Transportation Planning Research Articles

Enhancing Road Traffic Prediction Using Data Preprocessing Optimization

Traffic prediction is essential for transportation planning, resource allocation, congestion management and enhancing travel experiences. This study optimizes data preprocessing techniques to improve machine learning-based traffic prediction models. Data preprocessing is critical in preparing the data for machine learning models. This study proposes an approach that optimizes data preprocessing techniques, focusing on flow-based analysis and optimization, to enhance traffic prediction models. The proposed approach explores fixed and variable orders of data preprocessing using a genetic algorithm across five diverse datasets. Evaluation metrics such as root mean squared error (RMSE), mean absolute error (MAE) and R-squared error assess model performance. The results indicate that the genetic algorithm’s variable order achieves the best performance for the ArcGIS Hub and Frementon Bridge Cycle datasets, fixed order one preprocessing for the Traffic Prediction dataset and variable order using the genetic algorithm for the PeMS08 dataset. Fixed order 2 preprocessing yields the best performance for the XI AN Traffic dataset. These findings highlight the importance of selecting the appropriate data preprocessing flow order for each dataset, improving traffic prediction accuracy and reliability. The proposed approach advances traffic prediction methodologies, enabling more precise and reliable traffic forecasts for transportation planning and management applications.

A multi-objective model for integrated supplier order allocation and supply chain network transportation planning decision-making

Effective supplier order allocation (SOA) and transportation planning (TP) are critical for the smooth operation of supply chains, especially in dynamic markets with evolving customer demands. While previous research has made significant strides in addressing these areas individually, studies that integrate both aspects while considering a comprehensive set of objectives are limited. This study introduces an innovative multi-objective model that concurrently addresses total operational costs, supplier defect rates, sustainability performance, and supply chain network disruption risks. The model applies an augmented max–min approach of fuzzy multiple objective linear programming (AMM-FMOLP), which enhances overall utility while ensuring balanced performance across all objectives. The inclusion of all five objectives in the model is essential for a holistic evaluation of supply chain performance. The model’s effectiveness and practicality are validated through a case study involving a computer numerical control (CNC) machine tool assembly company, under various scenarios. Additionally, sensitivity analysis reveals how adjustments in supply chain structure can further improve performance. Moreover, the execution process of this study does not require expert intervention, making it a unique data-driven decision model particularly suitable for intelligent supply chain management and decision-support systems. This approach enhances the flexibility and resilience of supply chains, enabling them to effectively respond to unforeseen events and minimize their impact on business operations, especially in volatile global markets.

New challenges arise from consolidation of gender, health and transport research

BackgroundBased on a chapter in the recently published 3rd edition of Health of the Move, this article summarizes past and current knowledge regarding how gender, health and transport (GHT) interact, and implications for policy and practice in both transport and health spheres. MethodsThe chapter, ‘Gender, transport and health: Emerging trends and gaps in global research’, comprises an extensive review of research on these topics and their intersections in recent decades. It summarizes key concepts from the earliest publications regarding GHT issues and provides insights from 155 scientific articles published between 2000 and 2023. Results/findings“Gender”, a socially constructed concept reflecting culture-specific perspectives on the roles of men and women, is often used generically to reflect “sex”, that is solely the biological differences. Similarly, the assumption that transport is “gender neutral” remains a powerful arbiter, particularly within engineering and policy. Key findings are: 1) women's mobilities are significantly affected by violence. There is a need to address its association with hegemonic masculinity through sustained focus on the harmful attitudes and behaviours of this gender identity. 2) Women walk more and cycle less than men with positive and negative impacts to health depending on context. Transport infrastructure safety and accessibility must be improved to ensure women's health is equitably associated with travelling actively. 3) Women are more involved in caring for others than men. A gender-sensitive approach to mobilities must consider care-giving needs throughout the lifecycle. ConclusionsGender differences in travel are substantial and highly relevant to health equity. Gender-sensitive planning requires fuller integration of walking, cycling and intermodal solutions into regular transport planning, and requires strong policies to make all transport-related spaces accesible. Major gaps appear in research, particularly how hegemonic masculinity is related to road, gender and criminal violence that clearly limits the mobility of specific groups by gender.

Multiscale Analysis of Pedestrian Crossing Distance

Problem, research strategy, and findings Crossing distance is considered a factor in both pedestrian safety and behavior. However, it has seldom been quantified within or across entire cities or related to walking outcomes. Combining data encoded in OpenStreetMap and drawn from high-resolution satellite imagery, we measured formal pedestrian crossings throughout a dense European city (Paris [France]), a dense American city (San Francisco [CA]), and a less-dense, more car-centric American city (Irvine [CA]). This granular approach—covering roughly 49,000 total crossings—identified inter- and intraurban spatial patterns in the distribution of pedestrian crossing distance, including clusters of long crossings that likely deter walking and increase its risk. By overlaying recent pedestrian–vehicle collisions on these novel data sets we found that longer crossing distance correlated with increased likelihood of collisions, raising the salience of traffic-calming interventions. Takeaway for practice Quantifying pedestrian crossing distance at the scale of entire municipalities empowers transportation planners to identify pedestrian-hostile crossings (individuals and clusters), add context to collision trends, and geographically target locations for traffic calming. These cases collectively demonstrate how the increasing prioritization of the automobile in city planning quantitatively changes (and degrades) the pedestrian environment, as well as how low-tech investments, such as sidewalk extensions and refuge islands, can mitigate these trends.

Effects of sea-land breeze on air pollutant dispersion in street networks with different distances from coast using WRF-CFD coupling method

A WRF-CFD coupled model with high-temporal resolution is employed to investigate pollutant dispersions during a sea-land breeze (SLB) day in an identical building block configuration at three locations in Shanghai, China, and the blocks are set at the coast (L1), downtown (L2) and inland (L3). The results show that the localized wind speed drops below 1 m/s during the sea-land-breeze collision period (SLBCP), which leads to pollutant accumulation. The closer the block is to the coast, the earlier occurrence and longer duration of SLBCP, and Blocks L1, L2, and L3 experience SLBCPs during the morning peak traffic period (MPTP), low-traffic-volume period (at midday), and evening peak traffic period (EPTP), with durations of 2.5 h, 2 h, and 1 h, respectively. Due to the low wind speeds of both land breezes and sea breezes during the overlap of MPTP and SLBCP, the pollutant concentration in Block L1 is significantly elevated, and the peak concentration is two times higher than that in the non-coastal blocks (L2 and L3). Block L2 shows a peak concentration during the midday low-traffic-volume period, while no evident peak concentration is found in L3 in EPTP. The mean concentrations in Blocks L1, L2, and L3 during EPTP are 72 %, 57 %, and 31 % lower than those during MPTP, respectively. This suggests that SLB has significantly different effects on wind fields and pollutant dispersion in building blocks with different distances from the coast and can provide reference data for transport planning in coastal cities.

Optimal transport through a toll station

Abstract We address the problem of optimal transport with a quadratic cost functional and a constraint on the flux through a constriction along the path. The constriction, conceptually represented by a toll station, limits the flow rate across. We provide a precise formulation which, in addition, is amenable to generalization in higher dimensions. We work out in detail the case of transport in one dimension by proving existence and uniqueness of solution. Under suitable regularity assumptions, we give an explicit construction of the transport plan. Generalization of flux constraints to higher dimensions and possible extensions of the theory are discussed.

Smarter but more unequal transport? How socioeconomic and digital inequalities hinder adoption of mobility apps in the Global South

All over the world, cities are becoming “smarter.” The improved use of data generated by the transport system (e.g. smart cards data), combined with GPS trackers and citizens’ mobile data enabled the development of a new generation of smarter mobile apps (e.g., Waze) and several local real-time public transport services and trip planners. These technologies have the potential to reduce transport inequalities via two mechanisms. First, governments can develop more efficient and evidence-based public transport plans. Second, citizens have access to better, real-time information about public transport for trip planning and, thus, can make better—i.e., more efficient or cheaper—decisions regarding their everyday mobility. To assess whether citizens’ appropriation of smart mobility—as with their appropriation of any other digital service—depends strongly on having a certain set of socioeconomic and digital attributes, we analyzed both a mobility survey and a digital inequalities survey based on representative samples of adult Uruguayans living in the capital Montevideo. We find that while the use of mobility apps increased in the second half of the 2010s, the adoption of these tools was stratified by traditional digital inequalities, such as type of internet access and digital literacy, and by variables that predict inequalities in both digital and transport fields, such as age, gender and education. As a result, mobility continues to be stratified in favor of those who are more knowledgeable (i.e., tech-savvy) and have greater access to digital technology. Thus, “smart mobility” has failed to ameliorate—and may even exacerbate—transport inequality. Policy implications of these findings are discussed.

‘There is a lot of traffic at the school gate in the morning which makes me nervous’: exploring children’s current and desired school commutes

ABSTRACT Although children are the primary users of many spaces, their voices are often unheard in transport planning. We therefore do not know much about children’s barriers or wishes regarding mobility. What is known, however, is that children have become less independent in their daily mobility, with parents (or guardians) increasingly driving children instead of allowing them to walk and cycle. The decline in active mobility is worrisome, since active mobility is beneficial to children, but incorporating children’s voices in transport planning can be conducive to increased active mobility of children. The objective of this paper is to explore the wishes and barriers of children regarding school commuting. Data was collected from a survey completed by 1251 pupils and through workshops with four schools in a residential neighbourhood in Brussels, Belgium. We found that there is a significant gap between the current and desired transport modes of pupils, with an important untapped potential for cycling. We also found that traffic safety is a predominant worry of pupils. Additionally, when suggesting the re-design of their school neighbourhood, the most recurring suggestions from pupils included walking and cycling infrastructure, and reduced access to the school neighbourhood for cars.

Extending quantum detailed balance through optimal transport

We develop a general approach to setting up and studying classes of quantum dynamical systems close to and structurally similar to systems having specified properties, in particular detailed balance. This is done in terms of transport plans and Wasserstein distances between systems on possibly different observable algebras.

Spatial factors associated with usage of different on-demand elements within mobility hubs: a systematic literature review

ABSTRACT Mobility hubs offer a strategic opportunity to enhance multimodal transportation and reduce greenhouse gas emissions within the transport sector. Identifying the spatial factors determinants influencing the usage of mobility hub components is essential for policymakers and transport planners aiming to identify their optimal locations. This study undertakes a systematic literature review and ranking of spatial factors associated with the usage of key on-demand services within mobility hub elements, including bike sharing, scooter sharing, car sharing, ride hailing and taxi and electric vehicle charging stations. Utilising databases such as Web of Science, Google Scholar and Francis & Taylor, we evaluated 119 records, identifying 39 key factors from social and built environments that are associated with usage of the on-demand elements. Key findings highlight the significance of population density, employment density, proximity to public transport, recreational POIs and household income, along with a noted negative association with the factor slope. This research contributes to exploring how these factors align across various on-demand mobility services that can be potentially used for policymakers, and transportation planners in evaluating potential strategies for the optimal allocation and development of mobility hubs.

Implementation of smart mobility and relationship with transportation planning and regional development: A case study of South Tangerang city

Urbanization and suburbanization have led to high population growth in certain city regions, resulting in increased population density and mobility. Therefore, there is a need for a concept to address congestion, public transportation, information and communication systems, and non-motorized vehicles. Smart mobility is a concept of urban development as part of the smart city concept based on information and communication technology. Through this concept, it is expected that transportation services will be easily accessible, safe, comfortable, fast, and affordable for the community. This research aims to analyze smart mobility and its relationship with regional transportation planning and the development of South Tangerang, as well as to design a policy strategy model for the planning and development of South Tangerang with smart mobility. The research method used in this study is a mixed method, including analyzing the relationships and weighting of relationships between variables using the Cross Impact Multiplication applied to a classification (MICMAC) matrix. Multi-criteria decision analysis (MCDA) with Promethee software is also used to obtain the necessary policies. The results of this research indicate that the measurement of relationships between variables shows that smart mobility influences regional transportation planning, smart mobility affects regional development, and regional planning affects regional development. This research also provides alternative policies that policymakers should implement in a specific order. First, ensure the availability of public transportation; second, improve public transportation safety; third, enhance public transportation security; fourth, improve public transportation routes; fifth, provide real-time information access; sixth, improve transportation schedules; and seventh, increase the number of bicycle lanes.

Potentials of digital twin system for analyzing travel behavior decisions

This review explores the potential of digital twin systems to provide a more holistic representation of travel behavior and support transportation planning and policymaking. The paper introduces the concept of digital twins, their key characteristics, and their applications in various domains, including transportation. It discusses the traditional methods used in travel behavior analysis and their limitations, as well as the potential advantages of digital twin systems, such as the integration of heterogeneous data sources, real-time monitoring and prediction, and the ability to simulate and evaluate various policy scenarios. The review also identifies the key components of digital twin systems, the challenges associated with their implementation, and the current state of research on digital twins and related methods in travel behavior analysis. The paper highlights research gaps and future directions, emphasizing the need for privacy-preserving techniques, real-world case studies, and the integration of digital twins with decision support systems. Finally, the review discusses the broader implications of digital twin systems for transportation planning and policymaking, concluding by emphasizing the need for interdisciplinary collaboration and stakeholder engagement to fully realize the potential of digital twins in analyzing travel behavior decisions and shaping the future of transportation systems.

The deeper and wider social impacts of transportation infrastructure: From travel experience to sense of place and academic performance

Traditional transportation planning emphasized the direct economic benefits of transportation infrastructure. While there is a growing awareness of the environmental consequences, social impacts are frequently overlooked due to methodological complexities and political neglect. Although existing literature acknowledges the existence of transportation-related social exclusion, it primarily concentrates on quantifiable and immediate short-term social outcomes arising from improved accessibility and affordability, which facilitate place-to-place interactions and activities. There has been limited exploration of the more intricate and indirect societal impacts associated with transportation. This paper argues that new transportation infrastructure not only affects mobility and travel experiences but also has deeper social impacts on the sense of place. These effects may extend to broader benefits, including academic performance, by influencing place identity, attachment, and dependency, which in turn affect daily activities unrelated to travel. Our study focuses on a university student community (N = 323), a pivotal future workforce, and investigates how the introduction of a new metro line passing through the campus reduces commuting time, subsequently enhancing academic productivity. Employing structural equation modeling method, our analysis reveals that sense of place acts as a mediator between travel experience and student engagement under the influence of transportation mode choice. These findings may have broad applicability in identifying indirect social impacts of transportation infrastructure, thus providing insights for investment decisions.

Assessment and Modelling of Walk Trips in Akure, Nigeria

The study examined and modeled the walking behavior patterns of residents in Akure, Nigeria. A multi-stage sampling approach was used to collect relevant data for assessing and modeling the walking trip patterns. The questionnaires were administered to 300 participants between May to November 2019 (6 months) across three primary residential neighborhoods in the city; high-density, medium-density, and low-density areas. The obtained data were analyzed using SPSS software and subsequently modeled using multi-variable regression techniques. The study found that 48.7% of the sampled population preferred to walk, and 49.7% perceived walking as an alternative to motorized trips. Significant differences were observed in the socioeconomic characteristics of residents, such as age and income, across the residential zones (F = 54.731, p<0.001; F = 68.278, p<0.001). The key factors that greatly influenced decision of respondents to walk included socioeconomic factors, such as income, personal car ownership, educational qualifications, and employment status, with age and sex being the least significant socioeconomic determinants. Generally, the factors that motivated respondents to choose walking as a travel mode included its relative affordability, the lack of personal vehicles, awareness of health benefits, safety and security concerns, avoidance of motorized traffic congestion, and favorable weather conditions. The findings of this study have important implications for transportation planning. The paper recommends the need to incorporate non-motorized spaces and walkways into various levels of urban planning and implementation to foster a more walkable environment and encourage active transportation in the city.

Flood risk awareness and transportation mode choice in communities with varying flooding frequencies: The cases of Bozkurt, Kastamonu, Turkey and Malanday, Marikina, Philippines

This study investigates the post-flood transportation mode choices (TMC) of communities exposed to floods of varying frequencies, focusing on Bozkurt, Turkey, recently afflicted by a major flood, and Malanday, Philippines, which endures an average of 10 floods annually. The study considers 17 factors affecting TMC, including age, occupation, income, housing type, flood experience, education level, changes in travel time, primary transportation mode, duration of residence, gender, marital status, relocation status, personal losses, disruption of daily activities, time to return to routine, satisfaction with road maintenance, and satisfaction with flood measures. Data were collected through surveys and analysed using regression analysis.The findings indicate that personal and cultural characteristics, and flood frequency, have limited effects on TMC. The most impactful factors on post-flood TMC are changes in travel time (42.11 %), personal losses (23.75 %), and satisfaction with road maintenance (11.30 %). The study demonstrates that flood risk awareness is directly related to education level and flood experience. In Malanday, where 84 % of the population are university or high school graduates, floods are regarded as routine events. In contrast, in Bozkurt, where only 37 % have similar education levels, the community experienced panic under flood conditions, adversely affecting decision-making processes.The research provides insights into how communities exposed to floods adjust their TMC, offering essential information for mitigating flood risks and increasing flood awareness. Moreover, the findings deliver suggestive information for local governments and planners in developing more effective flood management and transportation planning strategies.

Access to green and gray urban nature amenities: exploring equity in Montreal's built environment

ABSTRACT Contemporary ideologies have identified two main paradigms contributing to sustainable cities: green urban and gray urban nature. The first refers to features that make cities greener, such as parks or tree coverage. The second refers to gray but sustainable areas, such as dense areas or the proximity to key amenities that can foster active travel. Accessibility to green and gray urban nature amenities by active transport is essential for evaluating if cities are sustainable. We analyzed the accessibility to green (green spaces) and gray (food stores and pharmacies) urban nature in Montreal. The findings show that most people have sufficient access to green and gray urban nature, and low-income groups have better access than high-income groups. Areas with access to both tend to be highly dense, suggesting that dense areas have sustainable attributes. Transport planning interventions in areas lacking access are necessary to achieve sustainable goals in Montreal.

Maximizers of nonlocal interactions of Wasserstein Type

We characterize the maximizers of a functional that involves the minimization of the Wasserstein distance between sets of equal volume. We prove that balls are the only maximizers by combining a symmetrization-by-reflection technique with the uniqueness of optimal transport plans. Further, in one dimension, we provide a sharp quantitative refinement of this maximality result.

Alignment and comparison of directed networks via transition couplings of random walks

Abstract We describe and study a transport-based procedure called network optimal transition coupling (NetOTC) for the comparison and alignment of two networks. The networks of interest may be directed or undirected, weighted or unweighted, and may have distinct vertex sets of different sizes. Given two networks and a cost function relating their vertices, NetOTC finds a transition coupling of their associated random walks having minimum expected cost. The minimizing cost quantifies the difference between the networks, while the optimal transport plan itself provides alignments of both the vertices and the edges of the two networks. Coupling of the full random walks, rather than their marginal distributions, ensures that NetOTC captures local and global information about the networks and preserves edges. NetOTC has no free parameters and does not rely on randomization. We investigate a number of theoretical properties of NetOTC and present experiments establishing its empirical performance.

Integrated optimization of logistics routing problem considering chance preference

PurposeThis study aims to examine the impact of the decision makers’ risk preference on logistics routing problem, contributing to logistics behavior analysis and route integration optimization under uncertain environment. Due to the unexpected events and complex environment in modern logistics operations, the logistics process is full of uncertainty. Based on the chance function of satisfying the transportation time and cost requirements, this paper focuses on the fourth party logistics routing integrated optimization problem considering the chance preference of decision makers from the perspective of satisfaction.Design/methodology/approachThis study used the quantitative method to investigate the relationship between route decision making and human behavior. The cumulative prospect theory is used to describe the loss, gain and utility function based on confidence levels. A mathematical model and an improved ant colony algorithm are employed to solve the problems. Numerical examples show the effectiveness of the proposed model and algorithm.FindingsThe study’s findings reveal that the dual-population improvement strategy enhances the algorithm’s global search capability and the improved algorithm can solve the risk model quickly, verifying the effectiveness of the improvement method. Moreover, the decision-maker is more sensitive to losses, and the utility obtained when considering decision-makers' risk attitudes is greater than that obtained when the decision-maker exhibits risk neutrality.Practical implicationsIn an uncertain environment, the logistics decision maker’s risk preference directly affects decision making. Different parameter combinations in the proposed model could be set for decision-makers with different risk attitudes to fit their needs more accurately. This could help managers design effective transportation plans and improve service levels. In addition, the improved algorithm can solve the proposed problem quickly, stably and effectively, so as to help the decision maker to make the logistics path decision quickly according to the required confidence level.Originality/valueConsidering the uncertainty in logistics and the risk behavior of decision makers, this paper studies integrated routing problem from the perspective of opportunity preference. Based on the chance function of satisfying the transportation time and cost requirements, a fourth party logistics routing integrated optimization problem model considering the chance preference of decision makers is established. According to the characteristics of the problem, an improved dual-population ant colony algorithm is designed to solve the proposed model. Numerical examples show the effectiveness the proposed methods.

Minimizing delays of patient transports with incomplete information: A modeling approach based on the vehicle routing problem

AbstractWe investigate a challenging task in ambulatory care, the minimizing of delays of patient transports. In practice, a limited number of vehicles is available for non-rescue transports. Furthermore, the dispatcher rarely has access to complete information when establishing a transport plan for dispatching the vehicles. If additional transport is requested on demand then schedules need to be updated, which can lead to long delays. We model the scheduling of patient transports as a vehicle routing problem with general time windows and solve it as a mixed-integer linear problem that is modified whenever additional transport information becomes available. We propose a modeling approach that is designed to determine fair and stable plans. Furthermore, we show that the model can easily be modified when transports need to satisfy additional requirements, e.g., during pandemics, exemplarily the Covid-19 pandemic. To show the applicability and efficiency of our modeling approach, we conduct a numerical study using historical data from the region of Middle Franconia. The results reveal and show that, by applying mathematical optimization—or, to be more precise by solving mixed-integer linear problem formulations—one can significantly decrease delays and have considerable potential for optimized patient transports.