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The Northern Sea Route (NSR) is an emerging alternative route to the Suez Canal; however, inconclusive research exists on its benefits and viability. This paper uses a two-stage Delphi approach to collect qualitative data from experts, on what actions Nordic countries[1] can undertake to prepare themselves to enter NSR and capture potential benefits deriving from trading in global transport networks. By conceptually developing a framework based on First Movers Advantage (FMA) and Dynamic Capabilities Theory (DCT), this paper empirically identifies a path to develop capabilities that could allow stakeholders to reduce logistics costs through collaborations in NSR. Our paper has made a twofold contribution, first to literature by linking FMA/DCT in a single framework and elaborating it in a global transportation and logistics context. Second, a practical contribution by identifying how countries along the NSR, and specifically Nordic countries, can capture and maximise its benefits by using the right policy framework. [1] Nordic countries are: Denmark, Norway, Sweden, Finland, and Iceland, as well as the Faroe Islands, Greenland, and Åland (Nordic Co-operation, 2020).

The critical infrastructure system is determined by subsystems essential for the functioning of the state (such as energy, transport, and emergency services). Disruption to the function of these subsystems would have serious effects on state security, the state economy, and the provisioning of the inhabitants’ basic human needs. Links connect these subsystems (i.e., sectors, subsectors, and elements), and these links ensure that certain subsystems are integrated into each other. Their interactions are derived from the type and intensity of the mutual link. The interlinked subsystems can thus be divided into influencing and dependent ones. The aforementioned mutual links in the critical infrastructure system allow, amongst other things, the spread of impacts of disruptive events amongst the subsystems via cascading effects. Disruptions to the performance of an influencing subsystem may have negative effects on a dependent subsystem, resulting in the spread of cascading effects in the critical infrastructure system. Such effects are often difficult to predict, which reduces the responsiveness of the dependent subsystems. Road transport is one of the most significant influences on critical infrastructure subsystems. For this reason, the article focuses on an indication of the negative effects of disruption of road infrastructure elements on dependent subsystems. The article describes the role of road infrastructure in the context of the critical infrastructure system. Defines the dependent subsystems of road infrastructure, categorises the negative effects, and presents a possible approach to assessing the adverse effects of disruption road infrastructure performance on dependent subsystems. First published online 10 February 2022

Owners are facing increased pressure to deliver major infrastructure projects in a timely and cost-efficient manner. Pain from inflation and labor/material short- ages are felt nationwide. To maximize limited budgets, owners are exploring alternative delivery methods. Attendees will learn about the benefits and pitfalls of progressive design-build (PDB) and construction manager/general contractor (CM/GC). Presenters will share best practices for determining if PDB and CM/GC are appropriate for your project and provide case study examples.

Many people outside of traffic engineering are required to conduct a crash history analysis as part of their scoping efforts for non-safety funded projects. Some engineers may not have much experience working with crash data or may not know how best to manipulate it to arrive at meaningful results. Using real-world examples, this presentation will walk through each step in requesting, filtering, diagramming, and interpreting crash data.

Broad Ripple Avenue (College Avenue to Winthrop Avenue) needed large-scale stormwater improvements. With the help of the Lochmueller Group and the Broad Ripple Village Association, Indianapolis DPW perceptively took this opportunity to also improve pedestrian facilities and regional multi-modal connectivity by combining multiple regional projects into one construction contract. This consolidation allowed for a cohesive public message through proactive public involvement. Presenters will share how consensus was built between invested parties through a successful public and private partnership.

Discussion of how and when Carmel implemented raised crosswalks for successful traffic calming and enhanced pedestrian safety.

This session is an updated version of “Traffic Signal Advance Pre-emption Design within 200’ of Active Railroad Crossings,”—a 2012 Purdue Road School presentation. The issue of Traffic Signal Preemption has changed, positively and negatively, for INDOT and the railroads. A review of the updated traffic signal preemption material will benefit designers, operations staff, and local agencies.

Truck automation arrived in the Midwest in 2022 with the advertising of procurement for truck platooning and Level 2 and 4 automations on trucks in operations on I-70. We will discuss the readiness of infrastructure and industry to accept this technology, debunk the headlines on automation, discuss real-world feedback from both technology and trucking industries, and spotlight the partners who are helping INDOT and DriveOhio advance this project.

The Reimagine Pleasant Street project is a multi-year initiative that will result in improved east-west connectivity, accessibility, and safety for the City of Noblesville, while still honoring its urban character and historic features. Participants will learn how the project team addressed the challenges and complexities of completing this $125 million local project in the heart of the city. Construction for phase 1 began in the fall of 2022, and phases 2 and 3 will start in the fall of 2023.

ASCE recently released two new SUE standards—ASCE 38-22 is the updated SUE standard commonly used during the utility coordination process during design, and ASCE 75-22 is the new utility as-built standard that is essential for the accurate location of newly relocated facilities in construction. This presentation will illustrate the interaction and relationship between SUE and utility coordination to enhance project deliverables and reduce risk during construction.

This presentation will go through the environmental process of a recent $125M local project within Noblesville. What are the major differences between the National Environmental Policy Act (NEPA) and State Environmental Policy Act (SEPA) process as it relates to an environmental assessment (EA)? What is required, what is not required, and what is optional? How long does the process take? Join us as we walk through this exciting process and experience.

This presentation will cover how the developments on the Olio Road Corridor have affected Hancock County’s roadway deterioration and construction, revenue and funding, and public involvement.

INDOT is actively pursuing innovative intersection treatments across the state to improve safety and mobility. Traffic analysis of these intersections is critical to ensure they will perform as intended, but can often be complex. This session will explore several best practices for modeling innovative intersections and will highlight commonly overlooked elements that are key to proper traffic analysis.

This session will highlight current IHCP tables, policy tables, request templates, analysis tools, INDOT queue analysis spreadsheet, INDOT detour route summary spreadsheet, hourly day-of-the-week con- version factors, additional modeling efforts, common and repeated mistakes, IHCP exception checklist, and example projects.

The Kentucky Transportation Cabinet (KYTC) responded to one its worst transportation challenges ever when historic flooding struck Appalachia and Eastern Kentucky counties in 2022. The transportation agency responded immediately to the disaster, and in the months following the event, KYTC was charged with assessing bridges for safety, clearing roads and streams, and restoring access to allow responders to reach those in need. New programs were quickly developed to address needs ranging from the installation of temporary bridges to the creation of temporary shelters for displaced residents. During this, C2 Strategic Communications partnered with KYTC to develop a communications campaign to help share important information and inspire hope in the impacted region.

Over the past 2 years, Indiana has been part of a nationwide surge in the number of motor vehicle fatalities and serious injuries. Even before that time, traffic deaths remained stubbornly high in comparison to other industrial peer nations. In 2022, INDOT engaged with stakeholders and partners inside and outside of state government to create a new Strategic Highway Safety Plan (SHSP). The new SHSP is aligned with the FHWA Safe Systems Approach and will help facilitate the changes brought by the Bipartisan Infrastructure Legislation (BIL Act) to state and local safety programs. This presentation will introduce the structure of the new SHSP, how data-driven analysis leads us to these strategies, and action plans to improve roadway safety throughout Indiana.

This session will explore how the Texas Department of Transportation Waco District addressed pedestrian/bicyclist safety and mobility during a multi-year construction project along I-35. This presentation will demonstrate the value of online tools, field implementations, and data collection. Attendees will learn the value of assembling a stakeholder steering committee; counting pedestrian and bicyclists before, during, and after construction; effectively using pavement clings; and using a webpage dedicated to pedestrian/bicyclist updates.

DOT staff and technology resources have the proven potential to help combat human trafficking if DOT employees know the indicators of human trafficking and how to cooperate with requests from agencies for information that can be derived from DOT assets. The Texas A&M Transportation Institute, NCHRP, and the Heart of Texas Human Trafficking Coalition will discuss the intersection of human trafficking with the transportation sector. Attendees will also learn the main components of human trafficking, the basic signs of human trafficking on DOT facilities, and resources to use in their own states.

Pavement management systems (PMSs) have a primary role in determining pavement condition monitoring and maintenance strategies. Moreover, many researchers have focused on pavement condition evaluation tools, starting with data collection, followed by processing, analyzing, and ultimately reaching practical conclusions regarding pavement condition. The analysis step is considered an essential part of the pavement condition evaluation process, as it focuses on the tools used to find the most accurate results. On the other hand, prediction models are important tools used in pavement condition evaluation to determine the current and future performance of the road pavement. Therefore, pavement condition prediction has an effective and significant role in identifying the appropriate maintenance techniques and treatment processes. Moreover, pavement performance indices are commonly used as key indicators to describe the condition of pavement surfaces and the level of pavement degradation. This paper systematically summarizes the existing performance prediction models conducted to predict the condition of asphalt pavement degradation using pavement condition indexes (PCI) and the international roughness index (IRI). These performance indices are commonly used in pavement monitoring to accurately evaluate the health status of pavement. The paper also identifies and summarizes the most influencing parameters in road pavement condition prediction models and presents the strength and weaknesses of each prediction model. The findings show that most previous studies preferred machine learning approaches and artificial neural networks forecasting and estimating the road pavement conditions because of their ability to deal with massive data, their higher accuracy, and them being worthwhile in solving time-series problems.

To model the car-following behavior more accurately, we carried out the molecular similarity analysis between the vehicles on the road and the inert gas system, comparing vehicles with microscopic particles in long and narrow pipes. The complex car-following interaction behavior is simplified into a dynamic process of the follower car that is constantly seeking to maintain the required safety distance from the leading vehicle. Through mathematical derivation of the Lennard–Jones potential function suitable for thermodynamic analysis of inert gas systems, the influence of each variable on the potential energy is clarified, and the existing problems of the existing molecular car-following model are analyzed, referring to the general Lennard–Jones potential function to build the vehicle interaction potential function. Considering the impact of the road wall potential generated by the lane boundary, a car-following model based on Lennard–Jones interaction potential is presented. The simulation test results show that compared with the existing molecular car-following model and IDM model, the average absolute error and root mean square error of the vehicle acceleration results obtained by this model and the actual data are lower, which proves that the vehicle is based on the Lennard–Jones interaction potential. The vehicle-following model based on Lennard–Jones interaction potential has a better fitting effect on the real vehicle-following behavior.

With the growth in global trade and its environmental footprint, sustainable modes of freight movement are increasingly important in today’s globalized world. This study focuses on on-dock rail, where the rail terminal is located within the marine container terminal. On-dock rail has in recent years become an essential mode of transportation to move containers out of congested marine container terminals. This study contributes to the literature by presenting tailored exact solution algorithms for a recently proposed optimization model to optimize the loading of double-stack trains. In particular, a 3-stage solution framework is presented for the case when rail cars have a single well. A complementary solution algorithm for the case when a rail car has multiple wells is also provided. Our results show that computational times can be drastically reduced, from 2+ hours to a matter of seconds, rendering the model suitable for practical use.

Despite the fact that significant research efforts have been made to the traffic flow theory of autonomous vehicles and manual vehicles, few existing studies have incorporated different modes of both vehicles in their analysis. In this study, we develop a cellular automata simulation model to investigate the impact of different modes of autonomous vehicles (autonomous car, autonomous bus, and autonomous micro car) and conventional vehicles (manual car, manual bus, and manual micro car) on the characteristics of traffic flow. A new type of autonomous mode, i.e., autonomous micro car, is investigated in the model to study the effects of this vehicle mode on the overall capacity of the network. Furthermore, two types of lane-changing behavior, i.e., aggressive lane changing and polite lane changing, are incorporated into the model. The results reveal that micro cars (manual and autonomous) have the potential to reduce traffic congestions and increase the capacity or flow rate (vehicles/hour) of the road. Where the average vehicle occupancy is less than 2, if autonomous micro cars are deployed alongside autonomous cars, the flow rate (vehicles/hour) can be increased significantly. The results highlight the significance of the autonomous micro cars to traffic flow, passenger occupancy, and road capacity.

Overfitting in a deep neural network leads to low recommendation precision and high loss. To mitigate these issues in a deep neural network-based recommendation algorithm, we propose a recommendation algorithm, LG-DropEdge, joint light graph convolutional network, and the DropEdge. First, to reduce the cost of data storage and calculation, we initialize user and item embedding in the embedding layer of the algorithm. Then, to obtain high-order interaction relationships to optimize the embedding representation, we enrich the embedding by injecting high-order connectivity relationships in the convolutional layer. In the training phase, DropEdge is used to randomly discard connected relationships (interaction edges) to prevent overfitting. Finally, to reasonably aggregate the embedding results learned on all layers, the weighted average is expressed as the final embedding, so that users can make preferences in the item. We conduct experiments on three public datasets, using two performance indicators; namely, recall and NDCG, are used for evaluation. For the Gowalla dataset, compared with the optimal baseline method, recall@20 and ndcg@20 increased by 2.53% and 2.39%, respectively. For the Yelp2018 dataset, recall@20 and ndcg@20 increased by 6.17% and 5.58%, respectively. For the Amazon-book dataset, recall@20 and ndcg@20 increased by 4.82% and 4.67%, respectively. The results show that LG-DropEdge can not only reduce the degree of neural network overfitting but also improve the recommended results’ precision.

Express buses—characterized by limited stops and sometimes higher frequencies or priority traffic measures—offer a cost-effective and efficient way to boost service convenience and reliability for riders. This paper assesses how the accessibility benefits of express bus route policy are distributed in Montreal, Canada, while providing a pathway for public transportation agencies to assess their policies and plans. To isolate the impact of bus express routes, we use General Transit Speed Specification (GTFS) data, the Open Trip Planner multimodal routing engine, and the 2013 edition of Montreal’s origin-destination survey to contrast travel time and accessibility at the trip and census-tract levels under two scenarios: one with the existing, complete network and the second a counterfactual scenario with no express bus routes. Our results indicate that bus express routes enable an overall increase in accessibility for the overall population. However, the accessibility benefits do not accrue evenly, as expected, but also tend to benefit a more significant number of higher incomes. This occurs despite the location of low-income populations in some outlying areas of the city, which express bus routes are supposed to serve. This paper closes with policy recommendations that help planners balance economic, environmental, and equity goals, perhaps one of the most complex challenges they face nowadays.

This study addresses uncertainty in a transportation network by proposing a trilevel optimization model, which improves resiliency against uncertain disruptions. The goal is to minimize the total travel time by designing a resilient transportation network under uncertain disruptions and deterministic origin-destination demands. The trilevel optimization model has three levels. The lower level determines the network flow, and the middle level assesses the network’s resiliency by identifying the worst-case scenario disruptions that could lead to maximal travel time. The upper-level takes the system perspective to expand the existing transportation network to enhance resiliency. We also propose a formulation for the network flow problem to significantly reduce the number of variables and constraints. Two algorithms have been developed to solve the trilevel model. The results of solving the highway network in Iowa show that the trilevel optimization model improves the total travel time by an average of 41%.

This research considers the aspects of decision-making according to the airport activities. The decision about airport planning and management should be comprehensive and operative and of course, the assessment of alternative decisions is necessary. The purpose of this research is to highlight the role of simulation modelling at the stage of airport development. The authors present the methodology of a model-driven decision-making approach and then describe 2 cases of using simulation for Riga International Airport (RIX) development. The 1st case study is used for analysis possibility of the development of the airport’s surrounding territory. The planned massive development of RIX and the surrounding area requires detailed analysis for increasing its positive impact on regional and national business economics, social aspects, business and the environment. The 2nd case supports decision-making for the needs of the terminal reconstruction, presents a helpful tool for visualization of the tendencies in the future, and allows the analysis of the different infrastructure layouts. Both cases give the possibility to predict the situation and evaluate the service provided for passengers (travellers) of the airport. Simulation modelling allows to study complex system – airport and evaluate direct and indirect impacts of planned reconstruction. First published online 20 January 2022

Intelligent connected vehicles (ICVs) have become the focus and development direction of the automobile industry. As a flexible intelligent terminal, ICVs will become a necessary part of the intelligent transportation system. The routes of developing ICVs based on “vehicle to X” (V2X) can effectively alleviate the demands of vehicles for intelligent functions and cut related research costs, accelerating commercialization of ICVs and leading to many social benefits. At present, China has made it clear to develop ICVs based on V2X, which requires simultaneous intelligent upgrades of vehicles and transportation infrastructure. Therefore, intelligent upgrades of transportation infrastructure must match the functional requirements of ICVs. In addition, the investment in intelligent upgrades of transportation infrastructure is mainly from the government, so the costs must be controlled reasonably to find the most cost-effective upgrade route. In this paper, the types of intelligent transportation infrastructures were determined by sorting out the demands of ICVs for transportation infrastructure, and the deployment methods and upgrade routes of intelligent transportation infrastructures were designed. Then, the cost evaluation model for intelligent upgrade of transportation infrastructures was established, based on which, the cost evaluation of different intelligent upgrade routes of transportation infrastructure was carried out in closed highway and open urban road scenarios to determine the optimal route. Besides, the key elements affecting the cost of transportation infrastructure upgrades were identified, and their impact degrees on transportation infrastructure upgraded were analyzed by scenario analysis. The results show that the intelligent transportation infrastructure for advanced ICVs mainly includes communication base stations, roadside units (RSUs), vision sensors, millimeter-wave radars, laser radars (LiDARs), meteorological sensors, intelligent signal machines, edge computing servers, and cloud computing centers. The route of deploying primary intelligent transportation infrastructure at first and then directly upgrading them to advanced level can well match the functional requirements of ICVs on the basis of lower costs. The costs of RSUs, LIDARS, and edge computing servers as well as data transmission rate of 5G are key elements affecting the costs of intelligent upgrades of transportation infrastructure.

At automated container terminals (ACTs), twin automated stacking cranes (ASCs) can carry out the tasks—store and retrieve containers simultaneously in a yard block using a handshake bay, where a primary ASC stacks the container at the handshake bay and the other crane carries it to the destination bay. Although the handshake bay increases the degree of crane utilization, the ASCs will interfere with each other at the bay, decreasing the stacking efficiency. This study formulates a mixed-integer linear program (MILP) to position the handshake bay and simultaneously schedule the twin ASCs to minimize the tasks’ makespan. The proposed formulation considers the safe time interval to avoid crane collisions during adjacent crane movements. To solve the model, we developed a random-key genetic algorithm with a priority-based decoding scheme to optimize the task sequences and tasks assigned to the cranes. The priority-based GA can always generate feasible solutions by ranking the container-handling tasks. Numerical experiments prove that the safe temporal interval affects the makespan and the handshake bay’s position. An optimal handshake bay reduces 35% of the makespan compared with a nonoptimal bay, and the proposed algorithm is competitive compared with the on-the-shelf MILP solver and can solve medium- and large-scale instances in short computing time with gaps lower than 5% compared with ideal solutions.

This study proposes a multiobjective mixed integer nonlinear programming model for a last-mile shuttle service to improve bus commuters’ travel time reliability. The approach aims to assign the routes that pick up the transit passengers located at the different stops by shuttle service. A bilevel optimization model is established: the upper model of route design considers the tradeoff between time cost and fare cost when some of the passengers take the shuttles, and the lower model assigns the demand of transit passengers. The proposed model effectively captures the reliability of travel time because related parameters are estimated by a statistical fitting test with a large number of real-world bus geographic information system (GPS) data. Moreover, dynamic demand diverting from conventional transit to shuttle service and travel time reliability, including passenger in-vehicle time (IVT) and waiting time (WT), are fully considered in this model. Since the task is a nonlinear programming model, a two-stage algorithm combined with linearization processing is presented to find an optimal solution. Finally, from the case study of Zhongguancun Software Park zone in Beijing, it is indicated that when last-mile shuttle service is provided, bus passengers’ travel time reliability of last-mile trips can be improved by 14%. The study can be an important reference for improving the low reliability widely existing in the current transit commuters’ last-mile problem.

In mixed traffic with autonomous vehicles, the relationship between speed and lane-changing behavior is an important basis for mixed traffic control. In this study, we use empirical, simulation, and data-driven methods to study the relationship between speed and lane change rates in mixed traffic under different autonomous vehicle penetration rates. We use the empirical data to establish the corresponding road simulation models. Based on the simulation model, the traffic flow simulation experiments under the conditions of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 90% penetration rate of autonomous vehicles were carried out. The analysis of the simulation results found that: (1) the penetration of autonomous vehicles into the road has a positive impact on the lanes far away from the entrance and exit, while the impact on the lanes closer to the entrance and exit is not obvious. (2) Lane-changing behavior has effectively decreased with the penetration of autonomous vehicles, but it is not obvious when the penetration rate exceeds 10%, and there is no significant drop in the lane connecting the entrance and exit. (3) There is a linear relationship between speed and lane-changing rate. Under different penetration rates, the data-driven analysis is used to perform multiple linear regressions, and the regression formula fits are all above 0.7. Based on the above findings, the linear formula of the fitting is proposed, and the value interval of the parameters in different states is given as well. Due to the small changes in the parameter values under different permeability conditions, the model has a certain degree of stability. The speed-lane change rate model proposed in this study can better describe the relationship between the speed of the ring-shaped urban expressway and the lane-changing behavior in the mixed traffic environment with the larger traffic flow.

Introduction. External forces from the working implements of tractor units or road construction machines often lead to uncontrollable displacement from a given trajectory. This movement is the sum of controlled movement and uncontrolled displacement (start of moving). The lack of adequate models of displacement (start of movement) is the reason for the insufficient study of uncontrolled movement at the present time. The goal is to build a model of uncontrolled displacement under the action of an external force, which allows obtaining the maximum value of the external force, depending on its direction.Materials and methods. The mathematical model of limiting equilibrium is built on the example of a bulldozer unit with a skewed blade. The force factors of the interaction of the mover with the soil included in the model were formed on the basis of the mathematical theory of friction. The model was improved by introducing different coefficients of adhesion in the longitudinal and transverse directions. This made it possible to take into account the anisotropy of the interaction of the propeller with the ground.Results. The hodograph of the limiting shift force was constructed as a result of a numerical experiment. His analysis showed that the shift force is equal to the adhesion limit only in the case of translational shear. In all other cases (instantaneous rotational shear) the value of the ultimate shift force is less than the adhesion limit. Anisotropy further reduces the value of the limiting external shear force and rotates the hodograph towards the lowest friction coefficient.Conclusion. The hodograph allows calculating the value of the limiting shear force and assessing the possibility of an uncontrolled deviation of the machine from a given trajectory. The resulting model will subsequently be used to build a control system for the operation of an unmanned vehicle, taking into account the external influence from the working tools.

Introduction. In the Siberian Federal Area, the abundance of clay soils sources with above-optimal moisture content significantly complicates the technology of operations, reduces the speed of work, and makes some reserves unusable. To solve these problems, the use of quicklime in preparation for quarrying of clay soils with above-optimal moisture content was considered.The experimental studies have been carried out on the dynamics of soil drainage (lightweight dust loam) from drilling a well filled with lightweight lime (concentrated lime method). During this study, three experiments were carried out on soil masses with different initial humidity, two of which were carried out under the influence of lime and one (control) without the effect thereof.In addition, the change in optimum humidity and maximum density of dry soil during lime injection into loamy soil (dosage from 2% to 6% by mass) was evaluated. On the basis of the results obtained and the analysis of literature sources rational distances between slots (wells) are justified when using concentrated lime action technology to drain soils with increased humidity in quarries.Negotiations and conclusions. On the basis of the results obtained in the course of the study, it can be concluded that drying the soil with lime by the proposed concentrated method has a positive effect on the physical and mechanical characteristics of the soil.

Introduction. An automobile vehicle consists of a large number of parts that affect traffic safety in different ways. The elements that critically affect the safety of the vehicle include automobile pneumatic tires. Their technical condition is currently being assessed visually, without the use of special equipment. This diagnostic method does not provide detection of hidden tire damage. This article describes the proposed method of diagnosing pneumatic tires of passenger cars, as well as the scheme of the stand for its implementation.Materials and methods. Based on previous studies, it was proposed to use the static stiffness of automobile tires as a diagnostic parameter when assessing their technical condition. To implement the use of this diagnostic parameter, a new method for assessing the technical condition of tires was proposed. It consists in determining and comparing the values of the static stiffness of the tire at its various points with the average stiffness value at all measurement points. To implement this method in the laboratory, a schematic diagram of the stand was proposed.Results. In accordance with the proposed scheme of the stand, a volumetric model of the stand was developed for the implementation of the proposed method in laboratory conditions, and the frame of the stand was made and its main elements were selected. As a converter of the rotational movements of the potentiometer handle into the electronic signal, it was decided to use the Arduino Uno R3 analog-to-digital converter. Software was also developed to automate the reading and processing of bus diagnostic results.Discussion and conclusions. The proposed method of tire diagnostics and the stand implementing it can increase the efficiency and simplicity of assessing the technical condition of pneumatic tires of passenger cars. Further research is needed to assess the effectiveness of the proposed solutions.

Introduction. The change of a winter season to a summer season is accompanied by a sharp increase in accidents on the roads; at the same time, the number of accidents is directly dependent on the air temperature. The reason for this is the adverse effects of high temperatures and solar activity, which create a “steam room” effect in the car interior.This article analyzes the thermal fields of the driver, who is in the car, in the hot season with different modes of compensation of the thermal effect. High temperatures can have a significant negative impact on the driver’s condition. This is due to the relevance of the issue under consideration.Materials and methods. In the work, the temperature and illumination were measured using an electronic TP101 thermometer and a Megeon-21550 luxmeter. Visualization of the thermal fields of the external and internal space of the car was made using a Testo 875 thermal imager. Upon completion of the survey of thermal fields, the data was processed using specialized software.Results. The main result of the work is the characteristic and distribution of the thermal fields of the driver, who is in the car, with an open window, with air conditioning and a climate control system in high ambient temperatures, which will allow to develop measures to improve the reliability of the driver and minimize accidents. These results represent the scientific novelty of the study.Discussion and conclusion. The application of the results of the work will make it possible to develop recommendations for complex motor transport enterprises on the organization of their technical and operational services, taking into account temperatures in the summer

Introduction. the article deals with the issues of the use of technological waste generated during rocks crushing.Materials and Methods. In the research the rock crushing screenings from the Rezhevsky crushed rock plant and dolomite screenings from the Satkinsky crushed rock plant were used. The data on the physical-mechanical properties of crushing waste is presented, as well as a study of dusty rock cuttings made with a Fritsch Analysette 22 laser particle size analyser. The structure of concrete was analyzed by JEOL JSM-6510 electron microscope.Results. The studying results of heavy weight cement concretes of classes B22.5 - B40 with crushed stone are presented in the article. To control the properties of concrete an MC-PowerFlow 3100 hyperplasticizer additive and an air-entraining additive Centrament Air 202 were used. The phase composition of the contact zone between the cement stone and the aggregate - granite screening has been investigated.Conclusion. compositions of heavy concrete have been developed with the use of crushed stone screenings and chemical additives to regulate concrete properties. A pilot batch of reinforced concrete products was produced at the Rotor reinforced concrete plant in Vinzili, Tyumen Region.

With the increasing application and utility of automatic identification systems (AISs), large volumes of AIS data are collected to record vessel navigation. In recent years, the prediction of vessel trajectories has become one of the hottest research issues. In contrast to existing studies, most researchers have focused on the single-trajectory prediction of vessels. This article proposes a multiple-trajectory prediction model and makes two main contributions. First, we propose a novel method of trajectory feature representation that uses a hierarchical clustering algorithm to analyze and extract the vessel navigation behavior for multiple trajectories. Compared with the classic methods, e.g., Douglas–Peucker (DP) and least-squares cubic spline curve approximation (LCSCA) algorithms, the mean loss of trajectory features extracted by our method is approximately 0.005, and it is reduced by 50% and 30% compared to the DP and LCSCA algorithms, respectively. Second, we design an integrated model for simultaneous prediction of multiple trajectories using the proposed features and employ the long short-term memory (LSTM)-based neural network and recurrent neural network (RNN) to pursue this time series task. Furthermore, the comparative experiments prove that the mean value and standard deviation of root mean squared error (RMSE) using the LSTM are 4% and 14% lower than those using the RNN, respectively.

The aim of this study was to explore the bus operating state of the city bus passenger corridor, taking the minimum bus operating cost and passenger travel cost as the objective function, taking passenger flow demand and operating income as the constraint, and considering the average speed change of the bus line in the bus corridor at different times. This paper proposes a dynamic optimization model of bus route schedule based on bus Integrated Circuit Card (IC Card) data. The optimization variable is the departure frequency of the candidate lines. To solve the model, a dynamic departure interval optimization method based on improved Genetic Algorithm (GA) was designed under different decision preferences. The method includes the calibration of generalized cost functions for passengers and bus companies and grasps the characteristics of bus operating speed changes and the design of departure strategies under different decision preferences. The validity and applicability of the proposed method are verified by a numerical example. We mainly carried out the following work: (1) Dynamic analysis of the time dimension of the bus departure interval takes into account the changes in passenger time characteristics during peak periods. (2) Seven schemes of weight ratio of passenger waiting time cost and bus operation cost were designed, and the departure intervals with different benefit orientations of passengers and operators were discussed, respectively, so as to select the corresponding departure schemes for decision makers under different decision preferences. The results show that (1) the total cost of the 7 different weighting schemes is lower than the actual value by 6.90% to 18.20%; (2) when decision makers need to bias the weight to the bus company, the weight ratio α : β between passengers and bus company is 0.25 : 0.75 which works best. The frequency of departures has been reduced by 6, and at the same time, the total optimized cost is reduced by 18.2%; (3) when decision makers need to bias the weight to the passengers, the weight ratio α : β between the passengers and bus company is 0.75 : 0.25 which works best. The frequency of departures has been increased by 19, and at the same time, the total optimized cost is reduced by 17.7%; and (4) when decision makers consider passengers and bus companies equally, the weight ratio α : β between passengers and bus companies is 0.5 : 0.5, the optimization cost is the closest to the actual cost, the optimization cost is reduced by 6.9%, and the frequency of departures has been increased by 5. The results show that the model in this paper provides a new idea for the information mining of bus routes in the research based on the bus IC Card data and provides an effective tool for the management of different operation decision preferences.

Many countries have made great efforts to boost the use of electric vehicles in recent years; for example, advanced countries including Norway and the Netherlands in Europe and the United States have enhanced people’s willingness to use electric vehicles by means of appropriate subsidies and suppression of private vehicles. In Asia, Taiwan has been promoting the policy of replacing traditional fuel two-wheeled vehicles (FTWVs) with electric two-wheeled vehicles (ETWVs) and strengthening the policy by means of replacing a large number of old FTWVs and subsidizing the purchase of ETWVs. This study took college students as the subjects, as they were the first potential group to buy ETWVs, and their concept of environmental sustainability can be shaped for cultivating vehicle use habits. This study applies a questionnaire to probe into the ETWV usage preferences of college students and explores the significant factors affecting college students’ purchase of ETWVs. This study uses a mixed logit (MXL) model for estimation. The results of model estimation show that those who are younger, have higher income, have good experience in using ETWVs, and are in user-friendly external traffic environments, are more inclined to choose ETWVs. In the future, government units can formulate policies to promote ETWVs according to the characteristics of different relevant factors.

To analyze the impact of different proportions of connected automated vehicles (CAVs) on fuel consumption and traffic emissions, this paper studies fuel consumption and traffic emissions of mixed traffic flow with CAVs at different traffic scenarios. Firstly, the car-following modes and proportional relationship of vehicles in the mixed traffic flow are analyzed. On this basis, different car-following models are applied to capture the corresponding car-following modes. Then, Virginia Tech microscopic (VT-micro) model is adopted to calculate the instantaneous fuel consumption and traffic emissions. Finally, based on three typical traffic scenarios, a basic segment with bottleneck zone, ramp of the freeway, and signalized intersection, a simulation platform is built based on Python and SUMO to obtain vehicle trajectory data, and the fuel consumption and traffic emissions in different scenarios are obtained. The results show that (1) In different traffic scenarios, the application of CAVs can reduce fuel consumption and traffic emissions. The higher the penetration rate, the more significant the reduction in fuel consumption and traffic emissions. (2) In the three typical traffic scenarios, the advantages of CAVs are more evident in the signalized intersection. When the penetration rate of CAVs is 100%, the fuel consumption and traffic emissions reduction ratio is as high as 32%. It is noteworthy that the application of CAVs in urban transportation will significantly reduce fuel consumption and traffic emissions.

China has already committed to peaking carbon dioxide emissions by 2030 and achieving carbon neutrality by 2060 (referred to as the 30·60 Target), which has brought both daunting challenges and great opportunities to the automobile industry in China. However, there is still a lack of comprehensive and in-depth studies on the challenges, paths, and strategies for reducing carbon emissions to fulfill the 30·60 Target in automobile industries. Therefore, this paper proposes low-carbon development strategies for China’s automobile industry. This study’s method is to integrate the results from different literature to summarize the status, challenges, opportunities, and refine the coping strategies for carbon emission of the automobile industry. The results indicated that the paths for achieving the 30·60 Target include joint carbon emission reduction by upstream and downstream enterprises inside the industry. It also needs cross-industry and cross-sector coordinated decarbonization outside the industry. Meanwhile, the low-carbon policy and regulation system should be established to provide a direct driving force and fundamental guarantee for the low-carbon development of China’s automobile industry.

Different human-machine collaboration modes and driving simulation tests with the orthogonal method considered are designed for a series of typical intelligent highway landscapes. The feedback of drivers under different interaction modes is evaluated through NASA-LTX questionnaire, driving simulator, eye tracker, and electroencephalograph (EEG). This optimal interaction mode (including voice form, broadcasting timing, and frequency) of each driving assistance scene in CVI (Cooperative Vehicle Infrastructure) environment under the conditions of high and low traffic is determined from subjective and objective perspectives. In accordance with feedback of these subjects on each set scene, the voice information structure of each assistance mode plays the most important role on drivers followed by the broadcasting timing and frequency. These broadcasts which provide good effects include scenarios such as various assistance scenes at curves and an early warning timing at a long-distance trip as well as a high early warning frequency; in addition, as for an exit-tip assistance scenario, a voice mode assistance is preferred; and for various speed assistance scenes, the beep mode is better. Furthermore, it is found that, at a higher traffic level but a short-distance trip, an early warning timing is favored generally for various scenes while under a low traffic level, a long-distance early warning timing is better.

This study aims to investigate the impacts of perception of infrastructure, sociodemographic characteristics, frequency of road use, and road user perception on safety, comfort, and chaos with respect to shared spaces. The case study area was the Via Maqueda, a shared street in Palermo, Italy. A face-to-face survey was conducted and the answers of 200 of the participants, who use three active travel modes, namely, walking, cycling, and micromobility, were analysed. The results obtained from the ordered logit models suggest that one-unit higher perception of infrastructure will increase safety and comfort perceptions for both walking and cycling. Females feel less safe while walking and less comfortable while cycling at shared spaces compared to males. Increasing the age group by one unit will decrease the safety and comfort perceptions for walking. The participants who use the shared spaces more frequently perceive that they feel more comfortable with cycling. Participants, particularly males, find the shared spaces less chaotic for walking when the perception of infrastructure is higher. Regarding the micromobility use at shared spaces, females feel less comfortable compared to males while using micromobility.

With the development of technology, shared autonomous vehicles may become one of the main traffic modes in the future. Especially, shared autonomous vehicle reservation system, commuting, and other trips with fixed departure time mostly submit their travel requests in advance. Therefore, it is important to reasonably match shared autonomous vehicles and reservation demands. In this paper, reservation requests are divided into short-term and long-term requests by inputting requests in a more realistic way. An integer linear programming model considering operator scheduling cost and system service level is established. A detailed scheme considering rolling horizon continuity and ridesharing is used to improve the dispatching result. Based on traffic data in Delft, the Netherlands, 164 scenarios are tested in which the parking cost, fuel cost, ridesharing effect, service level, and network size are analyzed. The results show that a better relocation and ridesharing matching scheme can be obtained when the rolling horizon is small, while the overall effect is better when the rolling horizon is large. Moreover, the buffer time, distance, and travel time limit for vehicle relocation should be selected according to the request quantity and the calculation time requirement. The result can provide a suggestion for the dispatching of shared autonomous vehicle reservation system with ridesharing.

In traffic scenarios, vehicle trajectories can provide almost all the dynamic information of moving vehicles. Analyzing the vehicle trajectory in the monitoring scene can grasp the dynamic road traffic information. Cross-camera association of vehicle trajectories in multiple cameras can break the isolation of target information between single cameras and obtain the overall road operation conditions in a large-scale video surveillance area, which helps road traffic managers to conduct traffic analysis, prediction, and control. Based on the framework of DBT automatic target detection, this paper proposes a cross-camera vehicle trajectory correlation matching method based on the Euclidean distance metric correlation of trajectory points. For the multitarget vehicle trajectory acquired in a single camera, we first perform 3D trajectory reconstruction based on the combined camera calibration in the overlapping area and then complete the similarity association between the cross-camera trajectories and the cross-camera trajectory update, and complete the trajectory transfer of the vehicle between adjacent cameras. Experiments show that the method in this paper can well solve the problem that the current tracking technology is difficult to match the vehicle trajectory under different cameras in complex traffic scenes and essentially achieves long-term and long-distance continuous tracking and trajectory acquisition of multiple targets across cameras.

Virtual evaluation of automotive safety with variation in occupant posture and shoulder belt fit is gaining importance, and there is a need of methods facilitating analysis of occupant postures in driving studies. This study is aimed to develop an AI-based computer vision method to automatically quantify occupant posture and shoulder belt position over time in a car. Traceable defined key points on the occupant were related with the shoulder belt and quantified over time in real 3D coordinates by predefined key measurements, utilising the underlying spatial information of a Intel RealSense 3D Camera. The key points are defined as traceable key points relevant to relate the occupant to the vehicle environment and to estimate shoulder belt position. Key point prediction results suggest an average deviation of around 1cm per coordinate, which enable a reliable spatial categorization of the respective tracked occupant by analyzing the key measurements. This method providing continuous information of the occupant position and belt fit will be useful to identify common occupant postures as well as more extreme postures, to be used for expanding variations in postures for vehicle safety assessments.

The development of international cargo transportation has been relevant since the emergence of the international division of labor. Billions of tons of goods of various names, values and volumes are transported across the borders of the Russian Federation every year. This paper examines the Eurasian Economic Union international transportation system, its transport system integration, and the formation of a common transport space. The authors analyzed the international transport market state and conditions and the level of containerization. The transport system is considered the country's economy "circulatory system", which makes it a key link in the implementation of economic reforms in the country. The transport industry has social significance, which also determines the specifics of the phased market transformations. The development of international multimodal container transportation is becoming a new trend in the development of the transport service market.

This paper considers LEO satellite- and cache-assisted UAV communications for content delivery in terrestrial networks, which shows great potential for next-generation systems to provide ubiquitous connectivity and high capacity. Specifically, caching is provided by the UAV to reduce backhaul congestion, and the LEO satellite supports the UAV's backhaul link. In this context, we aim to maximize the minimum achievable throughput per ground user (GU) by jointly optimizing cache placement, the UAV's resource allocation, and trajectory while cache capacity and flight time are limited. The formulated problem is challenging to solve directly due to its non-convexity and combinatorial nature. To find a solution, the problem is decomposed into three sub-problems: (1) cache placement optimization with fixed UAV resources and trajectory, followed by (2) the UAV resources optimization with fixed cache placement vector and trajectory, and finally, (3) we optimize the UAV trajectory with fixed cache placement and UAV resources. Based on the solutions of sub-problems, an efficient alternating algorithm is proposed utilizing the block coordinate descent (BCD) and successive convex approximation (SCA) methods. Simulation results show that the max-min throughput and total achievable throughput enhancement can be achieved by applying our proposed algorithm instead of other benchmark schemes., 14 pages, 6 figures

Every year, many road accidents occur on Polish roads, in which many people lose their lives and health. Therefore, an attempt was made to analyze road accidents in the Piła poviat. The source of the analysis were the authors' observations and statistical data. This study was conducted on a sample of 250 inhabitants. Hence, a questionnaire was used. Most people, more than half, about 56%, travel by car because it is a more convenient and faster means of transport. While 35% of respondents stated that they feel relatively safe on the roads. A majority, 65%, of the respondents did not participate in a road accident. Further, 60% of the respondents replied that there were many accidents in the Piła poviat, and only 11% answered that there were not many accidents. According to the respondents, the biggest cause of the accidents is alcohol, inattention of drivers and haste. Despite the information, advertisements, scale of these accidents, and opinions of family and friends, people still drive under the influence of alcohol. Year by year, the number of accidents on the roads of the Piła poviat is low, but still considerably high. There is no best way to stop this from happening. In Piła itself, circular intersections have been introduced to improve safety, such an operation is one of the methods for smoother traffic. Additionally, in residential areas, there are more speed bumps to reduce the speed of vehicles. The conclusions obtained in this article can be successfully implemented, not only in other cities in Poland but also in Europe as well.

The necessity of a positioning service for various ground handling assets is key to improving airport performance. Reported in this article is a system named “Ground Eye”, designed to be a test of a possible implementation of the independent LTE-based communication system and GNSS-based location services. The test campaign used a total of nine prototype devices for a period of one month at Gdańsk airport (Poland). The main goal of this demonstration was to verify the possibility of using the GNSS/LTE system as a fast-deployment option in the airport environment, as well as to evaluate its positioning and communication capabilities in conjunction with React.JS/Deck.GL/Node.JS dedicated application. The test campaign verified that even with simple processing and relatively simple single-frequency measurements, multi-constellation GNSS receivers, it is possible to obtain location with precision reaching better than 2.5 metres. This precision should be good enough for all ground handling operations at modern airports, without the need for additional fixed infrastructure.

In recent years, the research on ship behavior and ship berthing behavior is a hot topic in the navigation theory research, but the research on ship berthing behavior evaluation is relatively less. Based on the navigation theory, the characteristics of ship berthing behavior (including course, course changes, speed, speed changes and ship position) are extracted, and the berthing behavior evaluation index system is established. According to the characteristics of each behavior, the mathematical description is given for quantitative analysis. Based on the principle of “safety, stability and efficiency”, the evaluation standard is determined for each evaluation index, and the evaluation model is established. The Z-score method is used to standardize the evaluation index data, and the critical method is used to calculate the objective weight of each evaluation index; finally, the model is used to get the evaluation results of each berthing behavior. In this paper, the evaluation model is tested by using the one month’s AIS (Automatic Identification System) berthing data of Tianjin port, and the evaluation results are in line with the actual navigation.