Transportation Management System Research Articles

Effect of Changing a Traffic Control Device Color on Driver Behavior and Perception across Different Age Groups

The use of express lanes (ELs) in freeway traffic management has seen increasing popularity throughout the United States, particularly in Florida. These lanes aim at making the most efficient transportation system management and operations tool to provide a more reliable trip. An important component of ELs is the channelizing devices used to delineate the separation between the ELs and the general-purpose lane. With the upcoming changes to the FHWA Manual on Uniform Traffic Control Devices, this study provided an opportunity to recommend changes affecting safety and efficiency on a nationwide level. It was important to understand the impacts on driver perception and performance in response to the color of the EL delineators. It was also valuable to understand the differences between demographics in responding to delineator colors under different driving conditions. The driving simulator was used to test the responses of several demographic groups to changes in marker color and driving conditions. Furthermore, participants were tested for several factors relevant to driving performance including visual and subjective responses to the changes in colors and driving conditions. Impacts on driver perception were observed via eye-tracking technology with changes to time of day, visibility, traffic density, roadway surface type, and, crucially, color of the delineating devices. The analyses concluded that white was the optimal and most significant color for notice of delineators across the majority of subjective and performance measures, followed by yellow, with black being the least desirable.

What Impact Will the New-Built Metro Bring to the Transportation of Second-Tier Cities? From the Perspective of a Multilayer Complex Network

Metro is being developed rapidly in second-tier cities. There is a need to understand the impact it brings as it relates to the planning and management of the whole urban transportation system. In this paper, we applied the multilayer complex network theory to study this problem by contrasting the characteristics of transportation networks before and after the metro is built. We focused on transportation networks in second-tier cities and (1) proposed edge functions of the road subnetwork and rail transit subnetwork with impedance as weight; (2) established an interlayer function based on the transfer behavior to couple the above subnetworks into the multilayer weighted transportation network; and (3) redefined statistical parameters, such as node strength, chessboard coefficient, and average least pass cost. At last, Hohhot, China, a typical second-tier city, was taken as a case study. Calculations show that the new-built metro network in the second-tier city increases convenience and reduces travel cost, whereas, the vulnerability of the whole network increases, and the distribution of key nodes in the road network is reconstructed. For the sustainable development of urban transportation, more attention should be paid to the new-built metro in second-tier cities.

Paramount feat to sway and purge pollution by adopting computational intelligence

Human's can't imagine machines independent. From Vacuum Tubes technology to transistors and now with Integrated chip (IC), semiconductor technology defined another industrial revolution. The modern industrial twirl is already in transpire. Artificial intelligence (AI) is ushering in the new age of technologies that are super fast, more flexible, much potential, and initiating the world more digitally connected. No doubt the potential of IoT and AI to clean up the environment is cosmic. A computational concept like fuzzy logic, neural network, and machine learning will change the perspective of machine how they are used now. Our study reveals retrospect progression in the internet of things and artificial intelligence technologies to curb ecological pollution. New generation AI-enabled intelligent control systems are optimized with a complex algorithm to identify and eliminate pollutants for environmental clean-ups. With AI automation pollution management and mitigation, developments are examined. Adopting tech-savvy IoT and AI technology, dependency on machines can be seemly employed. For example; Transportation Management System using AI and IOT can be used to determine the best shipping routes by cutting fuel and gas consumption. To some extent ICT, wireless technology adds a contribution to reducing E-Waste. ICT together with IoT acts as a mediator while renting and sharing devices among people with different industries. AI helps to solve complex data analysis that supports Quick Decision System and policymaking. With intelligent robots, we can monitor and control acidification on Soil and water. The concept of neural network and fuzzy logic are greatly used to develop intelligent machines that predict different gas rates and chemical processes. AI machines that continuously check the pH level of water, Analysis Air Quality Index can be built to monitor water resources and atmosphere. Some AI robots can identify pollutants and helps to separate them. Now we are successful in a bifurcation of paper with plastic, Iron with aluminum. Such a method contributes to the waste management system appropriately. Our study also inspects the challenges of implementing AI, How data mining and big data management feed system.
 Authentication/Authorization work with industry and governing authority. Inspection of a biased algorithm, poor network, and security. There is no new route to achieve our goal. Our goal is to achieve paramount measures with two concepts in mind, that are Humans assist machines and Machines assist humans to control and prevent pollution in these critical situations. Both humans and machines together find an instant solution with renting and sharing that helps to minimize ecosystem effluence

Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives

Automated vehicles (AVs) are widely considered to play a crucial role in future transportation systems because of their speculated capabilities in improving road safety, saving energy consumption, reducing vehicle emissions, increasing road capacity, and stabilizing traffic. To materialize these widely expected potentials of AVs, a sound understanding of AVs’ impacts on traffic flow is essential. Not surprisingly, despite the relatively short history of AVs, there have been numerous studies in the literature focusing on understanding and modeling various aspects of AV-involved traffic flow and significant progresses have already been made. To understand the recent development and ultimately inspire new research ideas on this important topic, this survey systematically and comprehensively reviews the existing AV-involved traffic flow models with different levels of details, and examines the relationship among the design of AV-based driving strategies, the management of transportation systems, and the resulting traffic dynamics. The pros and cons of the existing models and approaches are critically discussed, and future research directions are also provided.

Transit ridership survey by analysis validation of electronic pass tickets

Introduction.The methods used today for determining the demand on public transport come with a big waste of time, resources and a need for great effort. In this regard, a special perspective is to study the transit demand based on the collection, integration and analysis of large and diverse data, which were generated by various sources of human life: Urban computing, Big data, Internet of things.Materials and methods.This article presents a method for determining (restoring) the correspondence of transit passengers by means of intelligent analysis of validation operations data of electronic travel tickets (smart card, transport card, magnetic card, mobile phone or other electronic devices (electronic gadgets)), which are recorded in the automated transportation management system during validation.Results.The algorithm for calculating passenger correspondence is implemented in a computer program using the relational DBMS MS SQL Server. The effectiveness of the proposed algorithm was verified by calculating the passenger correspondence of public transport in the city of Krasnoyarsk (Russia).Discussion and conclusion. The described method for calculating passenger flows, based on analyzing the data of validation operations of electronic tickets and data from the transit dispatch control system, makes possible to determine the route and passengers correspondence and, to carry out an objective assessment of the demand for public transport and the technical and operational indicators of the transit system.

Development of Transport Service Management under the Conditions of European Integration

The transport system of Ukraine, which consists of transport infrastructure, vehicles and management system, is studied in this paper. The dynamics of cargo transportation by all types of vehicles and the structure of exports and imports of transport services in Ukraine are analyzed. It is proved that transport logistics should include tasks, the solution of which will allow optimizing both transport processes and processes related to them. It is distinguished that one of the priority tasks of Ukraine in the conditions of European integration is the dynamic development of the domestic transport system with the help of smart technologies.

LOGISTICS MANAGEMENT SYSTEMS AND PERFORMANCE OF FAST-MOVING CONSUMER GOODS MANUFACTURERS IN NAIROBI, KENYA

Purpose: The purpose of this study was to establish the relationship between logistics management systems and supply chain performance of fast-moving consumer goods manufacturers in, Kenya
 Methodology: The study used descriptive research design was The study targeted the operations managers of the 51 FMCG manufacturers located in Nairobi. The sample size was 51 respondents who were selected using the census method. Questionnaires were used for data collection. For comprehension, logic and relevance, 5 respondents were used in pre-testing the questionnaire. Descriptive statistics will be used to analyze quantitative data. In order to test the significance of the effect of the predictor variables on response variables, the study used multiple linear regressions. Data collected was analyzed using SPSS version 23 and presentation of the findings done using figures, tables and charts.
 Results: The study found that warehouse management systems positively and significantly influences Supply chain performance of FMCG in Kenya; inventory management systems positively and significantly influences Supply chain performance of FMCG in Kenya; transportation management systems positively and significantly influence Supply chain performance of FMCG in Kenya; clearing and forwarding management systems have positive significant relationship with Supply chain performance of FMCG in Kenya; and information technology has a positive significant influence on the relationship between logistics management systems and supply chain performance of FMCG manufacturers in Kenya.
 Unique contribution to theory, practice and policy: The study recommends management of the company to ensure they remain informed on the changes in the market to ensure that their warehouse management system is up-to-date and therefore avoid process redundancy and inaccurate inventories. There is a need to use strategic approach in practices of managing logistics by embracing modernized technology and training of employees on the use of the same. Companies should automate their scheduling process this will lead to fewer interventions by the management and therefore lowering any chances of delays. It is also important for the government to ensure that there are clear regulations by custom department and ensure that the employees in this department are well knowledgeable of their task and are well organized and motivated to conduct their duties.

Driveability analysis of the european rail transport management system (ERTMS) - A systematic literature review

Train drivers in Sweden had the opportunity to test the new European Rail Transport Management System (ERTMS) during the early implementation of this signaling system in 2011 and 2012. Unfortunately, they have reported many implementation problems. These ERTMS lines have been evaluated as more challenging to drive compared to the previous signaling system. A systematic literature review was conducted to understand what network planning designers typically focus on when analyzing railway driveability and how driveability can be assessed. In the overall picture the impact on driveability originates from both technological, organizational, and train driver aspects. One technological issue found during the investigation is related to the speed profile design. Frequent speed changes were identified as the primary source of negative experiences during driveability evaluations, especially on retrofitted lines. Results also indicate the need for a methodology that includes the driver earlier in the network planning test process, to avoid the costly and time-consuming analysis done after project implementation. The results highlight the importance of the speed profile design to provide good driveability. Cognitive Task Analysis, simulations, and statistical calculations to predict driver and train performance were identified as applicable methods to involve train drivers earlier in the driveability analysis process.

An integrated modeling framework for active traffic management and its applications in the Washington, DC area

Developing appropriate modeling and simulation tools with the capability of analyzing traffic patterns, travel demand, and traveling/driving behavior responses at the regional level is important for the evaluation of active traffic management (ATM) and real-time transportation systems management and operations (TSM&O). In this paper, an integrated travel behavior and dynamic traffic assignment modeling tool, AgBM-DTALite, has been developed and adapted for real-time and dynamic analysis of ATM and TSM&O. The ATM algorithms are tightly integrated into the system, revising the control rates on a minute-by-minute basis. This tool also successfully incorporates travel demand and behavioral sensitivity into the traffic control and operations. The model is applied in a large-scale network to evaluate several ATM strategies, including variable speed limit (VSL) and ramp metering in the Washington, DC area. Significant departure time behavioral changes are found in response to ATM and the subsequent changes in traffic conditions. The impact on traffic dynamics is also quantified using various performance metrics.

Extrapolation-enhanced model for travel decision making: An ensemble machine learning approach considering behavioral theory

Modeling individuals’ travel decision making in terms of choosing transport modes, route and departure time for daily activities is an indispensable component for transport system optimization and management. Conventional approaches of modeling travel decision making suffer from presumed model structures and parametric specifications. Emerging machine learning algorithms offer data-driven and non-parametric solutions for modeling travel decision making but encounter extrapolation issues (i.e., disability to predict scenarios beyond training samples) due to neglecting behavioral mechanisms in the framework. This study proposes an extrapolation-enhanced approach for modeling travel decision making, leveraging the complementary merits of ensemble machine learning algorithms (Random Forest in our study) and knowledge-based decision-making theory to enhance both predictive accuracy and model extrapolation. The proposed approach is examined using three datasets about travel decision making, including one estimation dataset (for cross-validation) and two test datasets (for model extrapolation tests). Especially, we use two test datasets containing extrapolated choice scenarios with features that exceed the ranges of training samples, to examine the predictive ability of proposed models in extrapolated choice scenarios, which have hardly been investigated by relevant literature. The results show that both proposed models and the direct application of Random Forest (RF) can give quite good predictive accuracy (around 80%) in the estimation dataset. However, RF has a deficient predictive ability in two test datasets with extrapolated choice scenarios. In contrast, the proposed models provide substantially superior predictive performances in the two test datasets, indicating much stronger extrapolation capacity. The model based on the proposed framework could improve the precision score by 274.93% than the direct application of RF in the first test dataset and by 21.9% in the second test dataset. The results indicate the merits of the proposed approach in terms of prediction power and extrapolation ability as compared to existing methods.

Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis

The intelligent transportation system under the big data environment is the development direction of the future transportation system. It effectively integrates advanced information technology, data communication transmission technology, electronic sensing technology, control technology, and computer technology and applies them to the entire ground transportation management system to establish a real-time, accurate, and efficient comprehensive transportation management system that works on a large scale and in all directions. Intelligent video analysis is an important part of smart transportation. In order to improve the accuracy and time efficiency of video retrieval schemes and recognition schemes, this article firstly proposes a segmentation and key frame extraction method for video behavior recognition, using a multi-time scale dual-stream network to extract video features, improving the efficiency and efficiency of video behavior detection. On this basis, an improved algorithm for vehicle detection based on Faster R-CNN is proposed, and the Faster R-CNN network feature extraction layer is improved by using the principle of residual network, and a hole convolution is added to the network to filter out the redundant features of high-resolution video images to improve the problem of vehicle missed detection in the original algorithm. The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. The detection rate is satisfactory.

Automation of the procedure for assessing the quality of transport service for the population in the conditions of digitalization of the railway transportation system

The Strategic Program for the Development of Railway Transport until 2030 focuses on the development of a customer-oriented approach as one of the conditions for the company’s competitiveness. The customer focus is one of the elements of anti-crisis management of transport systems, it provides additional opportunities, especially when the volume of traffic decreases, when it is necessary to fight for attracting customers. A customer-oriented approach is closely related to the quality of the organization of transport services for passengers, which is certainly impossible without the use of modern automated technologies. Thus, a modern passenger is characterized by mobility and the habit of being online, in connection with which the passenger infrastructure and rolling stock must be provided with equipment and software that allows the passenger to remain in the familiar information environment.

Risk assessment of transport dangerous situations

Transport safety assessment plays a huge role in theory and practice of implementation of transport management systems. It should be noted that ensuring the transport safety is inextricably linked to identification of potentially dangerous transport situations and their risk assessment. To better manage transport risks we propose to apply a new integrated approach which allows to take into account the source of the threat, the degree of objects’ protection, kinds of threats, extent of damage in the event of dangerous situations, magnitude of the dangerous situation. This approach is anchored to systematic analysis of causes and conditions of formation of dangerous situations. Also, it provides timely forecasting of their development and consequences. Therefore, it is necessary to develop a new approach to transport risk assessment which will be able to effectively evaluate occurrence of dangerous transport situations. In this paper we present components of transport safety and provide a list of typical objects of transport infrastructure. Transport safety model and algorithm for identification of potentially dangerous transport situation is proposed. Also, we consider a new integrated approach based on transport risk assessment method. It is worth highlighting that the proposed method of transport risk assessment allows taking into consideration the uncertainty linked to the occurrence of dangerous transport situations and their conditions. The specified method can be widely used in modern geographic information systems for analysis of transport emergencies.

Data Analytic Solution for Heterogeneous Transportation Management Network System: A Case Study of Kwara State, Nigeria

When the transportation system of any States in Nigeria is effective, it positively contributes to effective economy growth and infrastructural facilities; saves stress and generate revenue to the authorities. This is the desire of every ministry of Transportation for State in Nigeria although a number of constraints usually make it not attainable. The transportation system presently operated by the Ministry of Transportation, Kwara was studied and found to be suffering, cumbersome, exploitative and fall short in all standards of a good transportation network system. Therefore this paper seeks to present the results of the research carried out to Big Data Analytic Solution (BDAS) for the management of the transport companies’ network system within Kwara State. The research adopts a transportation frame work design solution, MySQL for data migration and Php framework ‘codeigniter’ for productive server for the full development. The phase testing is carried out and presents the improved version for the improvement in routes schedules, company’s services and driver’s registration and user booking.
 The system will serve as open access to heterogeneous communities in Kwara State, Nigeria and make easy booking for passengers, assist communities in management of transportation systems within kwara state, Nigeria.

EFFECT OF TRANSPORTATION MANAGEMENT SYSTEMS ON SUPPLY CHAIN PERFORMANCE OF FMCG IN KENYA

Purpose: The purpose of this study was to determine the effect of transportation management systems on supply chain performance of FMCG in Kenya
 Methodology: The study adopted descriptive research design. The unit of observation was the operations manager of the 51 FMCG manufacturers located in Nairobi. The sampling frame of the current study consisted of operations managers in the manufacturers of the FMCGs in Nairobi. The study used the census method to select 51 manufacturers of the FMCGs in Nairobi, thus the sample of the study was 51 respondents. Primary data was used in the study. The study used questionnaires to collect data. Mixed methods technique of analyzing data was used where both descriptive and inferential analysis were used. The data collected from the field was analyzed using SPSS 23 program. The questionnaires were referenced and the items in them coded for easier data entry. The presentation of the findings was done using tables.
 Results: The study found that transport management systems positively and significantly influences Supply chain performance of FMCG in Kenya. The study established that transport management systems provides trade compliance information and documentation; transport management systems make it easier for businesses to manage and optimize their transportation operations, whether they are by land, air, or sea; transport management systems ensures timely delivery of freight and goods; transport management systems provides visibility into day-to-day transportation operations; and transportation management systems helps to streamline shipping process.
 Unique contribution to theory, practice and policy: The study recommended that companies should automate their scheduling process this will lead to fewer interventions by the management and therefore lowering any chances of delays. The study also suggests that companies can embrace the technology of Radio Frequency Identifications in boosting up their performance in regard to effectiveness and efficiency of manufacturing and performance of supply chain

Adaptation of trips by metro rail users at two stations in extreme weather conditions: Delhi

Weather influences travel behavior in both the short and long-term. We have studied the impact of extreme weather conditions of high temperatures, low temperatures, rain, thunderstorms and fog on travel choices by the metro rail users at two stations in Delhi. Stated adaptation choice survey is conducted at two metro stations (underground and elevated) having different built environments and transport infrastructure in the buffer area. The mode used and travel time to access metro stations vary between the two stations; however, the stated choices do not significantly vary between them. As per the analysis, the respondents are more likely to change their existing trip patterns during either rains or high temperatures. The metro rail users traveling for longer distances are less likely to change their existing travel patterns. Access travel time has a significant and positive impact on the alteration in travel choices during extreme weather conditions. The study highlights the need for provision and management of transport systems to support access/egress leg of the trip to minimize the exposure of users to extreme weather conditions. The study also identifies the impact of income, gender and trip purpose on the adaptation strategies.

Methodological Aspects of Transportation Systems Classification and Management

The development of the transport services sector in the global economy determines the effectiveness of economic links, both at the international level and at the level of organizing exchange processes within each country. In this regard, the topic of improving quality of organization of the transportation process, as well as organization of effective transport and logistics services within the transportation systems, remain relevant in Russia and abroad. The current state of the transport industry in Russia is characterized by such significant factors in formation of the market environment as digitalization of management processes and development of a customer-oriented policy, which is considered in various policy documents on development of transport. Competition in the Russian transport market is especially intensified for provision of cargo transportation services over medium distances. Currently, road transport services prevail over railway transportation in several regions of Russia, that negatively affects both goods safety rates and the cost of the transportation service itself. The comprehensive plan for modernization and enhancement of main transport infrastructure of the Russian Federation until 2024 involves creation of such transportation management systems that would not only ensure efficiency of delivery in the economic aspect but would also increase the system approach and reliability. It is proposed to consider mixed transportation systems as a form of organization of transportation systems. At the same time, the issues of methodology of classification and management of the transportation process in mixed systems acquire special relevance from the point of view of the choice of system management methods depending on the classification type of the system. The objective of the study is to develop the concept of «mixed transportation system» and a classification of mixed transportation systems in the field of cargo transportation. A classification system for mixed transportation systems is suggested based on four basic criteria. The classification uses a systemic and process approach, which is associated with the features of organization of multimodal transportation. The hypothesis of the study is to further develop the methodology of «management by results» for mixed transportation systems.

Impact of CoronaVirus (COVID19) in the Transport Management System: A Mini-Review

Human Coronavirus 2019 (COVID-19) is a consequence of severe acute coronavirus syndrome 2. The pandemic COVID-19 is an unprecedented, global pandemic. A novel COVID-19 affected human beings and a global public health emergency has been announced by COVID-19. In the global world, United States of America is the transport management system (TMS) is a global industry with a large market. TMS empowers to prepare, implement, and maximize the movement of goods, and to ensure that the transport is compliant, there are full and accurate records available at all times. Saudi Arabia is one of the leading TMS world widely. The aim of this review is to estimate the effect on transport management of the COVID-19 pandemic. The COVID-19 pandemic spread unpredictably around the world, infecting a number of nations with this epidemic. Nevertheless, globally and particularly in the United States was among the highly performed virus cases and mortality rates. Around the same time, even the transport/ traffic management system has affected this infectious disease. Saudi Arabia was also severely affected the impact of COVID-19 on TMS specifically the transport of international airports. The key goals for reinvigorating the growth potential in the future are to improve the production potential and increase employees. Future development of efficient distribution canals is expected to contribute to the potential growth of COVID-19 business TMS. This review concludes as COVID-19 has affected the TMS in the Saudi Arabia as well as global countries.

Process Mining as a Means of Improving the Reliability of Road Freight Transportations

The introduction of digital solutions in the automotive industry is often accompanied by a significant gap between the expectations and needs of the leaders of transport and logistics companies and the real business results achieved through the Transportation Management System. The causes of this phenomenon largely depend on the human factor, i.e. irrational actions of personnel who inefficiently use digital technology. The prerequisites for such actions are low competencies of employees, unfair attitude to work, sabotage. Accordingly, this leads to deviations in the transportation process, which can lead to violations of the conditions for the transportation of goods. From the point of view of the concept of reliability of road freight transport, this can be defined as a failure. Failures caused by the varied actions of managers when working with the Transportation Management System were extremely difficult to diagnose. Direct monitoring of managers during the working day is often fraught with various organizational difficulties, and is difficult to implement for a long time to identify ineffective staff activities. The concept of Process Mining, which has been known among scientists and researchers of information systems for more than 10 years, is currently of great interest in business. The paper examined the issues of improving and reorganizing the activities of managers of a transport company based on the mining of the TMS Autobase event log. Based on the results of the study, recommendations were made aimed at developing the digitalization of the transportation process, suggesting an increase in transportation reliability.

НОВІТНЯ ОЦІНКА УМОВ РУХУ ТРАНСПОРТНИХ ПОТОКІВ АВТОМОБІЛЬНИМИ ДОРОГАМИ «ТРІАДА ДОРОЖНЬОГО РУХУ»

The article explores the driving conditions for determining the demand of drivers of vehicles for the movement of roads, the road conditions of which should ensure this demand. The object of the study is automobile international and national transport corridors. When optimizing the management of the complex transport system «International, national and local traffic flows - Automotive International and National Transport Corridors» (MNMTP-AMNTC) can be sought to achieve different goals (criteria of optimality), and, depending on these goals, consider the different tasks of optimal management. On road transport, including in this concept of the system of communication routes (highways), the following tasks are the most important: ensuring the least time of communication at limited road costs; - ensuring the specified time of communication at the lowest road costs; - ensuring the lowest transport costs at a limited level of road costs; - ensuring the lowest road costs at a limited level of transport costs; - ensuring the maximum possible level of traffic safety at a limited level of road costs; - ensuring the required level of traffic safety at the lowest road costs; to achieve a minimum of road costs, provided that the specified volume of traffic (traffic), the specified speed and the necessary safety of traffic; ensuring maximum road capacity at a limited level of road costs. According to its parameters, the MMMTP-AMNTC refers to complex systems, the main characteristics of which are: efficiency indicator; stability; obstruction; Reliability. The newest approach of the «Traffic Triad» will allow to evaluate the functioning and ensure the rational management of any transport system with a focus on meeting the needs of users of highways - road users. KEYWORDS: HIGHWAY NETWORK, INTERNATIONAL, NATIONAL AND LOCAL TRAFFIC FLOWS, ROAD INTERNATIONAL AND NATIONAL TRANSPORT CORRIDORS.