Mobile Planning Research Articles

Adapting the ITF's Transport Policy with a Focus on the EU's Strategy of Sustainable Mobility

Urban regions worldwide face increasing challenges in mobility planning due to transformative developments such as climate change, energy crises, migration, digitalisation, and the rise of artificial intelligence. In Europe, frameworks like the European Union's Sustainable and Smart Mobility Strategy and the International Transport Forum's (ITF) policy measures aim to create sustainable, multimodal, and efficient urban transport systems. This paper explores how these frameworks can be integrated to enhance urban mobility governance, focusing on the Brussels-Capital Region’s Good Move plan. The plan emphasises shared mobility, digitalised multimodal systems like mobility as a Service (MaaS), and a regulatory framework that balances innovation with public oversight. Through a "learning by doing" approach, this study highlights the interplay between public and private actors, effective data governance, and market regulation to establish a viable MaaS ecosystem. Key findings underline the potential of MaaS to reduce urban emissions, improve accessibility, and promote sustainable travel while addressing regulatory challenges such as data-sharing, competition safeguards, and equitable mobility subsidies. The paper concludes with actionable recommendations to optimise MaaS integration and support urban regions in achieving resilient, livable cities through sustainable mobility solutions.

RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning

RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning

Social perception of transport services: case study at the Autonomous University of Mexico State

This study analyzes the social perception of the mobility system at the Autonomous University of Mexico State. The survey categorizes findings into five key dimensions: accessibility, jobs, mobility and connectivity, safety and public health, and livability. About accessibility (transport services, stops and financial means), the analysis reveals a significant reliance on urban transport 39%, and the Potro Bus service 22%, and perceived efficiency and cost-effectiveness; the stops of mobility service on University community was 1 or 2, and the cost of daily travel was 1.50 USD. The mobility and connectivity (level of satisfaction, punctuality and average distance), around 29% acknowledge the efficiency of the transportation system and economic viability, because is free for students. Safety and public health (accidents, carbon footprint and inclusivity), with 78 % reporting no accidents, and 43% praising the inclusiveness. Moreover, 70% are interested to learn about their carbon footprint associated with transport. The livability (University projects, Urban mobility plans and Technological tools), involves actively educating and engaging in sustainable transportation initiatives with technological and environmental point of view. Additionally, the research introduces the application of Social Life Cycle Assessment methodologies to evaluate the environmental and social impacts of mobility services, aligning with ODS.

The correspondence between urban transformation and sustainable urban mobility planning indicators in Nasr City District over five consecutive political eras (1956–2024)

ABSTRACT Urban Transformation has become a phenomenon in Egypt. With rapid changes within the Egyptian society, politics, and governance over the decades, skylines and images of its cities become more noticeable. This directly affected transportation infrastructure, modes, networks and urban mobility patterns, with most changes taking place in the urban areas of the Greater Cairo Region (GCR). While Egypt signed the New Urban Agenda in 2016, which aligns the process of urban development with the Sustainable Development Goals (SDGs), there might be stark controversies with the actual implementation on the ground concerning achieving sustainable urban mobility. The objective of this research was to investigate the relationship between traditional transportation planning interventions and the Sustainable Urban Mobility Planning (SUMP) indicators. A qualitative method was adopted, based on a longitudinal study on the macro and micro scales to assess Nasr City district’s urban transformation in terms of urban mobility and land use over five consecutive political eras (1956-2024). The physical transformation of the road cross-section and transportation modes of Mostafa AL Nahas Road, a main artery in NC district presented a deeper insight into the urban mobility planning interventions in NC. Furthermore, a matrix was designed to evaluate the correlation between the mobility interventions in NC and the sustainable Mobility indicators. The research reached the main conclusion that while mobility measures solely focused on easing the traffic flow and resolving congestion, urban transformation of the NC district has and will continuously witness the struggle between following SUMP and non-sustainable mobility interventions.

Politics and administration in support of transformation for sustainable mobility: a case study of the municipality Berlin–Pankow

The local political system with responsibility for transport planning is in the process of adapting to the goal of sustainable mobility. The resulting mobility policies and the associated planning are bringing about changes in structures and processes that involve governance innovations in decision-making, which are the objects of investigation in this case study. The central, mediating role of stakeholders involved in the administrative framework in a goal-oriented planning process that contributes to the implementation of sustainable mobility measures is part of an internal and external impact analysis conducted in the municipality of Pankow, a district in Berlin (Federal Republic of Germany). In an ex-post process evaluation, which included interviews with key stakeholders in the mobility planning process, we identified several planning cases that represent a typical change in mental infrastructures and ways of dealing with conflicts. These individual processes and adaptations in planning enable public administrators to deal with a transformation of the local living conditions by taking people’s mobility needs into account. Political conflicts in planning that occur on a local level and affect people’s behavior are generally circumvented or deferred rather than managed resulting in a transition that is non-transparent and complicating the local implementation of sustainable mobility.

The Impact of Mobile Data Cost on Consumer Price Sensitivity: A Study of a Hotel Booking App

The Impact of Mobile Data Cost on Consumer Price Sensitivity: A Study of a Hotel Booking App Mobile data cost arises from the perception that mobile data are more expensive than Wi-Fi because of additional charges incurred when exceeding fixed data quotas. Understanding mobile data cost is a global and industry-wide concern as the perception of this cost is common in both developed and developing countries, and even subtle behavioral shifts because of this cost can have significant impacts given the prevalence of mobile shopping. Using hotel search data, we find that consumers are approximately twice as price sensitive when using mobile data compared with Wi-Fi, leading to an average revenue reduction of $17 per hotel booking. Additionally, consumer search effort decreases across decision stages when using mobile data rather than Wi-Fi, showing that mobile data users pursue satisfactory options without extensive search effort, obtain less product information, and therefore rely more on price information, becoming more price sensitive. This study provides implications for mobile shopping environments in which limited mobile data plans are common, suggesting that firms should consider consumers’ connectivity types in marketing strategies, offer data subsidies to encourage more thorough searches, and develop customized recommendations and app versions for mobile data users and that policymakers should monitor potential price discrimination to protect consumer interests.

Problems with Implementation of Sustainable Urban Mobility in Selected Polish Cities

The concepts of sustainable development and later sustainable mobility were used as principal ideas to formulate transport policies for Polish cities since the early 1990s. This paper aims to review the implementation of these policies over the past 30 years. It presents changes and developments in urban transport systems in selected Polish cities, together with shifts in the travel behavior of their residents. A major factor contributing to the increase in car travel is the growing rate of motorization. The current state of urban transport subsystems—including public transport, road networks, parking, and pedestrian and bicycle infrastructure—is examined. Additionally, related issues such as spatial planning, road safety, and air pollution are discussed. Although most city councils have adopted sustainable mobility policies, their implementation remains unsatisfactory. The paper concludes with insights from nearly three decades of experience, highlighting obstacles that hinder the achievement of intended goals, such as the lack of national legislation and guidance on sustainable urban mobility planning and limited political backing. However, two recently adopted national strategic documents offer hope for progress in addressing sustainable mobility challenges.

Unveiling Travel Patterns and Challenges Considering Mixed Land Use and User Behavior in an Indian City

Transportation and land use are inextricably linked. Travel patterns are influenced by the location, design of new developments, and users’ behavior. In many Tier II cities in India where rapid transit systems are unavailable, such as Vadodara, spatial and transportation planning lack integration with land use. This disconnect neglects user behavior and travel needs, resulting in congestion and pollution as ongoing, reactive challenges rather than being addressed through sustainable and proactive solutions. This research used a triangulation approach incorporating literature analysis, questionnaire surveys, and field observations to enhance the robustness of the results. After a comprehensive analysis, findings were derived from the user behavior, traffic patterns, and field observations for mixed land use. The study revealed a heavy reliance on private vehicles for work trips (53%) despite low satisfaction with sustainable transport options (average rating of 2.8 out of 5). Infrastructure issues, such as disorganized parking and pedestrian safety concerns, exacerbate congestion and pollution. This study recommends a Comprehensive Mobility Plan (C.M.P.) and a land use and transport integration (LUTI) cell to address these issues and promote sustainability. Future research should explore comparative studies, socioeconomic factors, and legal frameworks for sustainable development.

Trajectory Planning With A* Algorithm and Tracking With Multiple Controllers

ABSTRACTThis article consists of mathematical modelling of differential drive mobile robot (DDMR), path planning and tracking application via multiple controller usage. Robot kinematic and dynamic models were constructed and simulated in virtual 2D map environment. A* algorithm was applied to the 2D map problem to acquire optimal pathfinding, efficiency and flexibility in trajectory planning stage. After the reference trajectory is obtained by algorithm, the robot needs to be guided using control strategy that manages the speed control of electric motors. At the first part of the control problem, kinematic based backstepping control (KBBC) were used to increase the efficiency of the control system. After that Sliding Mode Control (SMC) and Proportional‐Integral‐Derivative (PID) control strategies were applied to reduce tracking errors between reference and actual coordinate values and heading angle value. To test the robustness and efficiency of control combinations, two different simulation systems were designed using Matlab‐Simulink Software. First system was designed for the non‐disturbance condition, while the second system included disturbance torque and an additional mass applied condition. Test results showcasing the performance of the controllers are presented in the concluding section, through trajectory tracking and error comparison graphs.

Optimal Configuration for Shared Electric-hydrogen Energy Storage for Multiple Integrated Energy Systems With Mobile Hydrogen Transportation

The flexible operation and storage of hydrogen and electric energy provide an effective path for the development of low-carbon energy and transportation systems. This paper introduces a configuration method for electric-hydrogen shared energy storage supporting the multiple energy and capacity demands of integrated energy systems (IESs). A Stackelberg game-based shared energy framework with gaseous hydrogen transportation by transportation network for shared energy storage operators (SESO) and IESs is established. In this framework, the electric power and electric storage sharing are accomplished by power lines, while the shared hydrogen is achieved by the transportation of mobile trucks. The target of the energy storage operator is to maximize its trading benefits with IESs and lower the life-cycle cost of the whole system, while the IESs aim to meet their energy demand and lower the operation cost via energy storage sharing. To solve this planning model, a two-level sine cosine based grey wolf optimizer (GWO-SCA)-bisectional method is provided to realize the system configuration, mobile hydrogen planning, and economic trading of the shared energy operator. A case study with 3 IESs, real-world geographic roads, and environmental conditions is carried out to verify the effectiveness of the method and the life-cycle configuration and operation economy of the shared energy storage. The comparisons show that the proposed energy storage sharing frame can achieve a higher energy utilization ratio of 92% and the proposed method can solve the two-level problem more efficiently, the calculation time is reduced by 80.2%.

An Enhanced Deep Q Network Algorithm for Localized Obstacle Avoidance in Indoor Robot Path Planning

Path planning is a key task in mobile robots, and the application of Deep Q Network (DQN) algorithm for mobile robot path planning has become a hotspot and challenge in current research. In order to solve the obstacle avoidance limitations faced by the DQN algorithm in indoor robot path planning, this paper proposes a solution based on an improved DQN algorithm. In view of the low learning efficiency of the DQN algorithm, the Duel DQN structure is introduced to enhance the performance and combined with a Prioritized Experience Replay (PER) mechanism to ensure the stability of the robot during the learning process. In addition, the idea of Munchausen Deep Q Network (M-DQN) is incorporated to guide the robot to learn the optimal policy more effectively. Based on the above improvements, the PER-D2MQN algorithm is proposed in this paper. In order to validate the effectiveness of the proposed algorithm, we conducted multidimensional simulation comparison experiments of the PER-D2MQN algorithm with DQN, Duel DQN, and the existing methodology PMR-DQN in the Gazebo simulation environment and examined the cumulative and average rewards for reaching the goal point, the number of convergent execution steps, and the time consumed by the robot in reaching the goal point. The simulation results show that the PER-D2MQN algorithm obtains the highest reward in both static and complex environments, exhibits the best convergence, and finds the goal point with the lowest average number of steps and the shortest elapsed time.

Budgetary tracking of food and nutrition security funding in selected Sahel and West Africa regions from 2017 to 2019.

The longer-term trend towards decreasing foreign assistance has aroused great interest in tracking domestic funding given that more than half of the anticipated additional funding for nutrition is expected from domestic sources. Given the limited trend analysis of nutrition budgets across developing countries, this review aimed to examine trends in nutrition financing as a proxy of national commitment to nutrition. We explored the programme-based budget allocations and expenditure from 2017 to 2019 in the Chad Republic, Gambia and Ghana for food and nutrition security (FNS) activities in various sectors. The total annual allocations for FNS activities from 2017 to 2019 in the Chad Republic, Gambia and Ghana were €24,796,501, €155,416,112 and €3,299,472,194 of which 93.5%, 15.7% and 100% respectively of allocated funded were expended. The proportion of FNS allocations and expenditure was <5% of the gross domestic product across the three countries. Three-quarters (the Chad Republic and Gambia) and one-quarter (Ghana) of all FNS activities were nutrition-friendly as compared to being nutrition-specific/sensitive. Of the nutrition-specific/sensitive activities, about 9 in 10 were nutrition-sensitive. The main thematic areas of FNS activities were agriculture/food systems, health, education, water, sanitation and hygiene. There were significant resource gaps in FNS budget allocations and expenditure across the three countries making it difficult to establish a consistent domestic funding trend. Resource mobilisation plans to bridge budget implementation gaps for domestic funding are urgently needed to scale-up government commitments toward the attainment of the sustainable development goals in these countries.

ExAq-MSPP: An Energy-Efficient Mobile Sink Path Planning Using Extended Aquila Optimization Algorithm

Wireless sensor networks play a crucial role in gathering data from remote or hard-to-reach locations, enabling real-time monitoring and decision-making in a wide range of industries and applications. The mobile sink path planning (MSPP) enables mobile sinks (e.g., drones or rovers) to navigate through the environment, collecting data from different sensor nodes, ensuring comprehensive coverage, and adaptively addressing changing conditions. Still, the energy-efficient routing with minimal delay is the challenging aspect. This research focuses on improving data gathering in wireless sensor networks by introducing an efficient routing protocol. In this proposed protocol, sensor nodes are initially deployed using Voronoi diagrams to ensure uniform network coverage. The network is then divided into clusters using the low-energy adaptive clustering hierarchy (LEACH) algorithm for energy-efficient routing. To optimize the path planning of a mobile sink for data collection, we introduce the extended Aquila (ExAq) optimization algorithm, which uses a multi-objective fitness function considering factors such as delay, residual energy, link quality, priority, and distance. Simulation results demonstrate the effectiveness of the proposed ExAq-MSPP protocol in terms of reduced delay, improved network lifetime, higher packet delivery ratio, enhanced residual energy, and increased throughput compared to existing protocols with the values of 1.169, 99.857, 99.920, 0.997, and 255.306, respectively. Thus, the energy-efficient routing and optimizing path planning for mobile sinks, the proposed ExAq-MSPP protocol can extend network lifetime, increase data accuracy, and provide more robust performance under changing environmental conditions.

Application of ant colony optimization algorithm based on farthest point optimization and multi-objective strategy in robot path planning

With the continuous development of high technology and the continuous progress of intelligent industry, mobile robots are gradually widely used in various fields. In the field of mobile robot research, path planning is crucial. However, the current ant colony optimization algorithm applied to mobile robot path planning still has some limitations, such as early blind search, slower convergence speed, and lower path smoothness. To overcome these problems, this paper proposes an ant colony optimization algorithm based on farthest point optimization and multi-objective strategy. The algorithm introduces new heuristic information such as the normal distribution model, triangle inequality principle, smoothness function, safety value function, etc. It adopts multi-objective comprehensive evaluation indexes to judge the quality of paths. For the high-quality and poor-quality paths, the algorithm takes additional pheromone increments and decrements in pheromone concentration to speed up the algorithm’s convergence. Besides, the farthest point optimization strategy is used to improve the quality of the paths further. Finally, to verify the algorithm’s effectiveness, the algorithm is compared with 20 existing methods for solving the robot path planning problem, and the experimental results show that the algorithm exhibits better results in terms of convergence, optimal path length, and smoothness. Specifically, the algorithm can produce the shortest path in four different environments while realizing the least number of turns with faster convergence, further proving the effectiveness of the improved algorithm in this paper.

GIS-Based Geospatial Analysis for Identifying Optimal Locations of Residential On-Street Electric Vehicle Charging Points in Birmingham, UK

Global urbanization and the growing need for sustainable transportation solutions are increasing the demand for electric vehicle (EV) infrastructure. This research aims to identify optimal locations for Residential On-Street Electric Vehicle Charging Points (RO-EVCPs) that are essential for residents without access to off-street parking and to support the transition to a sustainable urban environment in Birmingham. A GIS-based model, incorporating key location criteria such as accessibility, environmental impact, and infrastructure compatibility, can effectively identify suitable locations for RO-EVCP deployment, improving access and inclusivity for electric mobility. The study develops a customized geographic information systems (GIS) model, utilizing the Analytic Hierarchy Process (AHP) for weighting location criteria, with validation through geospatial tools like Google Earth® and Street View. The model generates a spatial suitability map, categorizing areas into optimal, moderate, and limited suitability for EV charging, with an emphasis on accessibility, environmental impact, and inclusiveness. High-priority streets and recommended charging point numbers are identified. The findings emphasize accessibility and inclusiveness, crucial for individuals without off-street parking, promoting an equitable transition to electric mobility. This research contributes to sustainable urban mobility planning by advocating data-driven decision-making in EV infrastructure development, aligning with climate change mitigation objectives.

Evaluating the accessibility of collective fixed-route paratransit service in developing cities: A case study of Djibouti

This study provides a comprehensive evaluation of accessibility for collective fixed-route paratransit services in Djibouti, examining current conditions through diverse data sources, including geographic information systems and household surveys. The proposed accessibility model considers walking time, waiting time, and coverage ratio. It correlates the decrease in accessibility based on walking time with the reduction in paratransit ridership. To assess the impact of waiting time, the model compares an acceptable waiting time (5 min) with the average waiting time of the service. A threshold walking time of 8 min defines the service coverage area. Results indicate that the collective fixed-route service covers only 39.49% of the city’s urban area. Although accessibility is higher in the city center, the outskirts face substantial accessibility gaps. This analysis not only reveals the spatial distribution of accessibility within the city but also highlights areas with urgent improvement needs. The study includes paratransit accessibility maps with color-coded levels of accessibility across the city. These findings contribute to the growing research on paratransit accessibility, emphasizing the integration of spatial and temporal factors for enhanced urban mobility planning. The insights from this research can support evidence-based policy-making and promote sustainable urban development in the region.

Will new tram lines enhance the connectivity and walkability? A case study of Sakarya

&lt;p&gt;This study investigates the impact of planned tram lines on walkability and accessibility in Sakarya, utilizing Geographic Information Systems (GIS) for spatial analysis. The research evaluates the catchment areas of proposed tram stops, assessing their suitability and coverage, and examines how these areas integrate with existing public transport routes. By calculating time-oriented catchments for 5, 8, and 10-minute walking distances, the study identifies service gaps and redundancies in the public transport network. The findings reveal that the new tram lines will enhance accessibility by extending coverage to high-density areas and potentially reducing the demand on existing bus services. The analysis also highlights the overlap between bus transit lines and tram stops, suggesting optimizations to improve network efficiency. The results offer valuable insights for urban planners, aiming to optimize Sakarya’s public transport system to be more inclusive and sustainable. This study contributes to urban mobility planning by providing a detailed understanding of how new tram lines can improve connectivity and support sustainable urban development.&lt;/p&gt;

Association between land use features and changes in walking patterns from pre-pandemic to post-pandemic: A case study of city of Sydney (2013–2023)

While the impact of the pandemic on active mobility patterns is widely studied in several cities, the underlying characteristics that describe the heterogeneity in changes in active mobility are less understood. This is particularly important for post-pandemic active mobility planning. This study aims to investigate and describe the association between urban population and land-use features, as well as changes in the spatio-temporal patterns of walking from pre-pandemic to post-pandemic through a case study of the city of Sydney, Australia, using 11 years of pedestrian count data from 2013 to 2023. The findings indicate that during the pandemic, the average daily pedestrian traffic in Sydney decreased significantly compared to the pre-pandemic period. However, since experiencing the lowest pedestrian traffic in 2020, activities in the study area have shown signs of partial recovery, with a 51% increase observed in 2023. The observed changes in pedestrian activities are, however, spatially heterogeneous. Modeling results reveal that areas with greater commercial land use, more points of interest (POIs), higher population density, and higher network connectivity experienced a significant negative change in the number of walking trips from the pre-pandemic to the pandemic period. Areas with higher percentages of educational and residential use and with higher personal income experienced smaller changes in pedestrian activities during the pandemic compared to the pre-pandemic period. During the post-pandemic recovery, the influential features remain mostly unchanged; however, the association direction is the opposite.

Mobility against all odds: the experiences of Chinese international students in Portugal amid the COVID‐19 pandemic

AbstractThe COVID‐19 pandemic significantly affected international student mobility. Chinese international students had to deal not only with challenges such as border closures and lockdowns but also with discrimination and stigmatisation. In this paper, we examine the decisions of Chinese students to engage in international mobility and their experiences in Portugal during the pandemic, relying on 23 in‐depth interviews with Chinese international students living in Portugal during the first year of the COVID‐19 pandemic (2020–2021). Our findings indicate that, although these students were concerned about the COVID‐19 pandemic and its risks, they tended to prioritise their academic endeavours, while their mobility plans did not appear to have been significantly affected by the pandemic. These findings provide new insights into how international students structure their mobility plans and make sense of their experiences of studying abroad during “unsettling events”.

Sustainable mobility challenges – case study of the offshore center in Gdansk transport accessibility

Urban mobility planning is one of the key elements in building a sustainable future. Strategic management of urban transport traffic not only reduces congestion and minimises the negative impact on the environment but also positively affects the improvement of residents' quality of life. Furthermore, following the Corporate Sustainability Reporting Directive approved by the European Union in 2023, companies are obliged to submit annual reports on their environmental impact. One of its elements is the calculation of the organization's carbon footprint, which includes emissions caused by means of transport, including emissions from commuting to work. This case study investigates the impact of transport accessibility on employee preferences and behaviour in the context of changing the premises location, using the example of the Maritime Institute of Gdynia Maritime University (GMU), located at the newly opened Offshore Center in Gdansk seaport. The research hypothesis states that the relocation to new premises with limited transport accessibility may, as a consequence, influence the choice of commuting transportation methods among employees, potentially leading to a shift towards less sustainable means of transport. The results of the research survey prove that there is a complex interconnection between transport accessibility, commuting behaviours, and sustainable mobility initiatives. This pilot study aims to contribute to urban mobility planning by exploring how to transport accessibility influences employee behaviour and by proposing strategies to improve commuting conditions and promote more sustainable solutions.