JournalTOCs

Open Transportation Journal
Number of Followers: 1

This is an Open Access Journal

Open Access journal
ISSN (Online) 1874-4478
Published by Bentham Open

[69 journals]

The Effect of Modifying Double Continuous Flow Intersections Layout
Geometric Features on their Operation
- Abstract: Introduction:Continuous flow interventions were first introduced as an alternative to improve traffic operations in the intersections with severe congestion caused by heavy left-turn movements.Objective:This study quantified the effect of modifying the intersection angles of Double Continuous Flow Intersections (DCFI) on their operational characteristics. Mainly, the effects of changing the intersection angle between the different approaches of the main intersection and the angle of the minor cross-over intersections were investigated.Methods:VISSIM software simulation models were used for modifying several design features related to the DCFI and the operational performance was compared between the different simulation scenarios.Results and Discussion:Changes to the cross-over intersection angle increase the safety levels by providing better channelization of traffic movements on the minor intersections of the DCFI and reduce the intersection footprint to be used at high-density urban locations. Increasing the cross-over intersection angle and changing the layout geometry have adverse effects on the capacity of the conventional DCFI. This is mainly because of the added curvature in the intersection approaches which reduces the vehicle speeds, therefore reducing the overall capacity of the modified intersection when compared to the conventional DCFI. However, the total footprint for the intersection is reduced for the modified layout geometry, which improves the capacity of the DCFI.Conclusion:The study has explored the effects of modifying the DCFI intersection angles to fit the limited space in major urban areas on the capacity and performance of the intersection. It showed that DCFI designs could be applied in areas with limited space availability and skewed intersection angles.
Intelligent Transportation Systems along with the COVID-19 Pandemic will
Significantly Change the Transportation Market
- Abstract: Background:Reducing human presence in vehicles and transportation infrastructure is a common concept of Intelligent Transportation Systems and COVID-19 guidelines. However, the motivation for the reduced human presence is different. Intelligent Transportation Systems aim to improve transportation services with innovative technologies that can replace human handling and supervision. In contrast, COVID-19 guidelines aim to make the transportation means less busy, because a busy bus or a busy train means more opportunities for potential infection of passengers.Objective:The study aims to explain how the transportation market will be changed and why these changes are going to take place.Methods:The paper analyzes the current situation with its pros and cons and evaluates the ways in which the Intelligent Transportation Systems and the COVID-19 pandemic will affect this situation. A case study is also considered.Results:Intelligent Transportation Systems and the COVID-19 pandemic are two major factors in the transportation market that will significantly change the transportation means we know.Conclusion:It seems that the influence of the intense Intelligent Transportation Systems development and the impact of the COVID-19 outbreak is still underestimated by many governments; hence they continue to invest in traditional transportation instead of moving forward for a new generation of transportation.
Organization Leadership in the Automobile Industry: Knowledge Management
and Intellectual Capital
- Abstract: Background:Currently, the issue of a company’s innovative and competitive development is relevant in all areas of activity. The automobile industry, having innovative component as one of the development vectors, is faced with the task of achieving high competitiveness through active innovative learnings. This direction is influenced by Knowledge Management (KM) factors, which have a strong impact on the organizational leadership actions of automobile corporations.The automobile industry in Thailand is considered successful due to fast-driven KM and technology transfer activities. Unfortunately, the growth of the Thai auto industry is directly dependent on the performance of the offices of large international leading corporations; therefore, whether the Thai auto industry will be able to maintain the same marketing position through its own knowledge and technological capabilities is a question.This study analyzes the impact of KM-based organizational leadership in the automotive industry in Thailand using a Korean case study. Our research analyzed the knowledge-driven aspects of the automobile industry of Thailand and South Korea to identify the key factors that have a direct impact on competitiveness through the organizational leadership actions in these two countries.Objective:The study aims at investigating KM factors that influence the organizational leadership development of Korean and Thai automotive companies and evaluating their interdependence using the Cronbach alpha test.Methods:This research is based on statistical data and considers the specifics of the studied industry. It has limitations and uses quantitative data to generate results. The main source of data collection is open source. The test results for each component are organized according to the Cronbach alpha test.Results:Two automobile corporations from the Asian region were investigated. The application of organizational leadership in the technological field of automobile companies and knowledge transferring processes was found; an interdependence between the KM and organizational leadership was discovered as a result.Conclusion:Organization leadership could be used as an application for KM process development within the technological area of automobile companies. These findings can be used by managers to develop strategic programs to improve the knowledge transferring process and the organizational leadership in Asian automobile companies.
Sustainable Public Transportation Evaluation using a Novel Hybrid Method
Based on Fuzzy BWM and MABAC
- Abstract: Background:The transportation sector has wide-ranging effects on the human societies. Public transportation has a key and undeniable role in the lives of people in society and affects important aspects such as economic, social, cultural and environmental. Therefore, assessing the sustainability of public transportation in urban areas can be considered as a challenge for transportation policy makers.Methods:In this study, a novel hybrid multi-criteria decision-making (MCDM) method is proposed to evaluate sustainable public transportation in Tehran. Evaluation criteria have been identified using the literature and experts’ opinion. The proposed method integrates the fuzzy best-worst method (FBWM) and the multi-attributive border approximation area comparison (MABAC) method. a group of three experts determined the weight and importance of each criterion using FBWM. The MABAC method was then used to rank sustainable public transport alternatives.Results:The results indicate the reliability of the proposed method. Also, we can see that the results are congruent with the actual conditions of public transportation. The studied alternatives have been evaluated, and according to the decision criteria, metro and e-hailing have been the most sustainable alternatives. It is noteworthy that the economic and financial sustainability, service availability and environment sustainability have been the most important criteria.Conclusion:The proposed framework in this study can be used by public transportation planners and policy makers to identify sustainable options in order to consider facilities and implement incentive policies in this field. Also, the results of the proposed method used in this study can be used as a suitable guidance to assess the sustainability of public transportation.
Quantifying the Fleet Composition at Full Adoption of Shared Autonomous
Electric Vehicles: An Agent-based Approach
- Abstract: Aims:Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society.Background:Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles.Objective:To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand.Methods:An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type.Results:The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles.Conclusion:Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.
Impact of Experience and Training on Traffic Knowledge of Young Drivers
- Abstract: Background:An acceptable level of knowledge of traffic rules is needed for any driver to drive on public roads. This knowledge is typically acquired at a younger age during the process of attaining a driver's license.Aim:The purpose of this study is to investigate the level of knowledge among young drivers and how it could be improved. The study also explores the relationships between driving experience and knowledge scores as well as between driving training and knowledge scores for young drivers.Methods:A questionnaire survey that covered questions related to traffic law, fines, demerit points, traffic signs, and different driving situations was conducted among young drivers to assess their knowledge level. In addition to the different demographic questions, the survey included questions related to their licensing-related training and driving experience.Results:The participants revealed an acceptable level of knowledge in general, measured in terms of the percentage of correct responses. The participants showed an above-average level of knowledge of traffic signs, an acceptable level of knowledge in questions related to handling different driving situations, but they lacked knowledge of questions related to fines and demerit points. Drivers who attended a driving course before obtaining their driver's license performed better than drivers who did not. Similarly, drivers with more driving experience performed better than drivers with less experience.Conclusion:In summary, the results suggest that providing driving courses and acquiring driving experience are relevant to the acquisition of driving knowledge for young drivers.
Improving the Capacity and Level of Service at the Sixth Circle in Jordan
by Using Traffic Signals and Roundabout Metering Approach
- Abstract: Background and Objective:This study aims to improve the capacity and level of service at the sixth circle in Jordan by using traffic signals and a roundabout metering approach.Methods:VISSIM software and C++ program were used to improve the capacity and level of service. The site area (Sixth circle) was located near Crown Plaza and the Jordan Gate Towers project, which causes congestion due to heavy traffic flow. Therefore, this paper assesses the traffic in the sixth circle and presents the possible solutions to reduce the daily traffic flow for the users of this circle.Results:Four signals were placed at the roundabout in the second scenario, which was connected to each other with different cycle lengths. 90-second cycle length gives D value of the level of service. The third scenario was placed adaptive signals on the roundabout, which connects traffic signals with ground detectors placed at a certain distance before the signal and based on the queue length of the flow cars that pass the detector.Conclusion:The adaptive signals worked on the opening and closing and were designed according to the language simulation and the adoption of the language C++. The first two signals were opened considering the Swefieh road with the reference of King Faisal for a period of 45 seconds. It was then closed for 45 seconds to open the signal from the next street from the fifth circle with Zahran street.
In-tunnel Accident Detection System based on the Learning of Accident
Sound
- Abstract: Introduction:Traffic accidents are easy to occur in the tunnel due to its special environment, and the consequences are very serious. The existing vehicle accident detection system and CCTV system have the issues of low detection rate.Methods:A method of using Mel Frequency Cepstrum Coefficient (MFCC) to extract sound features and using a deep neural network (DNN) to learn sound features is proposed to distinguish accident sound from the non-accident sound.Results and Discussion:The experimental results show that the method can effectively classify accident sound and non-accident sound, and the recall rate can reach more than 78% by setting appropriate neural network parameters.Conclusion:The method proposed in this research can be used to detect tunnel accidents and consequently, accidents can be detected in time and avoid greater disasters.
Modeling Heterogeneous Fleet Vehicle Allocation Problem with Emissions
Considerations
- Abstract: Aims:This study proposes a bi-objective linear integer programming model for heterogeneous fleet VAP with emissions considerations. Profit maximization and emissions minimization objectives are employed to handle economic and environmental sustainability purposes.Background:Our literature survey shows that there is no model for the heterogeneous fleet VAP with emissions considerations that simultaneously consider vehicle heterogeneity, penalty costs for unmet demands, and emissions from transportation operations.Objective:The model is employed to also make several scenario analyses on sustainable freight logistics management to understand the trade-offs among economic and environmental objectives. In freight transportation problems, decision-makers need to be able to maintain profitability and to reduce emissions.Methods:In this study, a bi-objective linear integer programming model is proposed for a heterogeneous fleet Vehicle Allocation Problem (VAP) with emissions considerations encountered in the field of sustainable freight transportation.Results:In the numerical analyses, various practical assumptions that can be confronted by decision-makers in real life are discussed. In each analysis, total profit and emissions amounts are revealed along with several other KPIs. The results of the analyses provided in this study could also be useful in terms of understanding the relations among pillars of sustainability in VAPs.Conclusion:It is thought that the proposed model has the potential to aid decision-making processes in sustainable logistics management.In the base case analyses, the total profit obtained under profit maximization is about nine times higher than that obtained under emissions minimization. When the aim is to minimize emissions, the total emissions are found to be nearly one-tenth of that of profit maximization. Supported by also additional scenario analyses, it can be concluded that it might not economically viable to be environmentally-friendly for companies. Therefore, companies have to be encouraged or forced to take environmentally and socially responsible actions through legislation. The analyses demonstrated that various legislative policies on emissions may affect the transportation plans differently in such vehicle allocation systems.