Vehicle Motion Research Articles

Integrating multiple vehicle drivetrains into an energy system simulation model for Japan

To reduce the impact of climate change, the Japanese economy has set mitigation goals that include the decarbonisation of the energy sector and the electrification of transport. As a result, zero-emission vehicles could change the electricity demand curve, and it is thus necessary for them to be integrated into energy system models to estimate their impact and any opportunities or challenges they represent to grid stability. While previous studies have integrated single-vehicle technologies in the simulation of country-level energy grids, the present study improves on available models by integrating a country-level energy system model with a transmission grid, while considering two different drivetrains and improving on the diversity of the vehicle movement patterns considered. The simulation model results highlight that the electricity demand of each drivetrain is distinct, with a midday peak for battery electric vehicles and less pronounced morning and afternoon peaks for fuel cell electric vehicles. An important conclusion is that the infrastructure setup and associated use rules can be expected to significantly impact transport demand curves, indicating the need to further investigate how policy changes can impact the overall configuration of the energy mix.

Urban Traffic Congestion Prediction Using GTFS Data and Advanced Machine Learning Models

Urban traffic congestion represents a complex challenge influenced by many dynamic factors. Peak periods typically exacerbate congestion, while bad weather can slow vehicle movements and increase travel times. Accidents and road closures cause sudden and unexpected disruptions, making traffic management a constant challenge. Using a dataset of over 66,000 GTFS records with machine learning classifiers like Random Forest, XGBoost, CatBoost, and Decision Tree models, the study seeks to forecast traffic conditions. SMOTE is used to ensure greater representation of minority classes in order to solve the dataset's intrinsic imbalance, and feature scaling enhances model convergence. With an accuracy of 98.8%, Random Forest was the most accurate model for this challenge. The outcomes demonstrate that the system is able to precisely forecast traffic in real-time, which aids in route planning, traffic control, and enhancing urban mobility.

Humanising Commercial Streets as a Tool for Social Sustainability

Commercial Streets are the beating heart of any city, the hubs of leisure, business, and social gatherings, in which they also reflect cultures and be used to assess the level of well-being of citizens. Recently, due to the world population increase and other various factors, such as excessive urbanism and the domination of vehicle movement over pedestrianization rights, some commercial streets suffer from dehumanisation causes and symptoms. Those vary between substandard planning and construction, inhospitable landscaping, and excessive visual pollution, among other causes and symptoms. Thus, this research investigates various Humanisation strategies adopted worldwide. It discusses the potential of applying technological, spatial/physical, and social strategies to (re)Humanise commercial streets, using Othman Ibn Affan Street in Heliopolis as an applied case study. It suggests a rating system that could be adopted to measure the standard expected qualities of commercial streets. The research follows a mixed-method approach and uses various research tools, such as literature review, archival, critical analysis, observation study, and survey questionnaire to achieve its aim, which is creating a theoretical framework to achieve the Humanisation qualities in commercial streets. Through a critical discussion, the research determines in its developed framework that a combination of several defined Humanisation qualities is needed to (re)create Humanised commercial streets.

Quick commerce and the evolving business models of the food retail industry - Investigating the quick commerce supply chain and the urban impacts of dark stores

The transition to food e-commerce is made possible by the implementation of new technologies, by the arrival of new players, and by the development of new logistics capacities (dark stores and micro-hubs). The quick commerce sector marks an additional step in the development of instant deliveries, which now applies to the entire food and online shopping market. This research analyzes the organization of the quick commerce supply chain (organization based on logistics micro-hubs (dark stores), partnerships with large-scale distributors, third-party logistics operators, organization of the last mile) and also highlights the highly transport-intensive nature (in terms of vehicle movements and delivery flows) of dark stores.

Enhanced Vehicle Movement Counting at Intersections via a Self-Learning Fisheye Camera System

Enhanced Vehicle Movement Counting at Intersections via a Self-Learning Fisheye Camera System

Различные аспекты создания алгоритмов для модели транспортных потоков на основе теории клеточных автоматов

The preprint is devoted to the description of the complete set of algorithms for the model based on cellular automata, developed by the team of authors from KIAM RAS for the last few years. The paper presents algorithms of vehicle movement in various situations: changing lanes, avoiding obstacles, driving through different types of intersections, entrances/exits, etc. Driver behavior algorithms and their impact on traffic situation are presented.

Optimization of urban agglomeration transport flows

The article proposes methodological approaches to the study and optimization of traffic flows using simulation modeling by the example of one of the street intersections in the city of Novosibirsk. Possible stages of sequential implementation of analytical and practical measures for optimizing transport flows are given. It is proposed to use the AnyLogic environment as a modeling tool. When creating the simulation model, satellite images of the area were used, inserting an image of the analyzed section of the road network on top of the satellite image, setting objective indicators of traffic intensity, developing and optimizing a vehicle movement algorithm. The results of the study make it possible to assert that AnyLogic environment tools are an adequate way to optimize traffic flows. Optimization measures made it possible, based on adjusting the duration of traffic light control phases, to reduce the average time spent by cars at the intersection by 35% and, thereby, increase the throughput of the intersection by 10%. The use of the proposed approaches to the development of traffic simulation models is a promising direction for optimizing traffic control at urban intersections.

Методика разработки суточных планов интервалов движения пассажирских автотранспортных средств по городским регулярным маршрутам

Currently, the effectiveness of the influence of vehicle movement intervals on transport work has not been properly investigated. In addition, the rules for the formation of periods for the performance of transport work require further study. In this regard, the development of daily interval plans for passenger vehicles on urban regular routes becomes relevant. The article proposes a system of criteria for combining indicators of the passenger transportation process during periods of the day. This system is aimed at minimizing the value of the sum of the differences between the adjusted timetable and the estimated number of buses, taking into account work throughout all periods of the day, as well as ensuring the values of capacity utilization coefficients less than or equal to one. Based on the criteria system, an algorithm for developing daily interval plans for motor vehicles on urban regular routes has been obtained. The dependences have been established which demonstrate the sum values of the differences between the adjusted and calculated number of buses during all periods of the day along the route on the value of the adjustment interval. The dependencies have a minimum extremum, indicating the presence of an optimal peak interval.

효율적 감시 시스템 구축을 위한 객체 추출 알고리즘 구현에 관한 연구

Commonly used surveillance systems are stored as videos only when movement is detected. Therefore, they depend on a limited area. To expand their use, the limitations on the area and storage capacity must be overcome. A problem in terms of accuracy is that when targeting an object at a great distance, judging the object is difficult and cannot be used as evidence. In this study, to compensate for these problems, we proposed an efficient algorithm that could more accurately distinguish the background image and the target object by applying a mixed Gaussian model in the pre-processing process of the acquired image. Consequently, the average recognition and tracking rate of this algorithm was approximately 82%, compared with an average of 61% using conventional vehicle images and movement vectors.

MODELING CITY TRAFFIC MANAGEMENT AND IDENTIFICATION OF COMPETITIVE ROUTES USING INTELLIGENT TRANSPORTATION SYSTEMS

This article presents a conceptual approach to modelling city traffic management and identifying competitive routesusing intelligent transportation systems. It argues that modelling traffic in transport streams, considering the behaviour ofeach individual vehicle, yields the most reliable results for real-time modelling of specific intersections in city trafficmanagement. The proposed methodology for developing an algorithm to detect competitive routes allows users to choosethe optimum route. The method is based on the statistical relationship between route indicators and helps to accuratelycalculate the demand for the implementation and improvement of the transportation network with subsequent changes inits operation. Redistribution of traffic flows for the identification of competitive routes in transport corridors and the impactof random variable values on route indicators are discussed. It is proven that the probability of describing the distributionof intervals between vehicles entering the network is of utmost importance for describing processes in a transport corridor,with the exponential distribution being typically used for these purposes. The conclusion is made that the micro-levelmodel for calculating vehicle movement modes should meet the requirements necessary for solving the task of modelingcity traffic management and identifying competitive routes using ITS. Such conditions are characterized by significantfluctuations in vehicle movement modes, stops at regulated intersections and in traffic jams, lane and trajectory changes,which significantly affect the algorithm for finding a competitive route in the transport corridor.

CFD Analysis of Sloshing in the Fuel Tank of a Heavy Vehicle with Emergency Braking System

Liquid sloshing, which occurs in all accelerating and liquid-carrying vehicles, is of great importance, especially in the automotive and aerospace industries. Large-scale fluid sloshing causes both operational and safety problems in vehicles. In this study, the fuel tank of a heavy vehicle with an emergency braking system is designed in three dimensions, and liquid sloshing in the fuel tank is investigated by CFD analysis meth-od. VOF solution method, k-ԑ turbulence model, and PISO solution algorithm are used in the study. In the analysis of liquid sloshing, it is assumed that the vehicle is traveling at a certain speed, decelerates and stops with emergency braking, and remains station-ary for a while. The braking scenario and boundary conditions are based on test data from a heavy vehicle manufacturer. The designed fuel tank with a capacity of 207.6 li-ters was analyzed at 25%, 50%, and 60% diesel fuel filling levels in 6 different cases with and without anti-slosh baffles. Four virtual sensors were placed on the side wall of the fuel tank in the direction of vehicle movement, and time-dependent pressure changes were analyzed for all cases. In addition, the fuel volume ratio in all cases is visualized and presented for specific time steps. With the use of anti-slosh baffles, the maximum pressure, the rate of pressure increase, and the liquid sloshing were reduced by a factor of 2-3 for different cases. With the design of the fuel tank using anti-slosh baffles, instantaneous interruptions in the fuel system are prevented. Reducing the im-pact pressures on the tank walls is expected to positively affect noise, vibration, and stability problems.

Komparasi Konsep Penciptaan Tempat dan Keterikatan Desa Kota Studi Kasus Kota Denpasar

This study aims to compare the concept of place creation and place attachment in Denpasar City, Bali. In the context of rapid urbanization, urban development is becoming increasingly important in maintaining cultural identity and environmental sustainability. The main problem in this study is the difference in understanding and implementation of the concept of place creation and the level of place attachment by communities that focus on rural and urban urbanization. The urgency of the research lies in the need to understand Denpasar City as a center of cultural and tourism activities, blending urban growth with cultural and environmental preservation. The analysis was carried out on a review of government archives in the form of narratives, observations of service use, purchase of goods and vehicle movements, as well as examination of physical and spatial components. The results showed variations in people's perceptions of the concept of place creation, focusing on cultural and environmental preservation. In addition, the degree of attachment to places is related to the active participation of the community in the preservation of the cultural and environmental heritage of the city. This research reveals the importance of integrating people's aspirations in urban planning as well as promoting cultural and environmental sustainability as an integral part of the development of a better Denpasar City.

Regarding the issue of aquaplaning and the interaction of a car tire with the road surface through a layer of water

Problem. The process of interaction of a pneumatic tire of a car wheel with the surface of the road surface, which is covered with a layer of water, affects the safety of the vehicle movement, therefore, the assessment of the effect of aquaplaning when writing the conclusions of the auto technical examination is an actual direction of research. The study of the effect of aquaplaning will allow forensic experts and specialists in the automotive industry to make an objective analysis and form non-subjective conclusions. Goal. The purpose of the work is to determine the design parameters and operational features of the pneumatic tire, as well as the speed of the vehicle on the process of interaction of the car wheel tire with the surface of the road coating, which is covered with a layer of water. Methodology. The approaches adopted in the work to solve the set goals are based on the theory of aquaplaning, the theory of the interaction of the pneumatic tire with the road surface, the theory of the vehicle and the laws of theoretical mechanics. Results. The obtained results of the research in the form of an analysis make it possible to assess the impact of the aquaplaning effect of a pneumatic tire on road safety. It was established that the thickness of the water layer affects the conditions for meeting the requirements established by the traffic rules, since the decrease in the height of the tire tread pattern leads to unstable contact of the tire with the road surface. Originality. The results of the study provided an opportunity to get an idea of the influence of the design parameters of tires on road safety in terms of forming the conclusions of the motor-technical examination. Practical value. The obtained results can be recommended to forensic experts when writing expert opinions and for expert research

THE FACTORS THAT MOST INFLUENCE THE ATTRACTION OF THE MOVEMENT AT ST PAUL'S CATHOLIC MIDDLE SCHOOL, PALANGKA RAYA

Transportation is a basic need of an area that is used as an effort to improve the welfare of its population. Transportation planning is absolutely necessary to find the most efficient solution of the interaction of movement. Movement begins with the rise and pull of movement (Trip Generation). The education area is one of the land uses that generates mass movements and has a large size. Therefore, research was conducted on the pull of movement in the educational area at St. Paul Catholic Junior High School Palangka Raya using multiple linear regression analysis. That way it can be known the factors that most affect the pull of movement as well as the best model that can be made. The study was carried out for 6 working days, namely on Monday-Saturday at peak hours. The collected vehicle data is then converted into passenger car units. The variables used are the pull of vehicle movement (Y), land area (X1), building area (X2), number of classes (X3), number of students (X4) and number of teachers and employees (X5). Analysis using SPSS software version 26. Various data tests were carried out to obtain appropriate results, the results of the analysis and tests that have been carried out concluded the best model of total travel attraction (junior high school / hour), namely Y = -2645.194 + 4.194X4 + 6.452X5 where X4 is the number of students and X5 is the number of teachers and employees. Based on the results of the analysis, it is concluded that Factors whomost influence the pull of the movement are the number of students and the number of teachers and employees.

Инструменты цифровой трансформации логистических процессов в рамках торгово-экономических отношений

The article discusses the implementation of digital transformation as an integral part of the logistics industry, the purpose of which is to organize the use of digital technologies in all areas of trade and economic relations. The use of digi-tal technologies is considered on the example of their implementation in the functioning of international road check-points in order to ensure acceleration of their passage by road transport, as well as traceability of further movement of vehicles and cargo. The factors influencing the throughput of international road checkpoints during customs operations are systematized. An analysis of the impact of digital transformation of logistics processes on the development of trade and economic relations between countries was carried out.

Identification of places with deteriorated air quality in city of Žilina in relation to road transport

The aim of the research is to identify places with deteriorated air quality in the selected city. After an analytical analysis of the data, it is possible to propose steps that can be used to actively contribute to the reduction of air pollution, especially due to road traffic. Places where deteriorated air quality was identified were identified on the basis of practical measurements. Given that the measurement route was designed in a built-up area of the city with a large number of pedestrians, the research was primarily focused on the identification of particulate matters (PM) and the concentration of carbon monoxide CO. The measurements were performed repeatedly on a pre-defined route. The measurements were carried out repeatedly during the morning rush hour when traffic was congested on the roads. Based on the processing and evaluation of the measurements, the sections where increased values of individual emissions were recorded were determined. In this way, it is possible to precisely identify places where air quality deteriorates. The research conclusions provide support for planning the optimization of air quality management policies towards the creation of sustainable cities. The research results present the possibilities of identifying problematic sections from the point of view of emissions production. Critical places with regard to the production of emissions can be connected to places where a permanently increased movement of vehicles is observed.

Research on the encounter motion of super-cavitating vehicles

In this paper, the super-cavitating phenomenon under the effect of two vehicles’ encounter motion processes is numerically studied. Particular attention is given to the influence of the vertical gaps between the vehicle, the cavitation number, and the slenderness ratio on the cavity profile and radial force of the object. Several numerical models are built to study the cavity evolution process and the force acting on the vehicle to explore the influence mechanism of two vehicles’ encounter motion on supercavitating flow. The study shows that the cavity around the vehicle is primarily affected by the vertical gaps and cavitation number, but is relatively weakly affected by the slenderness ratio. Several impact laws are acquired in the paper. The relationship between cavity fracture time and vertical gaps is approximately a power function and obeys the law of t = 5.433h0.3688. The concept of the time of the maximum radial force occurrence and the cavitation number follows the formula of t = 4.86e0.3688σ. The relationship between the maximum radial force occurrence position and the cavitation number is a function of Ln and consistent with the law n = −0.799ln(σ) + 8.427.

Traffic Performance Analysis – Emp And Saturation Degrees Using Pkji 2023

The intersection of KH Wahid Hasyim Road and Inspection Road which is located in the Selokan Mataram, Dabag, Condongcatur, Sleman, DIY area has a high traffic volume because it is a link between residential, educational and economic zones and shopping centers. The problem that often occurs at the intersection of Jalan KH Wahid Hasyim and Jalan Inspection Selokan Mataram, Dabag, Condongcatur, Sleman, DIY is high traffic flow, which often results in traffic jams. The regulation of traffic lights currently in operation cannot overcome the congestion that often occurs, especially during peak hours. The aim of this research is to analyze the performance of signalized intersections using the PKJI 2023 method. To provide appropriate solutions and alternative problem solving at these intersections. Which can improve the performance of the signalized intersection Jl. KH Wahid Hasyim and Jl. Mataram Selokam Inspection. Based on the results of research that has been carried out, it is as follows: a. The traffic flow at the intersection of four is marked KH. Wahid Hasyim and the Mataram Sewer Inspection Road based on the analysis results show that the traffic volume at signalized intersections for 7 days is 16,527 PCU/hour. b. The traffic volume at the intersection with the KH road signal. Wahid Hasyim and the Mataram Sewer Inspection road at peak hours on Monday 02/10/2023, namely 2539 or 1106.2 SMP/Hour. c. Annual average daily traffic at the intersection of four with the KH road signal. Wahid Hasyim and the Mataram Sewer Inspection road for 7 days were taken at peak hours 06.00 – 07.00 and 16.30 – 17.30. get results, namely 45.10 Kend/Hour. d. Calculation of traffic performance and EMP. Which was carried out for 7 days with a K value of 0.08. according to the road width of 6m, you get a result of 3.60 SMP/hour. e. Degree of Saturation at the intersection of four signalized roads KH. Wahid Hasyim in the peak volume period Monday 02/10/2023. Taken at each intersection, North 0.520 SMP/hour, South 0.641 SMP/hour, East 0.162 SMP/hour and West 0.291 SMP/hour. 1. Degree of saturation at the intersection of four KH roads. Wahid Hasyim and the Mataram Sewer Inspection road for the period Monday 10/02/2023 is North 0.520 SMP/Hour, South 0.641 SMP/Hour, East 0.162 SMP/Hour and West 0.291 SMP/Hour. then the service level is D with unstable flow conditions but the speed and movement of vehicles is very low. 2. Vehicle volume based on the results of a 7-day traffic survey shows the number of heavy vehicles on Monday 02/10/2023 for the time period 06.00 – 07.00 and 16.30 – 17.30. namely 2539 Kend/Hour. 3. The capacity value (C) obtained is 2688 SMP/Hour. 4. The value of traffic flow and EMP passing through the four signalized intersections on Jl. KH. Wahid Hasyim and Jl. Sewer Inspection with a K value of 0.08 gets a result of 3.60 SMP/Hour.

Spatio-Temporal-Attention-Based Vehicle Trajectory Prediction Considering Multi-Vehicle Interaction in Mixed Traffic Flow

As a link connecting the environmental perception system and the decision-making system, accurate obstacle trajectory prediction provides a reliable guarantee of correct decision-making by autonomous vehicles. Oriented toward a mixed human-driven and machine-driven traffic environment, a vehicle trajectory prediction algorithm based on an encoding–decoding framework composed of a multiple-attention mechanism is proposed. Firstly, a directed graph is used to describe vehicle–vehicle motion dependencies. Then, by calculating the repulsive force between vehicles using a priori edge information based on the artificial potential field theory, vehicle–vehicle interaction coefficients are extracted via a graph attention mechanism (GAT). Subsequently, after concatenating the vehicle–vehicle interaction feature with the encoded vehicle trajectory vectors, a spatio-temporal attention mechanism is applied to determine the coupling relationship of hidden vectors. Finally, the predicted trajectory is generated by a gated recurrent unit (GRU) decoder. The training and evaluation of the proposed model were conducted on the NGSIM public dataset. The test results demonstrated that compared with existing baseline models, our approach has fewer prediction errors and better robustness. In addition, introducing artificial potential fields into the attention mechanism causes the model to have better interpretability.

Unlocking insights from commercial vehicle data: A machine learning approach for predicting commercial vehicle classes using Michigan State data (1999–2017)

Commercial vehicles have a significant economic effect by moving goods and services across national borders and around the globe. They are also responsible for most commercial transactions in several industries, including manufacturing, retail, agriculture, and building. Its characteristics, such as heavyweight and big vehicle size, also affect how traffic moves and streams behave. As a result, it adds to growing accident rates, congestion, pollution, and sidewalk deterioration. This paper uses the commercial vehicle survey (CVS) from Michigan state based on different establishments to investigate the pattern movements of commercial vehicles between 1999 and 2017. This study aims to develop predictive commercial vehicle classes through machine learning techniques. This study uses three machine learning methods to predict the Commercial Motor Vehicle (CMV) class (Naive Bayes, Linear SVM, and decision tree). A feature selection study selects the significant attributes for CMV class prediction. The accuracy of the classification prediction model methods was compared through the training and testing phases. The results show that The CVS was successfully used to classify commercial vehicles with accuracy greater than 89 %.