Special Issue "Transportation Planning and Public Transport"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: 6 September 2021.

Special Issue Editor

Dr. Hamid R. Sayarshad
E-Mail Website
Guest Editor
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA
Interests: demand analysis; freight transportation and logistics; transportation network optimization and modeling; dynamic optimization models; dynamic vehicle routing and pricing problems; machine learning

Special Issue Information

Dear Colleagues,

This Special Issue aims to bring together emerging research on different transport models to address current and future issues in transportation, transport economics, traffic demand, and transportation resilience. This Special Issue also aims to expand research on public transport systems, such as shared mobility systems and transit services. Submissions should improve our understanding of the sustainability of public transport services in terms of public welfare and social needs. This Special Issue encourages submissions of original research articles that report significant research findings on the following topics:

  • transport demand and travel behavior;
  • route choice models and traffic assignment;
  • shared mobility systems (dial-a-ride, dial-a-bus, and dial-a-flight problems and flying taxis, bikes, buses, subways, car-sharing platforms, and parking mechanisms);
  • interaction between public transport and other modes;
  • social welfare through public transportation;
  • game theory and social choice models in transportation systems;
  • clean transport systems (electric taxis, energy consumption, infrastructure charging facilities);
  • transport information (travel behavior, weather prediction, demand prediction);
  • resilience and recovery of transportation networks;
  • freight transport models.

Dr. Hamid R. Sayarshad
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

Article
Low-Carbon Multimodal Transportation Path Optimization under Dual Uncertainty of Demand and Time
Sustainability 2021, 13(15), 8180; https://doi.org/10.3390/su13158180 - 22 Jul 2021
Viewed by 286
Abstract
The research on the optimization of a low-carbon multimodal transportation path under uncertainty can have an important theoretical and practical significance in the high-quality development situation. This paper investigates the low-carbon path optimization problem under dual uncertainty. A hybrid robust stochastic optimization (HRSO) [...] Read more.
The research on the optimization of a low-carbon multimodal transportation path under uncertainty can have an important theoretical and practical significance in the high-quality development situation. This paper investigates the low-carbon path optimization problem under dual uncertainty. A hybrid robust stochastic optimization (HRSO) model is established considering the transportation cost, time cost and carbon emission cost. In order to solve this problem, a catastrophic adaptive genetic algorithm (CA-GA) based on Monte Carlo sampling is designed and tested for validity. The multimodal transportation schemes and costs under different modes are compared, and the impacts of uncertain parameters are analyzed by a 15-node multimodal transportation network numerical example. The results show that: (1) the uncertain mode will affect the decision-making of multimodal transportation, including the route and mode; (2) robust optimization with uncertain demand will increase the total cost of low-carbon multimodal transportation due to the pursuit of stability; (3) the influence of time uncertainty on the total cost is significant and fuzzy, showing the trend of an irregular wave-shaped change, like the ups and downs of the mountains. The model and algorithm we proposed can provide a theoretical basis for the administrative department and logistic services providers to optimize the transportation scheme under uncertainty. Full article
(This article belongs to the Special Issue Transportation Planning and Public Transport)
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Article
Analysis of the Evolutionary Game between the Government and Urban Rail Transit Enterprises under the Loss-Subsidy Mode: A Case Study of Beijing
Sustainability 2021, 13(14), 8041; https://doi.org/10.3390/su13148041 - 19 Jul 2021
Viewed by 198
Abstract
Most of the urban rail transit enterprises in China have high construction and operation costs, while the government imposes price control on their fares, making their revenues unable to cover their costs and thus causing certain losses. In order to ensure the economic [...] Read more.
Most of the urban rail transit enterprises in China have high construction and operation costs, while the government imposes price control on their fares, making their revenues unable to cover their costs and thus causing certain losses. In order to ensure the economic sustainability of urban rail transit enterprises, the government then subsidizes their losses. In the context of loss subsidies as the main subsidy mode for urban rail transit, the government regulates whether urban rail transit enterprises waste cost in order to protect social welfare and reduce the financial pressure of subsidies. This paper constructs an evolutionary game model between government regulators and urban rail transit enterprises, establishes replicated dynamic equations to obtain the evolutionary stabilization strategies of the government and urban rail transit enterprises under different situations, and analyzes the effects of various parameters on the cost control behaviors of urban rail transit enterprises under different loss-subsidy modes through numerical simulations. The theoretical study and simulation results show the following: When only the regulatory policy is adopted, the optimal strategy of urban rail transit enterprises may be cost saving or cost wasting under different subsidy models; if only the penalty policy is adopted, the enterprises will choose the cost wasting strategy when the penalty is small, and the enterprises will choose the cost saving strategy when the penalty is large; if only the fixed proportion subsidy model is adopted, no matter how large the proportion k of government subsidies is, the urban the optimal strategy for rail transit enterprises is cost wasting. If only the regressive loss subsidy model is adopted, the different sizes of its various parameter settings will also lead to the enterprises’ choice of cost wasting strategy or cost saving strategy. Therefore, the government should formulate corresponding policies according to different cost control objectives. Full article
(This article belongs to the Special Issue Transportation Planning and Public Transport)
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Article
Dynamic Inventory Routing and Pricing Problem with a Mixed Fleet of Electric and Conventional Urban Freight Vehicles
Sustainability 2021, 13(12), 6703; https://doi.org/10.3390/su13126703 - 12 Jun 2021
Viewed by 544
Abstract
Urban freight transport is essential for supporting our society regarding providing the daily needs of consumers and local businesses. In addition, it allows for the movement of goods, is distributed within urban environments, provides thousands of jobs, and supports economic growth. However, a [...] Read more.
Urban freight transport is essential for supporting our society regarding providing the daily needs of consumers and local businesses. In addition, it allows for the movement of goods, is distributed within urban environments, provides thousands of jobs, and supports economic growth. However, a number of issues are associated with urban freight transport, including environmental impacts, road congestion, and land use of freight facilities that conflicts with residential land use. Electric freight vehicles create zero emissions and provide a sustainable delivery system in comparison with conventional freight vehicles. In this study, a novel dynamic inventory routing and pricing problem under a mixed fleet of electric and conventional vehicles was formulated to minimize the total travel and charging costs. The proposed model is capable of deciding on replenishment times and amounts and vehicle routes. We aimed to determine the maximum social welfare (SW) capable of providing an optimal trade-off between the supplier cost and customer delay that uses a mixed fleet of vehicles. Our computational study was conducted on real data generated from a delivery dataset in Tehran. Under the proposed policy with a fleet of only electric vehicles, the SW increased by 3% while the average customer delay reduced by 15% compared with a fleet of conventional vehicles. The results show that the number of served customers and customer delay would be affected by transitioning conventional urban freight vehicles to electric vehicles. Therefore, the proposed delivery system has a significant impact on energy savings and emissions. Full article
(This article belongs to the Special Issue Transportation Planning and Public Transport)
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Article
User Preferences in the Design of Advanced Driver Assistance Systems
Sustainability 2021, 13(7), 3932; https://doi.org/10.3390/su13073932 - 02 Apr 2021
Viewed by 609
Abstract
The transport network and mobility aspects are constantly changing, and major changes are expected in the coming years in terms of safety and sustainability purposes. In this paper, we present the main conclusions and analysis of data collected from a survey of drivers [...] Read more.
The transport network and mobility aspects are constantly changing, and major changes are expected in the coming years in terms of safety and sustainability purposes. In this paper, we present the main conclusions and analysis of data collected from a survey of drivers in Spain and Portugal regarding user preferences, highlighting the main functionalities and behavior that an advanced driver assistance system must have in order to grant it special importance on the road to prevent accidents and also to enable drivers to have a pleasant journey. Based on the results obtained from the survey, we developed and present a working prototype for an advanced driver assistance system (ADAS), its architecture and rules systems that allowed us to create and test some scenarios in a real environment. Full article
(This article belongs to the Special Issue Transportation Planning and Public Transport)
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