Transportation Planning Research Articles

Contextualizing urban road network hierarchy and its role for sustainable transport futures: A systematic literature review using bibliometric analysis and content analysis tools

AbstractUrban road networks play a crucial role in transport and urban planning and have the potential to contribute to more sustainable futures if their hierarchy is properly understood. However, the concept of the urban road network hierarchy, which refers to street classification and prioritization, is not well defined within the domain of transport engineering management, leaving many questions unanswered. Is it simply a planning tool, or does it extend to defining the essence of cities? Is it a qualitative or quantitative concept? Does it emerge organically or require proactive planning? Given the lack of comprehensive answers to these questions, this research aims to provide a contextual understanding of the urban road network hierarchy through the lens of sustainable transport futures. To this purpose, we conducted a systematic literature review, which is an effective method for consolidating knowledge on a specific topic. A total of 42 articles were analyzed using both quantitative bibliometric analysis and qualitative content analysis. Our work demonstrates that the road network hierarchy consists of 16 sub-concepts. Four main research trends were identified and discussed: a) road morphology and structure, b) advanced algorithms for street classification, c) integrated street classification planning, and d) the social dimension of street classification. Recent literature indicates a shift toward alternative road network hierarchy approaches that prioritize sustainable mobility over car-centric models. In conclusion, our analysis reveals that the urban road network hierarchy is a multifaceted yet under researched “vehicle for change,” which, if utilized effectively, offers opportunities to reimagine urban road environments.

Exploring Spatiotemporal Patterns of Frequently Congested Urban Road Segments Based on Multi-Source Data: A Case Study of China’s Super-Large Cities

Traffic congestion has emerged as a primary obstacle to sustainable urban development and the livability of life. Seven super-large cities in China were the study area of this paper as the problem tends to be more severe in larger cities. First, frequently congested road segments were defined based on real-time traffic condition data from online maps. Then, the spatiotemporal characteristics of these road segments were explored. Finally, mitigation measures and ways to ease traffic congestion in big cities were discussed against the background of rapid urbanization. The results demonstrate that the proportion of frequently congested road segments takes up between 1.8% and 9.87% of China’s super-large cities. There is a positive correlation between the overall operational efficiency of the urban road network and the ratio of frequently congested road segments. Temporally, commuting patterns during the morning and evening are displayed by these road segments. Spatially, they also demonstrate significant clustering characteristics. The proportion of frequently congested road segments caused by the lack of alternative routes is about 20% in the six cities studied. The data for Chongqing is even higher at 42.94%. Therefore, congestion caused by the lack of alternative routes may be underestimated by existing research. This work could provide theoretical support for transportation planning and management. As cities continue to expand and urbanization accelerates, the significance of this research will increase.

Embracing Urban Micromobility: A Comparative Study of E-Scooter Adoption in Washington, D.C., Miami, and Los Angeles

E-scooters have emerged as a popular micromobility option for short trips, with many cities embracing shared e-scooters to enhance convenience for travelers and reduce reliance on automobiles. Despite their rising popularity, there is a lack of clear understanding of how user preferences and adoption practices vary by location. This study aims to explore user and non-user attitudes towards e-scooter use in diverse urban settings. A meta-analysis of data from three surveys (N = 1197) conducted in Washington, D.C., Miami, FL, and Los Angeles, CA, was performed to compare e-scooter users and non-user profiles, mode choice factors, and attitudes and preferences towards e-scooter use. Additionally, machine learning (ML) and SHAP (SHapley Additive exPlanations) analysis were utilized to identify influential factors in predicting e-scooter use in each city. The results reveal that the majority of e-scooter users are 25 to 39 of age, male, with higher income and a bachelor’s degree, and 92% possess a driver’s license. Significant differences in attitudes between e-scooter users and non-users highlight the complexity of perceptions towards e-scooter usage. The ML model indicates that employment status negatively impacts the prediction of e-scooter users, while factors such as living without a car and using non-motorized modes positively influence e-scooter use. Educational background is a significant e-scooter mode choice factor in Washington, D.C. and Miami, whereas attitudinal questions on car and technology usage are influential in Los Angeles. These findings provide valuable insights into the factors shaping e-scooter adoption, informing urban transportation planning and policymaking and enhancing understanding of shared micromobility and its impact on urban mobility.

A realistic and sustainable logistics transportation planning: a new cost model, meta-heuristic solving approach, and results

A realistic and sustainable logistics transportation planning: a new cost model, meta-heuristic solving approach, and results

A generalized vector-field framework for mobility

Given the identification with travel demand and its relevance for transportation and urban planning, the estimation of trip flows between areas is a fundamental metric for human mobility. Previous models focus on flow intensity, disregarding the information provided by the local mobility orientation. A field-theoretic approach can overcome this issue and handle both intensity and direction at once. Here we propose a general vector-field representation starting from individuals’ trajectories valid for any type of mobility. We also show with simplified models how individuals’ choices determine the mesoscopic properties of the mobility field. Distance optimization in long displacements and random-like local exploration are necessary to reproduce empirical field features observed in Chinese logistic data and in New York City Foursquare check-ins. Our framework is able to capture hidden symmetries in mesoscopic urban mobility and opens the doors to the use of field theory in a wide spectrum of applications.

Analysis of Changes in In-Store and Online Shopping Frequencies Due to the COVID-19 Pandemic: A Case Study from Bahrain

Online shopping (e-shopping) has been growing steadily in recent years; however, the COVID-19 pandemic resulted in a sudden increase in this growth. This study compares the in-store shopping and e-shopping frequencies within three distinct periods, i.e., before, during, and after the COVID-19 pandemic. It further investigates the frequencies and determinants of e-shopping across the three periods. The data on the in-store shopping and e-shopping frequencies for four different product categories, i.e., grocery, household essentials, electronics, and clothes, were collected through an online questionnaire in Bahrain, resulting in a total of 401 valid responses. Wilcoxon signed-rank tests were conducted to compare the frequencies of in-store shopping and e-shopping within the three periods as well as the frequencies of e-shopping across the three periods. The effects of the determinants of e-shopping were evaluated using chi-square tests. The results revealed that e-shopping experienced a temporary surge during the COVID-19 pandemic, returning to pre-pandemic levels afterward. The frequency of e-shopping varied across product categories and periods, and e-shopping during the pandemic was higher than before. However, no significant difference was found between the periods during and after the pandemic. This study provides insights for urban and transport planners regarding the frequencies and determinants of e-shopping behavior in the context of pandemics.

Proposal of a Transport Planning Model for the Removal of Quarry Stone Using a Simulation

This article describes a transport planning model which applies a simulation to support decision-making in quarry operations. The analysis of the transport system was used as input for creating the model and the subsequent research. There are five loading points in the quarry from which, according to the plan, the quarry stone is transported to the crusher, where it proceeds for further processing. The required daily capacity of the downstream technological line is 3800 t/day. Based on the analysis, it was found that it was impossible to fulfill this requirement from the two loading points which were the furthest from the unloading point. For this reason, two simulation models of the transport system were created. The first simulation model is a transport system (loading, removal and dumping of quarry stone) from one loading point. Simulation experiments were performed on this model for all loading points. The findings from the analysis confirmed the results of the simulation experiments. Subsequently, a model of the combined quarry stone removal from two loading points was proposed. The model was designed for two variants of dividing the work shift into two work sections. In the model, which had a tabular form, the combinations of loading points and values of the minimum number of unloaded cars for stone removal were suitable to ensure its necessary daily capacity. The last part of this research was expanding the original model with an additional loading point. Several experiments were performed on this model. The aim of these experiments was to verify the combinations of loading points presented in the proposed model and the combinations of unsatisfactory loading points. Based on the research results, the transport planning model and simulation models are suitable additional tools for the decision-making process in removing quarry stone.

Moment-SoS methods for optimal transport problems

Most common optimal transport (OT) solvers are currently based on an approximation of underlying measures by discrete measures. However, it is sometimes relevant to work only with moments of measures instead of the measure itself, and many common OT problems can be formulated as moment problems (the most relevant examples being Lp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^p$$\\end{document}-Wasserstein distances, barycenters, and Gromov–Wasserstein discrepancies on Euclidean spaces). We leverage this fact to develop a generalized moment formulation that covers these classes of OT problems. The transport plan is represented through its moments on a given basis, and the marginal constraints are expressed in terms of moment constraints. A practical computation then consists in considering a truncation of the involved moment sequences up to a certain order, and using the polynomial sums-of-squares hierarchy for measures supported on semi-algebraic sets. We prove that the strategy converges to the solution of the OT problem as the order increases. We also show how to approximate linear quantities of interest, and how to estimate the support of the optimal transport map from the computed moments using Christoffel–Darboux kernels. Numerical experiments illustrate the good behavior of the approach.

Serious gaming to co-create a value-based mobility mix in a multi-objective arena

IntroductionThe world is facing multiple challenges, e.g. in the realm of health, urbanization, climate change and social inclusion. Mobility can be part of the problem yet has the potential to be part of the solution. Serious games can support decision-making in a complex environment. This paper describes a serious game that aims to stimulate individual learning of (future) professionals in transport and urban planning, and facilitate discussions on goals and arguments concerning different (new) mobility options. MethodsThis paper presents the first version of the serious game: ‘the Optimal Mobility Mix’. This card game was developed and played in five sessions in the Netherlands, India and the USA with over 100 participants. Feedback was collected informally in a debrief, through a survey (N = 25) and through observation. ResultsDuring the game, participants formed small groups and collaborated to select a mobility mix using playing cards that aligned with the five societal goals (effective mobility, efficient city, economy, environment & health and equity), of the 5E framework (Van Oort et al., 2017). The survey indicated that the game was highly interactive, fun and relevant. Although the game's ‘reflection of reality’ scored relatively low, it still remained positive. ConclusionsOverall, the game successfully facilitated discussion on societal goals and transportation modes and appears positive on its learning objectives. The effect of the game in policy and decision making practice will be tested in future research. Striking a balance between capturing the complexity of reality and creating an accessible and flexible model for professionals to interact with – in the form of a game, is an ongoing challenge. Future developments aim to involve key players and broader planning-related policies through a codesign process with game design iterations. To support this process, observations and recordings can be intensified to improve feedback processing.

Participatory Planning in Designing Autonomous Mobility Systems: A Design Thinking Approach

The adoption of participatory planning approaches in the deployment of new mobility solutions is rare. In this study, we conducted a community-based planning exercise using design thinking approaches to engage residents in co-creating an Autonomous Mobility System (AMS) for their neighborhood in Singapore. Through this process, a baseline understanding of participants’ attitude toward autonomous vehicles (AVs) was established, along with understanding the residents’ travel patterns and challenges. A co-creation activity guided participants to design their ideal AMS for the local community living in the Punggol residential district in Singapore. The exercise resulted in 20 unique designs of AMS, producing novel ideas such as suitable AV-holding areas and service zones. The results of the design activities provided insights into community-level priority and values. For AMS, providing alternative transport options that complemented existing train and bus services was the priority. As participants co-designed an AMS that fitted their needs as well as the needs of other participants, the designs also suggested that participants valued transport equity and accessibility, especially for the marginalized population, highlighting the importance of a human-centric design approach to transportation planning.

Survey of driver's functional state change, considering movement through mountain passes

According to traffic accident statistics, the main causes are violations of traffic rules. Based on scientific research, it is clear that the main reason for these events is the drivers' incorrect assessment of the road situation and their inadequate response. Assessing road conditions depends on drivers' qualifications, skills, work experience, reaction time, and other physiological factors. The functional state of drivers is important to consider. It reflects their ability to work reliably and affects both fatigue levels and how fatigue builds up. Factors that impact decision-making speed and quality are crucial when evaluating the risks of the transportation process, particularly those associated with human behavior. This study investigates the safety of freight transportation for drivers, road users, third parties, and the environment. The study focuses on road traffic characteristics in mountainous conditions at high altitudes. The study aims to analyze how drivers' performance is affected while navigating challenging sections of mountain roads in the Ukrainian Carpathians. Four different routes will be examined. The research will provide graphic analysis of the results. It will show the main patterns of changes in drivers' functional state based on the route's complexity. The research aims to analyze indicators of drivers' functional state and their impact on their performance reliability. It allows for a more detailed evaluation of transport routes and planning of truck drivers' work and rest schedules on suburban routes.

Teaching design and implementation of traffic system simulation course based on a computer virtual reality software under the background of engineering education

AbstractThe further reform and development of engineering education courses can help improve the teaching quality of higher education institutions, implement the fundamental task of talent cultivation, and provide important support and channels for cultivating high‐quality and supportive engineering technical talents. The traffic system simulation course is an applied science closely related to engineering technology. It mainly cultivates senior engineering technical talents engaged in research and development of transportation engineering, analysis of road traffic characteristics, and transportation planning and design. Considering the characteristics of the traffic system simulation course, this study puts forward the course teaching design based on computer virtual reality software. Combined with the training objectives of applied talents in the traffic system simulation course, this study focuses on how to reform the teaching content and teaching mode with the help of Vissim computer simulation software. The course teaching design refines and optimizes the teaching content by the use of computer software. The use of Vissim software in the course enriches the teaching content and methods and stimulates students' interest in learning. Through the guidance of active exploration and self‐directed learning for students, the traffic system simulation course reform has created a more positive and effective learning environment for students, which helps to cultivate their exploratory spirit and innovative ability. The implementation of the course teaching reform has gradually improved students' learning initiative and ability to master course content, as well as their practical problem‐solving abilities. Good teaching results have been achieved.

A city-centric approach to estimate and evaluate global Urban Air Mobility demand

AbstractUrban Air Mobility is expected to effectively complement the existing transportation system by providing fast and safe travel options, contributing to decarbonization, and providing benefits to citizens and communities. A preliminary estimate of the potential global demand for UAM, the associated aircraft movements, and the required vehicles is essential for the UAM industry for their long-term planning, but also of interest to other stakeholders, such as governments and transportation planners, to develop appropriate strategies and actions to implement UAM. This paper proposes a city-centric forecasting methodology that provides preliminary estimates of the potential global UAM demand for intra-city air taxi services for 990 cities worldwide. By summing all city-specific results, an estimate of the global UAM demand is obtained. By varying the parameters of the UAM system, the impact of ticket price and vertiport density on UAM demand is shown. Considering low ticket prices and high vertiport densities, possible market development scenarios show that there is a market potential for UAM in over 200 cities worldwide by 2050. The study highlights the significant impact of low ticket prices and the need for high vertiport densities to drive UAM demand. This emphasises the need for careful optimization of system components to minimise costs and increase the quality of UAM services.

Agent-based decision-support model for bus route redesign in networks of small cities and towns: case study of Agder, Norway

Small cities and towns often struggle to provide high-quality public transport services to daily commuters. This is reflected in the modal split, where the share of car users dominates. Such a problem requires a modern solution, where transport planners can verify the impact of potential transport network improvements on the travel behavior of the residents before the changes are actually deployed. This study aims to demonstrate the usefulness of employing an agent-based simulation tool in the decision process for redesigning an express service regional bus route connecting a network of small cities and towns. The model was initially developed as a Mobility as a Service simulation solution for suburban areas of European metropolises. The model is adapted and applied to a case study for the region of Agder, Norway, simulating the impact of nine different scenarios on the patronage of a specific bus route. The simulation model proposes to upgrade the classic agent structure to a persona profile designed specifically for the case study. The main objective of this research is to identify the scenario that maximizes patronage while minimizing total route travel time and additional costs. The results suggest that the proposed model can be successfully adapted from suburban metropolitan areas to the realities of the considered case study, and potentially other similar regions. Specifically, out of the nine proposed scenarios, the model identified four promising ones. One of the four scenarios also fits the cost constraints imposed by the transport provider. The model provides a solid approach for analyzing complex transport systems that are practically impossible to consider in detail if the analysis is done without computer support. Thus, the results can be used as a decision support system for public transport planning and operations in networks of small cities and towns.

Women’s safety in Public Transportation: A case study of Jaipur city, India

Women's safety in public transportation is a major point of concern for transport planners worldwide, including India. Perceptions regarding safety can significantly influence commuters' mode choice decisions. This study aims to quantify the psychological factors that can impact women's perception of safety while traveling on public transportation in Jaipur, India. To conduct this study, we collected data from female commuters through a questionnaire, which included questions related to the respondents' socio-economic characteristics, safety perceptions while using buses, bus preferences among different types of buses, satisfaction with various attributes of public bus services, and Likert-scale responses regarding women's safety when using public buses. We obtained a total of 439 valid responses, which were used for analysis. The factor analysis technique was employed to analyze the responses, revealing that Infrastructure and operations of public buses, Safety concerns related to boarding/alighting, Information accessibility, and Positive sentiments towards bus stops are the major factors affecting safety. The results of this study will assist policymakers and transport planners in creating safe infrastructures for women to ensure their safety during public transportation commutes. Furthermore, it will contribute to an increased mode choice share of women in public transportation.

A case for race and space in auto ownership modeling: A Los Angeles County study

Auto ownership behavior is driven by complex relationships that can vary dramatically across different traveler groups and communities. Differences in auto ownership among racial groups have been of particular interest, given ongoing efforts to advance equity in transportation outcomes. There are a number of studies documenting racial disparities in auto ownership associated with racial and ethnic residential clustering, termed “automobile mismatch.” Yet, these differences in auto ownership behavior by race and residential location are virtually never considered in models of travel behavior, despite calls for the consideration for race in transportation planning and decision making. This study aims to bridge the gap between understandings of the connections between race and space and transportation outcomes, using Los Angeles County as a case study. A series of auto ownership model specifications are used to investigate statistical connections between the racial and ethnic categories of residents, and neighborhoods, revealing systematic variations across racial and spatial dimensions. The composite model, which includes racial and spatial indicators, outperforms the base model, suggesting that the inclusion of race and space explains significantly more information on variations in auto ownership and provides a superior fit to the data. Our findings also suggest that the exclusion of racial and spatial indicators may lead to overestimation of certain effects, and may completely misrepresent the importance of certain household, individual-level, and built environment effects in explaining auto ownership preferences. Given the increasing attention to equity and representation in transportation outcomes, models that exclude considerations for race and space may be poorly positioned to support meaningful transportation equity analyses.

A methodology for optimal placement of energy hubs with electric vehicle charging stations and renewable generation

The use of electric vehicles and renewable energy sources can significantly contribute to the reduction of pollution levels, fostering a cleaner and more sustainable environment. In addition to their positive environmental impact, electric vehicles can also serve as energy storage units, enabling a bidirectional energy flow between the vehicles and the grid. Despite these promising prospects, a disjointed approach to charging infrastructure planning overlooks the synergies between the energy and transportation ecosystem. This calls for a holistic and coordinated approach to infrastructure development that harnesses the benefits emerging from the convergence of electric vehicles, renewable energy, and transport planning. This paper presents a methodology for the optimal placement of future Energy Hubs for electric vehicle charging and renewable generation. The methodology uses data from open-source datasets involving renewable energy sources, traffic density, charging patterns, road topology, and land use. The optimization problem is formulated as a multi-objective linear programming problem, with the objectives of minimizing the number of Energy Hub units, minimizing electric vehicles charging radius coverage and distance from power substations, and maximizing energy generation. The methodology is demonstrated through an application in Trondheim, Norway, which produces a Pareto front for decision-makers to evaluate the best trade-offs between objectives.

A Methodology for a Comprehensive Evaluation of an Urban Transport Network Structure Using Geographical Information Systems (GIS)

Abstract The transportation network is the most important component of an urban infrastructure. The efficiency of a region’s transportation system can be understood by the effectiveness of its transport network arrangement. The current study employs Geographical Information Systems (GIS) to assess the structure of a transport network in various clusters of the Hyderabad Metropolitan Area (HMA). The study focuses on a thorough assessment of the transport (or) road network structure in terms of various criteria such as connectivity, accessibility, maturity, and development. The study also categorizes each Transport Network Structural Evaluation Criteria (TNSEC) level as “very low, low, medium, high, or very high”. The goal of this research is to create a Road Network Structural Performance Index (RNSPI), which is usually used to measure the efficiency of a study area’s transportation network structure. The study’s findings serve as a foundation for city transportation planners to put efforts in the planning to enhance network facilities in the study region. The study also investigates the utility of Arc GIS software in assessing the structure of an urban transport network.

Developing B2C freight trip generation model from Courier Express Parcel establishments: A case study of two Indian cities

A panoptic study of transportation planning requires an investigation of both passenger and freight transportation for the holistic growth of the concerned infrastructure. The increase in online purchases in the last few years has surcharged the courier, express and parcel (CEP) sector and the inclusion of freight trips generated by such establishments is essential while exploring urban freight transport scenarios. This paper essentially explores the different parameters which impact B2C freight trip generation and employs the ordinary least square (OLS) regression approach to model the same. A combined dataset of 104 CEP establishments from two cities in Northeast India, Guwahati and Silchar, was collected using an establishment-based freight survey (EBFS). Modelling inferences showed that delivery executives (DE), gross floor area (GFA) of the establishment, and category of clients (COC) were significant variables in forecasting B2C freight trip generation. The statistical results also showed a positive correlation between the predictors and the B2C freight trips. The estimation of the B2C freight trip model showed that CEP establishments are large freight traffic generators which will provide insight to the urban planners for policy making and r emedial measures.

Roadways for People: Rethinking Transportation Planning and Engineering by Lynn Peterson (review)

Roadways for People: Rethinking Transportation Planning and Engineering by Lynn Peterson (review)