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"Transportation services"
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Automatic License Plate Recognition System for Vehicles Using a CNN
Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with regard to unusual varieties of license plates or their success at night. We present an efficient ALPR system that uses a CNN for character recognition. A combination of pre-processing and morphological operations was applied to enhance input image quality, which aids system efficiency. The system has various features, such as the ability to recognize multi-line, skewed, and multi-font license plates. It also works efficiently in night mode and can be used for different vehicle types. An overall accuracy of 98.13% was achieved using the proposed CNN technique.
Journal Article
Pricing Decision and Research of Dual-Channel Cargo Transportation Service System Based on Queuing Theory
Against the backdrop of China’s “public-to-railway” freight policy that has led to railway yard congestion and imbalanced modal capacity utilization, this study develops a Dual-Channel Cargo-Transportation Service (DCTS) system model using queuing theory to optimize freight flow allocation and pricing strategies. Integrating the behavioral decisions of governments, carriers, and cargo owners, the research employs M/M/1 queuing models and the Logit choice framework to analyze the dynamic equilibrium between goods waiting times and carrier profits, exploring objectives of minimizing system-average waiting time and maximizing carrier profits. Key findings show that regulating highway pricing can effectively divert freight flows to reduce railway congestion and improve system efficiency, with optimal pricing intervals for highways identified based on service capacity to balance congestion relief and profitability. The model quantifies the trade-off between transportation costs and waiting times to guide cargo owners’ mode choices, and numerical simulations validate that strategic highway price adjustments alleviate bottlenecks and enhance modal synergy. This paper provides a theoretical basis for the government to formulate freight-transportation policies and optimize freight flow allocation. At the same time, it also provides a practical, theoretical basis and methodological reference for carrier pricing decisions, as well as for solving the problem of freight flow congestion and optimizing the pricing of transportation services.
Journal Article
Tools and Methodologies for the Analysis of Home-to-Work Shuttle Service Impacts: The ENEA “Casaccia” Case Study
Mobility management is a regulatory framework designed to streamline systematic mobility and mitigate energy, environmental and economic impacts. In this work, we propose a flexible methodology for evaluating the sustainability of home-to-work travel, providing a comprehensive and detailed ex post cost–benefit assessment. Specifically, we analyzed the effectiveness of the shuttle service operating in the ENEA “Casaccia” Research Centre in pre-pandemic times. Initially, we conducted an online survey to collect data with the aim of characterizing the travel behavior of the staff and reconstructing the multi-modal individual mobility patterns. Over 70% of the recipients, which amounted to about 950 individuals, completed the survey. Subsequently, we studied two alternative scenarios—with and without the shuttle service—comparing their total mileage, energy consumption, and pollutant emissions and performing an economic analysis. Our findings suggest that operating the service has a significant impact on air pollutants and greenhouse gas emissions, with reductions of 97% for volatile organic compounds, 72% for particulate matter, and 60% for carbon dioxide. Moreover, the cost–benefit analysis reveals that both users and the community reaped benefits from the provision of the collective service. These benefits are estimated to be almost EUR 1.35 M per year.
Journal Article
Leader-based diffusion optimization model in transportation service procurement under heterogeneous drivers’ collaboration networks
One of the key issues in transportation systems is allocating shipping orders to the most appropriate drivers in the shortest time and with the maximum profit. Many studies were carried out in the transportation service procurement process for allocating orders, but none of them considered driver-to-driver interactions and applied information diffusion concepts as a framework to maximize the profit, due to the lack of a framework to model the interactions. In this paper, we present a weighted drivers’ collaboration network to form the interactions. To predict the behavior of drivers, a new community detection algorithm is developed to extract communities and their leaders in terms of the speed and power of receiving and diffusing shipping orders. In addition, we present a profit maximization model that utilizes the information diffusion power of community leaders. The results show the model is able to allocate shipping orders to the most suitable drivers in the shortest possible time and with the highest profit. To demonstrate the performance of the developed algorithm, we present a numerical example. Finally, a case study is applied to solve the optimization problem. The results show that the optimized behavior of companies in allocating orders to drivers is based on their risk level, reputation, and the average number of their customers.
Journal Article
Winner Determination with Sustainable-Flexible Considerations Under Demand Uncertainty in Transportation Service Procurement Auctions
Sustainability and flexibility are two main factors not being investigated explicitly by existing winner determination literature. From a fourth party logistics (4PL) provider’s point of view, an innovative sustainable-flexible winner determination problem under uncertain demand is particularly studied in transportation services procurement auctions. Based on a multi-attribute decision-making method, a linear constraint related to each bidder’s sustainability score and flexibility score can be constructed, and then we integrate an outside option policy to formulate a two-stage stochastic sustainable-flexible winner determination model. Subsequently, we develop an approximation approach to solve the model based on the principles of dual decomposition Lagrangian relaxation and the sample average approximation. Using an established generator to obtain random instances, the effectiveness and applicability of this research could be verified by conducting numerical experiments. Also, managerial insights can be obtained to provide decision support for running an efficient sustainable-flexible logistics system by using a Chinese 4PL firm’s real data.
Journal Article
Driving sustainable transportation: insights and strategies for shared-rides services
The concept of sharing, enabled by emerging technologies, is playing an increasingly important role in contributing to a transformation toward more sustainable transportation. This study aimed to contribute to the growing body of literature on on-demand transportation services, with a particular emphasis on sharing or pooling a ride when using services such as transportation-network companies (TNCs) and microtransit. The study conducted a shared mobility survey of over 2,500 respondents from selected locales across Texas—ranging from large urban areas to small cities and rural areas. We analyzed the survey data in detail using extensive statistical analysis and inferential techniques and adopted an analysis approach toward implementation-oriented research to address the gap between theory and practice. Demographic, as well as geographic and built-environment, factors were found to play an important role in determining whether users will opt for a shared or pooled service and/or how they perceive these alternatives. The findings highlight the importance of improving safety and security, increasing awareness of the benefits of ride-sharing, and designing appropriate policy measures to promote sustainable mobility. We identified potential operational improvements, government policies, and employer programs to improve shared-ride services and encourage their use, such as reducing uncertainty in shared rides and minimizing inconvenience for passengers. A critical finding was the need to prioritize operational improvements in shared-ride trips over solely relying on financial incentives to induce behavior change. Enhanced public awareness and education were also determined to be crucial regardless of the nature of improvements, policies, or programs that are implemented.
Journal Article
Impact of College Provided Transportation on the Absenteeism and Academic Performance of Engineering Students
Students use different modes of transport to go to college. While many transportation programs exist at different universities and many experts find these programs to have a positive impact, no studies have investigated the impact of such programs on the absenteeism and academic performance of college students. The main purpose of this study is to investigate the impact of a college provided transportation program on the absenteeism and performance of engineering students. Different types of data were collected from a sample of engineering students, including attendance records, grade point average (GPA), course grades, majors, and bus ridership information for two years. The findings suggest that there is a positive impact of providing a college transportation service to engineering students in the form of better attendance and higher GPA. The outcomes of this study can be used to evaluate similar programs in the future and can be used by public agencies and policymakers to make decisions on expanding investments in such programs.
Journal Article
Assess Spatial Equity Considering the Similarity Between GIS-Based Supply and Demand Maps: A New Framework with Case Study in Beijing
Spatial equity is a critical issue that the supply allocation should align with the level of demand, enabling all community members to equally benefit from the city’s resources and opportunities, yet commonly used assessment methods have inherent limitations. This study proposes a new framework to assess spatial equity based on the evaluation of similarity between GIS-based supply and demand maps and provides a simplified case study that assesses public transportation services across the area inside the Sixth Ring Road of Beijing to facilitate the comprehension of this framework. The results show that while services in this region are relatively spatially equitable, significant spatial inequity remains in certain areas, where targeted policy recommendations are put forward such as promoting innovative transportation solutions and redistributing excessive demand to less congested facilities. The application prospects and future development directions of the proposed framework are thoroughly discussed. This framework stands out for its ease of comprehension, visualization, and general applicability. Specifically, it is capable of identifying areas with severe inequity, thus contributing to the establishment of targeted intervention measures to mitigate spatial inequity.
Journal Article