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A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 26433

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Special Issue Editors

Dr. Mahyar Amirgholy

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Guest Editor

Department of Civil and Environmental Engineering, Kennesaw State University, Marietta, GA 30060, USA
Interests: cooperative control systems; urban network modeling; large-scale optimization; transportation economics
Special Issues, Collections and Topics in MDPI journals

Dr. Jidong J. Yang

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Guest Editor

College of Engineering, University of Georgia, Athens, GA 30602, USA
Interests: sustainable and resilient infrastructure systems; smart mobility systems; big data mining and analytics; deep learning methods and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Transportation planning requires the continuous assessment of the outcomes of the policies designed to enhance safety, sustainability, mobility, accessibility, and equity in the short- and long-run. While the short-term outcomes of planning policies have direct impacts on their social acceptance, planning policies designed only based on the short-term assessment of the outcomes may not result in the desired strategic goals in the long run. To attain the short- and long-term goals, there are various factors that should be taken into account in the decision-making process, including the travel behavior and mode choice of commuters, the design of traffic control and demand management strategies, the operation of public transit and ride-hailing systems, the availability of ride-sourcing micromobility modes, the allocation of right-of-way to various modes of transportation, and the advent of electric powertrain and autonomous driving technologies. In this Special Issue, we invite the submission of research papers that specifically address decision making and policy analysis in transportation planning in the short- and long-run. The goal of this Special Issue is to cover the state-of-the-art contributions to data curation and analysis, model development, policy design, and system management. Topics of interest with a general focus on transportation planning include, but are not limited to:

Social acceptance of planning policies;
Investment in multimodal transportation systems;
Travel behavior and mode choice of multiclass users;
Public transportation and customized transit services;
Emerging micromobility and ridesharing services;
Lane management and allocation of right-of-way to non-motorized modes;
Carbon taxing and congestion pricing;
Sustainability planning and zero-emission transport;
Travel demand management and cooperative traffic control;
Electric vehicles and charging infrastructure development;
Automated vehicles and management policies.

Dr. Mahyar Amirgholy
Dr. Jidong J. Yang
Guest Editors

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 submissions that pass pre-check are 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. Systems is an international peer-reviewed open access monthly 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 2400 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.

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Published Papers (10 papers)

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Research

26 pages, 25069 KiB

Open AccessArticle

Management Policy in Urban Rail Transit System: Trade-Off between Social Distancing and Service Efficiency Using Simulation in the Post-Epidemic Era

by Zhichao Cao, Avishai (Avi) Ceder, Zihan Wang, Silin Zhang and Yaoyao Wang

Systems 2024, 12(5), 151; https://doi.org/10.3390/systems12050151 - 27 Apr 2024

Viewed by 1484

Abstract

The past COVID-19 pandemic introduced the world to the necessity of dealing with the trade-off between minimizing probability of contagion, and providing people with services they need. This trade-off stipulates that a large person-to-person distance will reduce contagion probability, but will render service inefficient, and vice versa. This work focuses on the urban rail transit (URT) hub, as an example of a busy passenger area, from which we can derive an optimal preparedness policy to use during the pandemic time of any coronaviruses. We use simulation methodology, based on the classical social force model, to represent behaviors and characteristics of pedestrians. Passenger flow movement process is a mechanism we explore to figure out how the epidemic management policy and pedestrian psychological-related behaviors interact with the URT system. The systems’ complexity regarding contagion-prevention distances are tested over a few scenarios: before/after the outbreak, and for different person-to-person distances demonstrating different crowd levels. A case study of Xinjiekou Station, Nanjing URT, China, enables assessment of passenger management policy with person-to-person distances of 0.5 m, 1.0 m and 2.0 m. Multi-scenario performance illustrates the trade-off in dynamic between the efficiency of pedestrians’ walking behaviors and the distancing needs for preventing coronaviruses transmission. The results show that queuing length with social distancing of 1.0 m and 2.0 m is increased by 4.17% and 21.22%. The average delays in boarding are 14.1 s and 22.5 s for 1.0 m and 2.0 m, which leads to 15.29% and 22.39% increases, respectively, in comparison with ordinary social distancing of about 0.5 m. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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20 pages, 3597 KiB

Open AccessArticle

Exploring the Impact of Charging Behavior on Transportation System in the Era of SAEVs: Balancing Current Request with Charging Station Availability

by Yi Zhu, Xiaofei Ye, Xingchen Yan, Tao Wang, Jun Chen and Pengjun Zheng

Systems 2024, 12(2), 61; https://doi.org/10.3390/systems12020061 - 17 Feb 2024

Viewed by 1778

Abstract

Shared autonomous electric vehicles (SAEVs) can offer safer, more efficient, and more environmentally friendly real-time mobility services with advanced autonomous driving technologies. In this study, a multi-agent-based simulation model considering SAEVs’ vehicle range and charging behavior is proposed. Based on real-world datasets from the Luohu District in Shenzhen, China, various scenarios with different fleet sizes, charging rates, and vehicle ranges are established to evaluate the impact of these parameters on parking demand, charging demand, vehicle miles traveled (VMT), and response time in the era of SAEVs. The results show there would be much more charging demand than parking demand. Moreover, a larger fleet size and longer vehicle range would lead to more parking demand, more charging demand, and more VMT while increasing the charging rate can dramatically reduce the charging demand and VMT. Average response time can be reduced by increasing the fleet size or the charging rate, and a larger vehicle range leads to longer response time due to the longer time spent recharging. It is worth noting that the VMT generated from relocating from the previous request destination to the origin of the upcoming request accounts for nearly 90% of the total VMT, which should be addressed properly with appropriate scheduling. A charging policy considering current requests and the availability of charging stations was proposed and verified in terms of reducing the response time by 2.5% to 18.9%. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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13 pages, 5250 KiB

Open AccessArticle

Strategic Sensor Placement in Expansive Highway Networks: A Novel Framework for Maximizing Information Gain

by Yunxiang Yang and Jidong J. Yang

Systems 2023, 11(12), 577; https://doi.org/10.3390/systems11120577 - 18 Dec 2023

Cited by 2 | Viewed by 1715

Abstract

Traffic sensors play a pivotal role in monitoring and assessing network-wide traffic conditions. However, the substantial costs associated with deploying an extensive sensor network across real-world highway systems can often prove prohibitive. Thus, the strategic selection of optimal sensor locations within budget and resource constraints becomes imperative, leading to the well-known Traffic Sensor Location Problem (TSLP). In this study, we introduce a novel framework to address the TSLP for large-scale highway networks, focusing on maximizing information gain in a joint vector space that comprehensively captures both network topology and segment-level features. To solve this optimization problem, we devised a genetic algorithm (GA) with penalty handling. Additionally, we developed a physics-guided random walk algorithm, which not only significantly reduces the search space but offers remarkable flexibility in striking a practical balance between computational load and the confidence of achieving global optimality. For illustration purposes, the proposed framework was applied to the Savannah highway network in Georgia. The results from our GA method align well with those from exhaustive research, but with significantly reduced computational time. By leveraging information theory and maximizing information gain in a low-dimensional vector space, the proposed framework permits parallel, scalable computation and offers considerable potential in the strategic planning and deployment of various sensors for expansive, real-world highway networks. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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13 pages, 1228 KiB

Open AccessArticle

Does Robotaxi Offer a Positive Travel Experience? A Study of the Key Factors That Influence Consumers’ Use of the Robotaxi

by Chun Yang, Chao Gu and Wei Wei

Systems 2023, 11(12), 559; https://doi.org/10.3390/systems11120559 - 29 Nov 2023

Cited by 3 | Viewed by 3394

Abstract

Presently, robotaxi is being tested in cities such as Beijing, Changsha, Guangzhou, etc., and it remains a relatively new mode of transportation for consumers. Considering that robotaxi is a new mobility model, its popularity has an immediate impact on the function and efficiency of urban traffic, so further research on consumers’ perceptions is necessary in order to improve their acceptance of robotaxi. In this study, we explored the behavioral intention of current users of robotaxi based on their performance expectancy, effort expectation, and perceived risk. Based on the results, it appears that performance expectations and effort expectations positively influence usage intentions, which indicates that improving travel efficiency and lowering the threshold for robotaxi use will assist consumers in accepting it. In terms of consumer behavior, perceived risk negatively impacts usage intention, meaning that personal safety, service quality, and travel experience are important factors. Performance expectancy and effort expectancy are positively correlated, indicating that improving travel efficiency and lowering thresholds are complementary. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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29 pages, 4020 KiB

Open AccessArticle

Estimating Benefits of Microtransit for Social Determinants of Health: A Social Return on Investment System Dynamics Model

by Mohammad Maleki and Janille Smith-Colin

Systems 2023, 11(11), 538; https://doi.org/10.3390/systems11110538 - 4 Nov 2023

Cited by 2 | Viewed by 3332

Abstract

Lack of transportation services in low-income communities greatly affects people’s health and well-being, creating barriers to social determinants of health (SDOH). One potential solution that has gained the attention of US decision-makers in recent years is microtransit, a transportation intervention aimed at addressing this issue. Despite promising results from prior microtransit implementation, the extent to which these programs deliver social benefits remains uncertain. This study presents a novel model called Social Return on Investment System Dynamics (SROISD) to forecast the social benefits of a microtransit program in Holmes County, Mississippi. The SROISD model identifies the scope and key stakeholders, maps outcomes, and gives outcomes a value. A causal loop diagram is developed next based on mapped outcomes and a literature review, thereby conceptualizing the processes through which social benefits are gained from the microtransit program. Three stock and flow diagrams are then created from the causal loop diagram to formulate the system and produce results. Outcomes mapped relative to three SDOH areas (1) accessing healthcare, (2) accessing employment, and (3) social participation indicate an overall positive return from investing in microtransit within the low-income community of interest. Additionally, ridesharing demonstrates a significant positive correlation with the SROI ratio. These findings offer support for the advantages of investing in microtransit. Additionally, the SROISD methodology offers decisionmakers a dynamically responsive approach that integrates traditional return on investment methodologies with system dynamics to explore social benefits across a variety of impact categories. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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15 pages, 6865 KiB

Open AccessArticle

Acceptance Analysis of Electric Heavy Trucks and Battery Swapping Stations in the German Market

by Florian Noto and Hamid Mostofi

Systems 2023, 11(9), 441; https://doi.org/10.3390/systems11090441 - 24 Aug 2023

Cited by 4 | Viewed by 2535

Abstract

Heavy-duty vehicles are a major contributor to CO₂ emissions in the transportation sector, and it is necessary to develop clean and green technologies to replace diesel trucks. Electric trucks have not reached a breakthrough in the German market. In addition to technology development, customer acceptance of new technologies is a critical factor in the success of sustainable transportation policies. This study aims to fill this knowledge gap by investigating the perceptions regarding electric trucks and providing insights into the acceptance of these technologies. Data and arguments on the expected risks and benefits of heavy-duty electric trucks, with a special focus on the battery swapping solution, were collected through a survey and expert interviews in the German commercial transport sector. The authors collected a sample of 146 qualitative responses and 61 individual statements on the expected risks and benefits of electric trucks and battery swapping. While the responses to the classified questions are overwhelmingly positive, the individual statements show that there are still many open questions. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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25 pages, 3146 KiB

Open AccessArticle

Prediction of China Automobile Market Evolution Based on Univariate and Multivariate Perspectives

by Debao Dai, Yu Fang, Shihao Wang and Min Zhao

Systems 2023, 11(8), 431; https://doi.org/10.3390/systems11080431 - 17 Aug 2023

Cited by 3 | Viewed by 2415

Abstract

The automobile is an important part of transportation systems. Accurate prediction of sales prospects of different power vehicles can provide an important reference for national scientific decision making, flexible operation of enterprises and rational purchases of consumers. Considering that China has achieved the goal of 20% sales of new energy vehicles ahead of schedule in 2025, in order to accurately judge the competition pattern of new and old kinetic energy vehicles in the future, the automobile market is divided into three types according to power types: traditional fuel vehicles, new energy vehicles and plug-in hybrid vehicles. Based on the monthly sales data of automobiles from March 2016 to March 2023, the prediction effects of multiple models are compared from the perspective of univariate prediction. Secondly, based on the perspective of multivariate prediction, combined with the data of economic, social and technical factors, a multivariate prediction model with high prediction accuracy is selected. On this basis, the sales volume of various power vehicles from April 2023 to December 2025 is predicted. Univariate prediction results show that in 2025, the penetration rates of three types of vehicles will reach 43.8%, 44.4% and 11.8%, respectively, and multivariate prediction results show that the penetration rates will reach 51.0%, 37.9% and 11.1%, respectively. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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19 pages, 2531 KiB

Open AccessArticle

Gender Gaps in Mode Usage, Vehicle Ownership, and Spatial Mobility When Entering Parenthood: A Life Course Perspective

by Hung-Chia Yang, Ling Jin, Alina Lazar, Annika Todd-Blick, Alex Sim, Kesheng Wu, Qianmiao Chen and C. Anna Spurlock

Systems 2023, 11(6), 314; https://doi.org/10.3390/systems11060314 - 20 Jun 2023

Cited by 4 | Viewed by 2368

Abstract

Entry into parenthood is a major disruptive event to travel behavior, and gender gaps in mobility choices are often widened during parenthood. The exact timing of gender gap formation and their long-term effects on different subpopulations are less studied in the literature. Leveraging a longitudinal dataset from the 2018 WholeTraveler Study, this paper examines the effects of parenthood on a diverse set of short- to long-term outcomes related to the three hierarchical domains of mobility biography: mode choice, vehicle ownership, spatial mobility, and career decisions. The progress of the effects is evaluated over a sequential set of parenting stages and differentiated across three subpopulations. We find that individuals classified as “Have-it-alls”, who start their careers, partner up, and have children concurrently and early, significantly increase their car uses two years prior to childbirth (“nesting period”), and they then relocate to less transit-accessible areas and consequently reduce their reliance on public transportation while they have children in the household. In contrast, individuals categorized as “Couples”, who start careers and partnerships early but delay parenthood, and “Singles”, who postpone partnership and parenthood, have less pronounced changes in travel behavior throughout the parenting stages. The cohort-level effects are found to be driven primarily by women, whose career development is on average more negatively impacted by parenting events than men, regardless of their life course trajectory. Early career decisions made by women upon entering parenthood contribute to gender gaps in mid- to longer-term mobility decisions, signifying the importance of early intervention. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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16 pages, 3661 KiB

Open AccessArticle

Ramp Spacing Evaluation of Expressway Based on Entropy-Weighted TOPSIS Estimation Method

by Jie Ma, Yilei Zeng and Dawei Chen

Systems 2023, 11(3), 139; https://doi.org/10.3390/systems11030139 - 4 Mar 2023

Cited by 12 | Viewed by 2331

Abstract

The main objective of this study is to design a method for evaluating the reasonability of ramp spacing of the expressway in a specific district. The study proposes an entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) estimation method, in which the entropy weight method determines the indicator weights, and TOPSIS is employed to compare different alternatives of ramp spacing. Four patterns of evaluation indicators are taken into account representing traffic efficiency, safety, traffic accessibility, and economy, respectively. Using the Beijing–Hong Kong–Macao Expressway in Henan Province as a case study, the validity of the method is verified, and the optimal ramp spacing is obtained as 14 km for the given scenario. The results of the study show: (1) extreme spacing values are not conducive to the overall benefits of the expressway; (2) ramp spacing settings that allow for coordinated sharing of traffic demand along the route (TDAR) are a prerequisite for an expressway to have great overall benefits; and (3) appropriately shortening ramp spacing will allow the expressway to effectively respond to increased TDAR. The estimation method proposed in this study provides a theoretical reference for the local authority to plan ramp spacing that can satisfy regional traffic demand and ensure the overall benefits of expressways in a sustainable urban context. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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19 pages, 1978 KiB

Open AccessArticle

High-Speed Rails and City Innovation System: Empirical Evidence from China

by Jiafeng Gu

Systems 2023, 11(1), 24; https://doi.org/10.3390/systems11010024 - 4 Jan 2023

Cited by 8 | Viewed by 2714

Abstract

The rapid development of high-speed rail has markedly shortened the travel time from one city to another. However, the impact of space–time compression brought about by high-speed rail on city innovation has not received sufficient attention. This paper examines the space–time compression phenomenon produced by high-speed railway networks and its impact on city innovation from 2000 to 2019 using a sample of 279 Chinese prefecture-level cities. The empirical results show that there was a strong space–time compression during this period. The development of high-speed rail can promote city innovation. However, the construction of high-speed rail also produces a siphon effect, which accelerates the convergence of innovative elements in cities with stronger innovation capabilities. Nevertheless, it has a negative spillover effect on cities with weaker innovation capabilities. Finally, policy recommendations for promoting the balanced development of city innovation and recommendations for future research are presented. Full article

(This article belongs to the Special Issue Decision Making and Policy Analysis in Transportation Planning)

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