logistics operations managers who work directly with planning and elaboration of route plans and who aim to make their operations more sustainable. Therefore, this research addresses the literature gap by identifying which performance objectives should be considered in the elaboration of route plans and how they relate to sustainability guidelines. It is noteworthy that no other study with a similar objective was identified in the literature.

INFLUENCE OF PUBLIC TRANSPORT STOPS ON THE THROUGHPUT OF THE CARRIAGEWAY OF THE STREET

In the presented article, an analysis of the urban traffic flow by composition was carried out, as a result of which it was revealed that cars make up to 80% of the total number of vehicles moving along city street. The influence of public transport stops on traffic conditions and traffic capacity of the carriageway of city streets is considered. The analysis of the calculation is carried out and measures are proposed, the implementation of which will make it possible to change the situation for the better.

Legislative novels in the field of transport management: a retrospective and comparative legal analysis

The Russian Federation today is a developed modern state. The state policy is primarily aimed at the protection of the rights and legitimate interests of society and the state. The rapid socio-economic development of society has led to an increase in the total number of vehicles, and an increase in the number of vehicles on the roads has inevitably led to the emergence and progressive increase in traffic crimes. The criminal legislation provisions regulating the punishment assignment for the road traffic offense by a person subjected to administrative penalty have been changing throughout the entire historical period and up to the present. Article 264.1 of the Criminal Code of the Russian Federation can hardly be called perfect. It is positive that the legislator is making attempts to reflect in the criminal law provisions the concepts proven and substantiated in the legal doctrine. The study’s relevance is due to the need for analysis, scientific and theoretical understanding of the transport crimes problem in the Russian Federation.

Assessing adoption intention of electric vehicles in India: The mediating role of government policies

The total number of vehicles is expected to be 2.5 billion by the year 2050. To stabilize the impact on environment, the automobile sector has shown various innovations by shifting from conventional vehicles to electric vehicles (EVs). However, there is less acceptance of electric cars in India, so this research paper explores the various factors affecting EV adoption intention. The key factors studied are price, environmental concern, infrastructure requirement, and knowledge of EV. This paper also shows that government policies act as a mediator between factors like price, knowledge of EV, and infrastructure requirement on adoption intention of EVs. This research paper presents insights for the decision-makers to understand the determinants and design the strategies for increased adoption intention of EVs.

Investigation of the Fatigue Stress of Orthotropic Steel Decks Based on an Arch Bridge with the Application of the Arlequin Method.

Orthotropic steel decks are widely used in the construction of steel bridges. Although there are many fatigue-evaluation methods stipulated by codes, unexpected fatigue cracks are still detected in some bridges. To justify whether the local finite element model commonly used in fatigue investigations on orthotropic decks can correctly instruct engineering practices, the Arlequin framework is applied in this paper to determine the full fatigue stress under traffic loads. The convergence on and validity of this application for orthotropic decks are checked. Results show that the Arlequin model for deck-fatigue analysis established in this paper tends to be an efficient method for complete fatigue stress acquisition, whereby the vulnerable sites of orthotropic steel decks under traffic loads are defined. Vehicles near the flexible components, such as hangers or cables, can have adverse effects on the fatigue durability of decks. Additionally, the total number of vehicles and their arrangement concentration also affect fatigue performance. Complex traffic conditions cannot be fully loaded in local models. Regardless of the gross bridge mechanics and deck deformation, the fatigue stress range is underestimated by about 30–40%. Such a difference in fatigue assessment seems to explain the premature cracks observed in orthotropic steel decks.

ASSESSMENT OF THE IMPACT OF VEHICLE EMISSIONS ON THE ATMOSPHERE OF THE CITY OF VORONEZH AND THEIR MINIMIZATION

The paper considers the emissions of pollutants from road transport, in the total air pollution they make up 70 % on the example of a particular metropolis. The highway is considered as a linear source consisting of single point sources of pollution. Special attention is paid to suspended fine particles in the solid phase. It is determined that when assessing the level of environmental pollution, it is important to take into account not only the total number of vehicles, but also the ratio of cars of different categories, since they, having different emission factors, supply unequal volumes (mass) exhaust gas components. The variability of the traffic flow density on the streets of six administrative districts of Voronezh and the complexity of zoning the city territory because of three-year monitoring were established. It is proposed to place accounting points on streets that differ in their status in the general transport network of the city in order to obtain reliable data during the monitoring period [11]. The simulation of diffusion movements and migrations of solid-phase air pollutants of roadside territories is carried out. The model of diffusive displacements and migrations of heavy metals is considered in relation only to passive contaminants. The choice is implemented and the method of studying the level of dustiness of motor transport roads is recommended, which allows fixing dust particles from 0.1 microns to 250 microns in the air. An algorithm of an improved system for monitoring the content of fine dust in the atmosphere of a residential zone is proposed. [16]. To minimize the emission of suspended substances, a two-stage emission purification system consisting of a gas-liquid absorber and a catalytic adsorber is proposed.

Environmental Aspects of Toll Plazas & Vehicular Pollution

Abstract: The study aims to encapsulate the effects of toll plazas on environment. It is intended to outline various environmental aspects that are of serious concern and should be looked upon necessarily to curtail their long term ill effects on environment and humans. The rapid development in urban India has resulted in a tremendous increase in the number of motor vehicles. Air pollution is a serious environmental health threat to humans. Adverse effects range from nausea, difficulty in breathing and skin irritations, birth defects, immunosuppression and cancer. Air pollution, particularly in the form of particulate matter, is a serious challenge in India, and transportation is a significant factor in the nation’s air quality problems. According to the 2017 Global Burden of Disease, some 1.1 million people in India die prematurely each year from diseases directly related to air pollution, making it the fifth leading cause of death in the country. Transportation sources account for approximately a third of PM pollution in India, and a somewhat higher proportion of nitrogen oxides, another set of compounds harmful to human health. Because its vehicle fleet is small relative to its large population, India has very low per capita transportation emissions. But that fleet is growing rapidly: total vehicle sales (including motorcycles) increased from about 10 million in 2007 to over 21 million in2016, and the total number of vehicles on the road is expected to nearly double to about 200 million by 2030. All these situations indicate that air pollution becoming a major problem in Indian context and there is an essential need to build up healthy environment and increase the level of research around the world. The study is based on the case study results from one of the toll plaza’s (KACHKOOT TOLL PLAZA) in j&k,India .. Keywords: (Air pollution, Vehicular emission, Carcinogenicity ,Air Quality Index, Toll, Diseases)

Relieving the Congestion around a School via Automatic Vehicle Identification Technology-Based Traffic Measures

Recently, many parents drive their children to and from schools, leading to serious road congestion around the school gate. The school-related congestion is a special type of congestion caused by periodic impulsive aggregation of specific travellers for certain events. In this study, the individual long short-term traffic behaviours were reconstructed based on automatic vehicle identification (AVI) technologies. The cause and countermeasure of congestion around the service centers were identified through the individual behavioural properties. The vehicles that were primarily responsible for periodic impulsive aggregation congestion (PIAC) around the school gate were precisely targeted via a proposed vehicle grading clustering framework. The road management objectives were updated in the AVI data environment and it was found that only 3%–5% of the total number of vehicles passing by the school gate require specific management such as traffic enforcement activities. A series of traffic measures were formulated based on the results of vehicle grading clustering and achieved positive effects in a periodic impulsive aggregation area. It is an effective way to solve the PIAC by formulating management with different activity levels and resolutions for specific travellers. The methodologies and experience presented in this study may provide a useful tool for relieving such special type of congestion around other service centers faced with similar scenarios.

Identyfikacja liczby pojazdów przeciążonych na podstawie danych z wybranych preselekcyjnych stacji ważenia pojazdów w ruchu

W artykule przedstawiono wyniki wykonanych w 2014 i 2018 roku badań dotyczących liczby pojazdów przeciążonych poruszających się po wybranych drogach. Zbadano procentowy udział pojazdów przeciążonych w całkowitej liczbie pojazdów, określono liczbę dni charakteryzujących się dziennym udziałem pojazdów przeciążonych przypadającym na dany przedział – przy różnych wariantach pomiarów, bez kontroli i z kontrolą Głównego Inspektoratu Transportu Drogowego (GITD). Ustalono, że procentowy udział pojazdów przeciążonych zależał od intensywności kontroli prowadzonych przez GITD. Udział pojazdów przeciążonych (tj. w przypadku braku kontroli wyniósł 25,1% (wartość minimalna 18,5%, maksymalna 31,4%). Przy sporadycznych kontrolach udział pojazdów przeciążonych wyniósł 9,0% (wartość minimalna 6,4%, maksymalna 11,0%). Przy intensywnych kontrolach udział pojazdów przeciążonych wynosił 1,2% (wartość minimalna 0%, maksymalna 2,5%) oraz 2,2% (wartość minimalna 0%, maksymalna 7,7%). Stwierdzono, że histogramy procentowego udziału pojazdów przeciążonych mogą być aproksymowane rozkładem normalnym.

Study on the minimum fleet size based on deadheading time threshold

By integrating travel demand and car-hailing supply information, the car-hailing platforms have realized a more targeted non-cruise mobile order receiving mode. That reduces the deadheading (DH) time and the number of online car-hailing vehicles. This result will lead to a significant change in the number of online car-hailing vehicles. This paper studies the minimum fleet size based on deadheading time threshold. Then Then we use Suzhou taxi data to solve the minimum number of vehicles. Firstly, the space-time description of online car-hailing operation was established to study the influence of the DH time threshold on the total number of vehicles. The results show that the total number of vehicles decreases with the increase of the DH time threshold, and the trend tends to be gentle. Secondly, this paper discusses the relationship between the time cost of passenger and driver and the DH time threshold. Thirdly, this paper discussed the influence of the number of car-hailing platforms on the total number of vehicles, and it proves that the total number of vehicles in the multi-platform market is larger than that monopolized by a single platform. Finally, the feasibility of the research is verified by using Suzhou taxi data. Meanwhile, it proves that the minimum total number of vehicles has a certain robustness.

Impacts of Various High Beam Headlight Intensities on Driver Visibility and Road Safety


 
 
 Based on several studies, driving above certain speed at night while using low beam headlights has been found to result in insufficient visibility to respond to road hazards. Luckily, vehicle headlight technology has advanced so much and the system is commercially available in many parts of the world. However, the technical development for optimal photometric performance raises a few questions. The use of high beam headlight system creates a glare to drivers of oncoming and preceding vehicles (because of both oncoming headlights and preceding taillights), to the extent that it has become necessary to determine the need to put a limit on the luminous intensity of high-beam headlights. This study shall therefore summarize and investigate visual performance that allows for evaluation of the potential benefits of increased luminous intensity by considering glare rating related to safety. Two different car models; the Proton Prevé and the Perodua Myvi were used in the experiments. The results showed that the highest average illuminance [lux] for single vehicle was 17.5, 7.5, 5.0 and 1.0 for the distances of 30m, 60m, 120m and 150m. However, the average illuminance based on total number of vehicles was 1.0, 0.5, 0.0 and 0.0 at distances of 30m, 60m, 120m and 150m, which were considered below maximum recommended safety level (max. 9.0 – 11.0 lux). The current average vehicle high-beam headlight control was found at the level of acceptable glare control (glare to oncoming and preceding drivers) and below the maximum level of illuminance rate with the normal speed of 40 km/h.
 
 

Traffic Light Controller using Image Processing

Traffic congestion at junctions is a serious issue on a daily basis. The prevailing traffic light controllers are unable to manage the different traffic flows. Most of the current systems operate on a timing mechanism that changes the signal after a particular interval of time. This may cause frustration and result in motorist's time waste. Traffic congestion is a major problem in the currently existing systems. Delays, safety, parking, and environmental problems are the main issues of current traffic systems that emit smoke and contribute to increasing Global Warming. Sensor-based systems reduce the waiting time and maximize the total number of vehicles that can cross an intersection. Our proposed system can control the traffic lights based on image processing without the need for traffic police. This can reduce congestion, delay, road accidents, need for manpower. Under image processing, we use sub techniques like RGB to Gray conversion, Image resizing, Image Enhancement, Edge detection, Image matching, and Timing allocation. A real-time image is captured for every 1 second. After edge detection procedure for both reference and real-time images, these images are compared using SURF Algorithm. Then the amount of traffic is detected and the details are stored in the server. Arduino is used for a traffic signal in the hardware part. It consists of a Wi-Fi module. The micro-controller used in the system Arduino. Four cameras are placed on respective roads and these cameras are used to capture images to analyze traffic density. Then the traffic signals are decided according to the density of traffic. Our technique can be effective to combat traffic on Indian Roads. A lot of time can be saved by deploying this system and also it conserves a lot of resources as well as the economy