Vehicle Dimensions Research Articles

An Estimation Method for the Overthrowing Moment of Vehicles on the Car Deck of the Ro-Ro Ferry

Ensuring passenger safety and comfort is crucial for maintaining trust in sea transportation, especially as ship accidents remain a concern. One critical area for improvement is the vehicle fastening systems on Roll-On-/Roll-Off (Ro-Ro) ferries, which must account for fastening techniques and vehicle positioning to prevent shifting or overturning during adverse conditions. This study calculates the shear and overturning moments acting on vehicles when a ferry experiences rolling motion due to beam waves, using numerical simulations to evaluate the impact of vehicle placement. Wave heights were adjusted to reflect operational area conditions, and vertical and lateral accelerations were derived based on vehicle dimensions, type, and enter of gravity. A case study of a Ro-Ro ferry operating on the Bira-Pamatata route revealed that Bus 2, located at the rear centreline, exhibited the highest rolling moment of 14,370 N·m, while Ayla 21, positioned at the front centreline, had the lowest moment of 1,141 N m. These results demonstrate that vehicle mass, dimension, and vertical and horizontal center of gravity significantly influence rolling and share moments.

Leader–follower identification with vehicle-following calibration for non-lane-based traffic

Most car-following models were originally developed for lane-based traffic. Over the past two decades, efforts have been made to calibrate car-following models for non-lane-based traffic. However, traffic conditions with varying vehicle dimensions, intermittent following, and multiple leaders often occur, making subjective Leader–Follower (LF) pair identification challenging. In this study, we analyze Vehicle Following (VF) behavior in traffic with a lack of lane discipline using high-resolution microscopic trajectory data collected in Chennai, India. The paper’s main contributions are threefold. Firstly, three criteria are used to identify LF pairs from the driver’s perspective, taking into account the intermittent following, lack of lane discipline due to consideration of lateral separation, and the presence of in-between vehicles. Secondly, the psycho-physical concept of the regime in the Wiedemann-99 model is leveraged to determine the traffic-dependent “influence zone” for LF identification. Thirdly, a joint and consistent framework is proposed for identifying LF pairs and estimating VF parameters. The proposed methodology outperforms other heuristic-based LF identification methods from the literature in terms of quantitative and qualitative performance measures. The proposed approach can enable robust and more realistic LF identification and VF parameter calibration with practical applications such as level of service (LOS) analysis, capacity, and travel time estimation.

Prediction of full-scale crashworthiness performance based on component-level testing: application to bus structures

The growing interest in vehicle crashworthiness necessitates efficient methods to predict full-scale crash performance from component-level testing. This study introduces a framework for predicting vehicle crashworthiness using component-level tests. The framework employs a scaling procedure incorporating factors like total energy, deformation mode, and vehicle dimensions. The feasibility of this method was validated both experimentally and numerically in a study on the rollover performance of paratransit buses, utilizing two decades of data from full-scale and component testing of six buses. Wall-to-floor connections, prone to plastic deformation during rollovers, were tested for component bending. A rollover performance index was developed as a scaling procedure, establishing a clear correlation between full-scale and component tests. Additionally, extensive finite element simulations confirmed the framework applicability to numerical simulations, demonstrating its practical use in vehicle crashworthiness evaluations to foster resource-efficient design and reduce dependence on full-scale tests.

An Assessment of Accurate Range Estimator for Electric Vehicle Applications

Abstract: The world’s primary modes of transportation are facing two major problems: rising oil costs and increasing carbon emissions. As a result, electric vehicles (EVs) are gaining popularity as they are independent of oil and do not produce greenhouse gases. However, despite their benefits, several operational issues still need to be addressed for EV adoption to become widespread. One of the main obstacles for the acceptance of EV’s is the driver’s fear of being stranded by a depleted battery. In other words, accurate estimation of the remaining SOC is required to provide positive edge towards adoption of EV. In this work, an EV is tested for a drive line cycle of 10 Km for a trip, and key parameters such as elevation, speed, body dynamics, vehicle dimensions, on track speed have been collected. A model of EV power train is developed in MATLAB Simulink from the data logged and a static app is being developed which estimates the vehicle dynamic forces, power consumption, energy utilized for the trip, State of Charge (SOC) and remaining mileage of the vehicle.

An Overview of the Efficiency of Roundabouts: Design Aspects and Contribution toward Safer Vehicle Movement

Transforming intersections into roundabouts has shown that a sufficient degree of road safety and traffic capacity can be achieved. Because of the lower speeds at the area of a roundabout, drivers tend to become more easily adaptive to any kind of conflict with the surrounding environment. Despite the contribution to safety, the design elements of roundabouts are not uniformly fixed on a worldwide scale because of different traffic volumes, vehicle dimensions, drivers’ attitude, etc. The present study provides a brief overview of the contribution of roundabouts to road safety and the interactions between safety and the design elements of roundabouts. In addition, discussion points about current challenges and prospects are elaborated, including findings from the environmental assessment of roundabouts; their use and performance on the era of autonomous vehicles that will dominate in the near future; as well as the role and importance of simulation studies towards the improvement of the design and operation of roundabouts in favor of safer vehicle movement. The criticality of roundabouts, in terms of their geometric design as well as the provided road safety, lies upon the fact that roundabouts are currently used for the conventional vehicle fleet, which will be gradually replaced by new vehicle technologies. Such an action will directly impact the criteria for road network design and/or redesign, thereby continuously fostering new research initiatives.

Automatic Outer Contour Detection and Quantification of Vehicles Using Monocular Vision

Oversized vehicles have the potential to collide with walls or ceilings when passing through tunnels and bridges, posing a serious threat to the health of transportation infrastructure and public safety. Hence, it is crucial to accurately and immediately detect vehicle dimensions, including length, width, and height, to avoid such accidents. Using computer vision and view geometry, this study presents a framework for automatically detecting and quantifying the outer contours of vehicles through monocular vision. First, traffic scene images are captured which are then used to create a transformation matrix of the ground surface. Second, a modified Mask region-based convolutional neural network (Mask R-CNN) is constructed to detect and segment the vehicle instances from the video frames. Finally, a view geometry-based algorithm was developed to detect the outer contours of passing vehicles and quantify their dimensions. In the field test, the accuracy of the vehicle segmentation and the identified vehicle dimensions was validated. In addition, the proposed method’s superiority was confirmed by comparing it with two other existing approaches. The comparison results show that the proposed method has better accuracy and is more convenient to use since it does not require a premeasured reference. In addition, the developed method can accurately identify not only the dimensions of vehicles parallel to the road but also vehicles that are changing lanes or making a U-turn.

Derivation of vehicle dimensions at the early concept stage based on occupant posture

Derivation of vehicle dimensions at the early concept stage based on occupant posture

Derivation of vehicle dimensions at the early concept stage based on occupant posture

Derivation of vehicle dimensions at the early concept stage based on occupant posture

STRUCTURAL DESIGN OF A WORKBENCH FOR THE NEEDS OF A SERVICE TECHNICIAN

The presented paper deals with the structural design of a workbench with adjustable height, which will serve as part of the equipment of a light commercial vehicle for the needs of a service technician. The main objective of this paper is to create a functional design and 3D CAD model of a workbench that will meet the requirements of safety, mobility, and simple utilisation. Moreover, the design needs to consider the requirements of adjustable height and the dimensions of the work vehicle. The lifting mechanism is represented by arms fitted with sleeves that move along a lead trapezoidal screw rotating by a hand crank. In this paper, the force action in the axis of the threaded rod of the lifting mechanism is scrutinised in two extreme positions (highest and lowest position). The highest axial load on the threaded rod was found to be 9927.13 N in the lowest position of the mechanism. On the basis of this load, a right and left-hand trapezoidal threaded rod TR16×4 is selected, which satisfied the strength condition. The design of the sleeve height and the number of sleeve threads required are essential for safe utilisation. Due to the dimension of the guide rod, the height of the sleeve is selected to be 40 millimetres. The work surface is an important part of the workbench and consists of two parts. The chief larger part is made of medium density fibreboard and the smaller modular part can be in the two modular forms. The first version is the medium density fibreboard, and second alternative is a board designed to fix the components during their maintenance, repair as well as for welding.

Developing rear-end and side-swipe conflict prediction models for urban signalized intersections under disordered traffic conditions

A Traffic Conflict Technique is a proactive approach that identifies observable critical vehicle interactions (conflict) that could have led to a crash. This paper develops conflict-based safety performance functions (SPFs) to predict the number of traffic conflicts at the signal cycle level in mixed traffic conditions with poor lane discipline (disordered traffic conditions). 9586 vehicle trajectories were extracted from traffic video data collected from 4 signalized intersections in India. Critically interacting vehicle pairs were estimated using Time to Collision (TTC). The conventional surrogate measure is modified into a 2-dimensional surrogate approach which captures the conflicts by incorporating the vehicle dimension, heading direction, position, speed, and acceleration in the longitudinal and lateral direction between vehicles. Rear-end and side-swipe conflicts are identified at varying threshold values to incorporate severity. Rear-end conflict SPFs show that higher conflict occurrence is expected during signal cycles with more traffic volume, higher vehicle arrival speed, more right-turning traffic, and a lower platoon ratio. At severe threshold (TTC ≤ 1 s), one 1 m/s increase in speed of vehicle increases the expected number of rear-end conflicts by 6%. Furthermore, SPFs show that severe side-swipe conflicts are expected during signal cycles with more lane-changing maneuvers and right-turning vehicles. For TTC ≤ 1 s, one unit increase in the number of lane changes would increase the expected number of sides-wipe conflicts by 7.9%. The finding of this study can be most beneficially used for arriving at policy measures and improving the safety of signalized intersections in disordered traffic conditions.

I-24 MOTION: An instrument for freeway traffic science

The Interstate-24 MObility Technology Interstate Observation Network (I-24 MOTION) is a new instrument for traffic science located near Nashville, Tennessee. I-24 MOTION consists of 276 pole-mounted high-resolution traffic cameras that provide seamless coverage of approximately 4.2 miles I-24, a 4-5 lane (each direction) freeway with frequently observed congestion. The cameras are connected via fiber optic network to a compute facility where vehicle trajectories are extracted from the video imagery using computer vision techniques. Approximately 230 million vehicle miles of travel occur within I-24 MOTION annually. The main output of the instrument is vehicle trajectory datasets that contain the position of each vehicle on the freeway, as well as other supplementary information such as vehicle dimensions and class. This article describes the design and creation of the instrument, and provides the first publicly available datasets generated from the instrument. The datasets published with this article contains at least 4 hours of vehicle trajectory data for each of 10 days. As the system continues to mature, all trajectory data will be made publicly available at i24motion.org.

Fire design approach for modern vehicles with combustion or electrical engine

AbstractDue to climate changes and environmental considerations, the current transportation changes to modern vehicles with different vehicles models and engine types. Especially vehicles with alternative types of drive, such as electrical vehicles, are increasing. This raises the question of whether modern vehicles, such as electric vehicles, lead to an increased fire risk as well as an increased heat release rate (HRR). In this article, a new fire design approach for modern vehicles is presented to evaluate the fire risk of electric vehicles compared to vehicles with combustion engines with respect to the fire resistance of the structural elements in open car parks. For this purpose, HRRs of different vehicles are analyzed and an approximated approach for modern vehicles is derived. The methodology can be used for performance‐based design, where the HRR plays a fundamental role. Furthermore, modeling approaches of the vehicle dimensions are presented, which are based on statistical data of the German Federal Motor Transport Authority. The vehicle dimensions are used to determine the fire spread time between vehicles using a parameter study. Based on the statistical data analyses and the parameter studies, this article provides a new fire design approach for modern vehicles in fire.

Convolutional Neural Network-Based Approximation of Coverage Path Planning Results for Parking Lots

Parking lots have wide variety of shapes because of surrounding environment and the objects inside the parking lot, such as trees, manholes, etc. In the case of paving the parking lot, as much area as possible should be covered by the construction vehicle to reduce the need for manual workforce. Thus, the coverage path planning (CPP) problem is formulated. The CPP of the parking lots is a complex problem with constraints regarding various issues, such as dimensions of the construction vehicle and data processing time and resources. A strategy based on convolutional neural networks (CNNs) for the fast estimation of the CPP’s average track length, standard deviation of track lengths, and number of tracks was suggested in this article. Two datasets of different complexity were generated to analyze the suggested approach. The first case represented a simple case with a working polygon constructed out of several rectangles with applied shear and rotation transformations. The second case represented a complex geometry generated out of rectangles and ellipses, narrow construction area, and obstacles. The results were compared with the linear regression models, with the area of the working polygon as an input. For both generated datasets, the strategy to use an approximator to estimate outcomes led to more accurate results compared to the respective linear regression models. The suggested approach enables us to have rough estimates of a large number of geometries in a short period of time and organize the working process, for example, planning construction time and price, choosing the best decomposition of the working polygon, etc.

Efficiency of ferromagnetic shielding of superconducting coils of high-speed maglev crew

Background: Magnetic levitation transport with combined traction, suspension and guidance systems based on superconducting coils (SCC) allows reaching speeds of up to 500600 km/h with a very significant (up to 150200 mm) air gap, which is an important factor in ensuring the safety of high-speed transportation. However, SCC are a source of strong external magnetic fields, which, in conditions of limited crew dimensions, can have a harmful effect on both passengers and on-board auxiliary equipment.
 Aim: to analyze the external magnetic fields of the SCC systems for traction, suspension and direction of maglev vehicles and the effectiveness of ferromagnetic screens as a means of ensuring the electromagnetic safety of passengers and the electromagnetic compatibility of the SCC with other onboard equipment.
 Materials and methods: to achieve this goal, methods of analytical and numerical modeling of the magnetic fields of the SCC using modern software packages were used. As a prototype of the combined magnetic system of traction, suspension and direction, the system of the MLX-L0 maglev vehicle, which is undergoing pilot commercial operation at the Yamanashi test line (Japan), was adopted.
 Results: it is shown that the value of the external magnetic fields of the SCC of the traction and guiding systems in the passenger cabin of the prototype crew exceeds the maximum permissible levels established by domestic and foreign regulatory documents, both without shielding and with passive shielding with flat steel sheets.
 Conclusion: passive shielding of the SCC with steel sheets, including multilayer ones, does not provide the required reduction in the level of external magnetic fields for a given vehicle dimensions.

IMPROVEMENT OF THE WEIGHT AND DIMENSIONAL CONTROL OF MOTOR VEHICLES ON THE HIGHWAYS OF THE REPUBLIC OF KAZAKHSTAN

The purpose of this article is to develop an automated system for monitoring the weight and size indicators of cars on the highways of Kazakhstan. The advantages of automated weighing systems of transport systems used on the world's highways are analyzed. The hardware architecture of the system with remote processing of weight norms by motor vehicles has been developed. The effectiveness of the use of stationary posts for monitoring weight indicators and measuring the overall dimensions of vehicles is substantiated. As a result of the study, a comparative analysis of advanced technologies for weighing trucks in traffic was performed.

Presenting the Self-Healing Potential Model by Induction Heating Method in Warm Asphalt Mixtures by Artificial Neural Network

The increasing number of vehicles in the world and the increase in the dimensions of light and heavy vehicles with different combinations, including simple and compound axles, have caused various types of damage in the asphalt, which affects the performance of the roads and requires a suitable pavement. For this reason, engineers try to improve the performance of asphalt mixture in different ways and increase their useful life. Cracking is one of the main failure modes of asphalt pavements. Fatigue cracking is the most common form of asphalt failure and is one of the important factors in reducing the life of road pavements. The purpose of this research is to investigate the index of self-healing potential (HI) of asphalt mixtures containing activated carbon and zycotherm by induction heating method and modelling by artificial neural network. First, by making warm mixture asphalt samples containing activated carbon, self-healing by induction heating method was provided in the pavement, and then the effect of traffic loading and environmental conditions simultaneously in terms of changes in loading parameters, taking into account the conditions of the service life. The results show that the use of activated carbon increases the values of shear modulus. It also improves the properties of modified bitumen at all temperatures. The resistance of the asphalt mixture against breaking and cracking, as well as the maximum force tolerance at the temperature of -16°C is higher than at the temperature of 25°C, which is one of the reasons for the reduction of flexibility of bitumen at low temperature. Also, for modelling, perceptron multi-layer neural network (MLP) with 9 input variables, three hidden layers and one output layer has been used. The results showed that the explanation coefficient of the neural network model for training, validation and evaluation data was 0.99717 for training, 0.62053 for validation and 0.9301 for testing. These values correctly show the high fitting ability of the proposed neural network model. Also, the lowest value obtained for the mean squared error is 4.9223x10^(-5) and in epoch 14.

Evaluating the Factors Affecting Electric Vehicles Adoption Considering the Sustainable Development Level

Electric vehicles are an important part of governments’ environmental policies, and therefore understanding the factors affecting their market share is very important. So, this research is designed to investigate the factors affecting electric vehicle adoption, considering the effects of the COVID-19 pandemic and sustainable development level. Effective factors have been investigated in three categories. One is the characteristics of electric vehicles; the other is the impact of the COVID-19 pandemic on demand for these vehicles; and finally, the impact of the level of sustainable development of countries on adopting electric vehicles. Our analysis method is based on grey econometric and grey regression methods. The results show that vehicle dimensions, battery warranty conditions, battery life, and charging facilities are effective factors in the field of vehicle characteristics that can increase the adoption of electric vehicles. Also, the analysis shows that the COVID-19 pandemic has reduced the adoption of electric vehicles. Finally, we have shown that the market share of electric vehicles is higher in countries with a higher sustainable development level because of better economic, social, and cultural infrastructures.

Vehicle-following behaviour in mixed traffic – role of lane position and adjacent vehicle

ABSTRACT In mixed traffic condition, varying vehicle dimensions and lack of lane discipline lead to parallel movement of vehicles in the same lane or between lanes. This results in a condition where the longitudinal response of vehicles gets affected by adjacent vehicles and their configurations. Correspondingly, the adjacent vehicle configurations are significantly influenced by the lane position of subject vehicle. To accommodate this scenario, the study formulates longitudinal acceleration models from trajectory data considering the influence of subject vehicle’s lane position along with adjacent vehicle characteristics. The response under different cases of subject vehicle’s lane position and adjacent vehicle configurations are evaluated. The statistical analysis indicates that the following behavior varies based on lane position of subject vehicle and adjacent vehicle attributes. It is also found that disregarding these attributes can produce significantly erroneous acceleration estimates. These features can improve existing following behavior models and can enhance the realism of the microscopic modeling scheme for mixed traffic conditions.

Estimating vertiport passenger throughput capacity for prominent eVTOL designs

Urban Air Mobility has the potential to substantially reduce travel times in some cases of urban-related transportation. Travel time savings strongly depend on fast processing at vertiports, which presents a key challenge considering demand levels’ vertiports would experience when becoming an established mode of transport. This article sheds light on the passenger throughput vertiport airfields can manage and how the operations are sensitive to changes. One main contribution of this article is the introduction of hourly passenger throughput per area as a performance indicator that allows to compare vertiports of different sizes. VoloCity is studied as a reference vehicle and the resulting space requirement of the carefully specified baseline scenario is 188 square-meters per passenger per hour. A total of 13 prominent eVTOL designs are included in the study from which the current design space between maximum vehicle dimension and number of seats is deducted. The study shows that vehicles with a small maximum dimension yield the highest passenger throughput capacity. CityAirbus performs best (46.3 m2/PAX/h) with a diameter of 7.92 m and Archer Maker performs worst (221 m2/PAX/h) with a diameter of 12.2 m. How the performance indicators can be used as rules-of-thumb in the first-order estimations of vertiport throughput capacity or space requirement is described by means of illustrative examples. The insights presented in this paper might be useful for researches, vehicle developers, and municipalities alike.

Roadway and Traffic Attributes Influencing Occupancy Time of Minor-Road Right-Turning Vehicles at Urban Uncontrolled Intersections

The performance of uncontrolled intersection is usually measured based on delay of the least priority movement. Perhaps, most of the studies assumed single stage crossing and had to overlook additional factors for estimating occupancy time. The present study examines occupancy time under two-stage crossing under the influence of roadway and traffic attributes. Field data for this study are collected at five different isolated intersections. The analysis of field data is performed by observing the movements of individual vehicles from the minor road approach by considering various factors affecting it under mixed traffic conditions. And it was observed that Two-wheelers are tended to encroach into smaller gaps in between the vehicles due to its physical dimension and easy maneuvering followed by threewheelers. The occupancy time is observed had strong correlation with conflicting area, conflicting flow the proportion of U-turning major road traffic, vehicle dimension, and the increase of median width.