Urban Mobility Systems Research Articles

Analysis of the Public Transportation Compactness on Urban Mobility System by Bus

Analysis of the Public Transportation Compactness on Urban Mobility System by Bus

Bike-sharing systems: Effects on physical activityin a Spanish municipality

Introduction: Urban mobility (such as walking or biking) and public Bike-Sharing Systems (BSS) have begun to emerge through programs and services that drive change from the strong culture of dependence on motor vehicles in most developed countries. At the international level, the 2030 Agenda of the United Nations (UN) opted to establish objectives for sustainable development, addressing the need to establish changes in urban mobility. The World Health Organization (WHO) has concluded that physical inactivity and being overweight / obesity are the fourth and fifth risk factors for non-communicable diseases in the world, respectively. The objective of this study is to know if a BSS has been able to serve as a means of promoting Physical Activity (PA) in the urban environment. Material and Methods: A quantitative and longitudinal study has been designed with data collection and analysis from July 2009 to January 2012. The sample consisted of a total of 3,268 users and a total of 59998 observations were recorded (Men: n = 42,411; Women: n = 17,587). SPSS 21.0 and ANOVA were used for statistical analysis. Results: Users between the ages of 20 and 44 have spent an average of 30.7 minutes, between 45 and 64 years an average of 36 minutes and between 65 and 79 years an average of 51.1 minutes. Conclusions: The data suggest that the WHO (2010) PA recommendations may be being met. BSS can favor the practice of PA in the urban environment, and thus, be able to promote less polluted and traffic-congested environments. Men from 65 to 79 years old have had the most average minutes of use. The routes that took the most minutes were those that go between the same stations and those that pass between stations on the urban outskirts.

Multi-Sensor Fusion Technology, Spatial Simulation and Environment Mapping Algorithms, and Real-World Connected Vehicle Data in Smart Sustainable Urban Mobility Systems

Multi-Sensor Fusion Technology, Spatial Simulation and Environment Mapping Algorithms, and Real-World Connected Vehicle Data in Smart Sustainable Urban Mobility Systems

Spatial equity analysis of urban public services for electric vehicle charging—Implications of Chinese cities

• An accessibility measurement model is developed for electric vehicle public charging facilities. • A procedure of spatial equity evaluation is further devised. • The methodology is performed for ten representative Chinese cities to demonstrate its applicability and examine their spatial equity in charging infrastructure. • Over half of the cities exhibit spatial inequity in access to charging infrastructure. • Targeted polities are required to reduce regional disparities in recharging service provision. The widespread adoption of electric vehicles (EVs) is crucial for urban sustainability, which can promote the low carbon transition of urban mobility systems and increase energy independence. However, inadequate access to charging infrastructure has posed significant challenges on penetration to the mass market, which requires an equitable distribution of public charging facilities among residents. Current planning and deployment of public charging facilities only take efficiency into account, with limited attention to the spatial equity in distribution. Hence, this study proposes a spatial statistical approach to evaluate whether electric vehicle charging services (EVCS) are equitably distributed. An innovative accessibility measurement model is first developed for EVCS, considering competition over changing demand and different charging capacities. On this basis, a spatial autocorrelation analysis procedure is further designed to investigate spatial patterns of residential accessibility and detect regional disparities. The proposed methodology is tested with the top ten cities in China by their capacity of EVCS, where most cities exhibit significant inequitable distribution but with different regional characteristics. It is demonstrated that the methodology can improve the accuracy of measurement while remaining easy to implement. Therefore, it can serve as a policy tool for EVCS planning to maximize its capability to facilitate EV uptake.

An Intermodal Dispatcher for the Assignment of Public Transport and Ride Pooling Services

This paper describes the components of an intermodal dispatcher of ride pooling requests to integrate these urban mobility systems with the public transport network in an urban area, thus making possible a new intermodal system. The intermodal dispatcher makes use of a prior dispatcher, developed exclusively for conventional ride pooling systems and a method that filters out the requests that have few possibilities of being served using the public transport system, leaving them to be served directly by ride pooling vehicles. The assignments of customers to vehicles of the ride pooling system are finally determined by an integer programming model of reduced dimensions, so that it can be solved efficiently by conventional solvers as shown in the preliminary computational results included in the paper.

Geospatial Data Mining, Computer Vision-based Lane Detection and Object Localization Algorithms, and Mapping and Navigation Tools in Smart Urban Mobility Systems

Geospatial Data Mining, Computer Vision-based Lane Detection and Object Localization Algorithms, and Mapping and Navigation Tools in Smart Urban Mobility Systems

When Shared Autonomous Electric Vehicles Meet Microgrids: Citywide Energy-Mobility Orchestration

Problem definition: We develop a crossdisciplinary analytics framework to understand citywide mobility-energy synergy. In particular, we investigate the potential of shared autonomous electric vehicles (SAEVs) for improving the self-sufficiency and resilience of solar-powered urban microgrids. Academic/practical relevance: Our work is motivated by the ever-increasing interconnection of energy and mobility service systems at the urban scale. We propose models and analytics to characterize the dynamics of the SAEV-microgrid service systems, which were largely overlooked by the literature on service operations and vehicle-grid integration (VGI) analysis. Methodology: We develop a space-time-energy network representation of SAEVs. Then, we formulate linear program models to incorporate an array of major operational decisions interconnecting the mobility and energy systems. To preventatively ensure microgrid resilience, we also propose an “N − 1” resilience-constrained fleet dispatch problem to cope with microgrid outages. Results: Combining eight data sources of New York City, our results show that 80,000 SAEVs in place of the current ride-sharing mobility assets can improve the microgrid self-sufficiency by 1.45% (benchmarked against the case without grid support) mainly via the spatial transfer of electricity, which complements conventional VGI. Scaling up the SAEV fleet size to 500,000 increases the microgrid self-sufficiency by 8.85% mainly through temporal energy transfer, which substitutes conventional VGI. We also quantify the potential and trade-offs of SAEVs for peak electricity import reduction and ramping mitigation. In addition, microgrid resilience can be enhanced by SAEVs, but the actual resilience level varies by microgrids and by the hour when grid contingency occurs. The SAEV fleet operator can further maintain the resilience of pivotal microgrid areas at their maximum achievable level with no more than a 1% increase in the fleet repositioning trip length. Managerial implications: Our models and findings demonstrate the potential in deepening the integration of urban mobility and energy service systems toward a smart-city future.

Skyport location problem for urban air mobility system

With rapid advancement in aerial vehicle technologies, air taxi is drawing keen interest as a new type of transportation service. One of the necessary elements for air taxi-based transportation service system is a skyport, which is a designated area for take-off and landing of air taxis. In planning a skyport network for air taxi transportation system, it is important to consider midair congestion between air taxis. Severe congestion increases the risk of collisions, which in turn increases the complexity in scheduling and routing in the subsequent operations phase.In this study, we propose a novel hub location problem (HLP) that incorporates traffic congestion caused by intersecting vehicles along hub-to-hub arcs. Modeling congestion in an HLP formulation involves nonconvex bilinear terms, which makes it difficult to solve. We tackle this challenge by exploiting a property of an optimal solution and reformulating the original model to obtain a linear formulation. We also develop a heuristic algorithm based on a genetic algorithm to handle large-size problems for practical applications. Using the proposed model and solution methods, extensive experiments have been conducted to study optimal design of air taxi network under various environments. Our analyses demonstrate that viability of air taxi service is a complicated function of many factors including collision risk, system cost, airspace design, to name a few. Our model can offer quantitative understanding of such complex relationships to assess and develop strategies to improve the viability of an air taxi transportation system.

Predicting hourly origin–destination demand in bike sharing systems using hurdle models: Lisbon case study

Bike Sharing Systems (BSS) have gained popularity all over the world. BSS success requires efficient location of stations and the rebalancing of the network, both of which depend on predicted demand and flows between stations. Therefore, predicting BSS demand is essential to optimize logistic operations, as well as network reliability and availability. The present work develops statistical models to predict the hourly origin–destination demand in the Lisbon BSS network. Models predict the number of trips that will occur between an origin station and a destination station (OD pair) at a certain hour, as well as the duration of such trips. This study also examines the effect of several explaining variables, including the weather, intermodality effects, effects of station location close to different types of points of interest and the time/hour effect. These effects were all tested using different statistical models, including the Generalized Linear Models (GLM) and zero-augmented ones: the hurdle model and the zero-inflated model. The hurdle model showed the best fit to the data and several explaining variables exhibited statistical significant effects. A discussion on the potential logistic and policy impacts of such findings is also provided, so that BSS network design and operations can incorporate them within the urban mobility system policy.

Public policies and strategies of a complex system: the change in the urban mobility system of Bogotá

Purpose – Urban mobility is one of the most relevant themes in discussions regarding quality of life in large urban centers worldwide. It is a challenge that local governments have been facing due to a significant growth in the urban population. The purpose of this study is to analyze the changes in public transport made by the local government in the city of Bogotá, ColombiaDesign/methodology/approach – It is an in-depth case study of a qualitative nature, based upon primary (interviews and observation) and secondary data. Data was collected in Brazil and Colômbia.Findings – The case signaled a significant change process by improving urban mobility through the implementation of successful public policies and strategies. The findings indicated that transforming a chaotic public transport system into a point of reference in this field is a notable effort.Practical implications – This study provides insights to public administrators that manage organizations that operate complex systems and pluralistic contextsOriginality/value – This paper contributes to the field by discussing a unique case study in which the administration of a large capital of a South American country promoted a substantial change in the urban mobility system, tackling obstacles and developing an efficient approach.

Circular economy concepts in urban mobility alternatives using integrated DIBR method and fuzzy Dombi CoCoSo model

This study aims to explore the circular economy concepts which are also sustainable and can be used for the 17th Sustainable Development Goals (SDGs) adopted by United Nations member countries. The study focuses on the urban mobility setting. The prioritization of the possible CE concepts for a planning authority in a big city is examined where the decision process is subject to certain restrictions such as existing natural resources, financial and human capital. A case scenario is used to illustrate the formulation and solution of the problem. The method used to solve the problem comprises two stages. First, the DIBR method (Defining Interrelationships Between Ranked criteria) is presented to determine the weights of criteria. Then second, the fuzzy Dombi based Combined Compromise Solution (D’ CoCoSo) is proposed for prioritizing the circular economy concepts for urban mobility. The proposed multi-criteria framework allows decision-makers to better perceive the relationship between the criteria, which contributes to rational reasoning and objective evaluation of alternatives. The DIBR method enables decision-makers to better perceive relationships between criteria, since it considers relations between adjacent criteria. Thus, it eliminates the problem of defining relations between remote criteria, which often decreases the consistency of results in subjective models. The results obtained for case scenario emphasize that among four alternatives “Building infrastructure for zero-emission vehicles and energy storage” should be prioritized over relatively cheaper remedies such as “Using big data solutions to optimize urban mobility systems”. In that respect, the planners are expected to be direct and long-term focused in choosing the CE concepts. The method used here can be extended for other decision-making problems of planners in achieving SDGs for urban planning.

The Other Side of the (Policy) Coin: Analyzing Exnovation Policies for the Urban Mobility Transition in Eight Cities around the Globe

Many cities all over the world highlight the need to transform their urban mobility systems into more sustainable ones, to confront pressing issues such as air and noise pollution, and to deliver on climate change mitigation action. While the support of innovations is high on the agenda of both national and local authorities, consciously phasing-out unsustainable technologies and practices is often neglected. However, this other side of the policy coin, ‘exnovation’, is a crucial element for the mobility transition. We developed a framework to facilitate a more comprehensive assessment of urban mobility transition policies, systematically integrating exnovation policies. It links exnovation functions as identified in transition studies with insights from urban mobility studies and empirical findings from eight city case studies around the world. The findings suggest that most cities use some kinds of exnovation policies to address selective urban mobility issues, e.g., phasing-out diesel buses, restricting the use of polluting motor vehicles in some parts of the city, etc. Still, we found no evidence for a systematic exnovation approach alongside the innovation policies. Our framework specifies exnovation functions for the urban mobility transition by lining out policy levers and concrete measure examples. We hope that the framework inspires future in-depth research, but also political action to advance the urban mobility transition.

Rhythmic Control of Automated Traffic—Part II: Grid Network Rhythm and Online Routing

Connected and automated vehicle (CAV) technology is providing urban transportation managers tremendous opportunities for better operation of urban mobility systems. However, there are significant challenges in real-time implementation as the computational time of the corresponding operations optimization model increases exponentially with increasing vehicle numbers. Following the companion paper (Chen et al. 2021), which proposes a novel automated traffic control scheme for isolated intersections, this study proposes a network-level, real-time traffic control framework for CAVs on grid networks. The proposed framework integrates a rhythmic control method with an online routing algorithm to realize collision-free control of all CAVs on a network and achieve superior performance in average vehicle delay, network traffic throughput, and computational scalability. Specifically, we construct a preset network rhythm that all CAVs can follow to move on the network and avoid collisions at all intersections. Based on the network rhythm, we then formulate online routing for the CAVs as a mixed integer linear program, which optimizes the entry times of CAVs at all entrances of the network and their time–space routings in real time. We provide a sufficient condition that the linear programming relaxation of the online routing model yields an optimal integer solution. Extensive numerical tests are conducted to show the performance of the proposed operations management framework under various scenarios. It is illustrated that the framework is capable of achieving negligible delays and increased network throughput. Furthermore, the computational time results are also promising. The CPU time for solving a collision-free control optimization problem with 2,000 vehicles is only 0.3 second on an ordinary personal computer.

APPLICATION OF MUNICH AGILE CONCEPTS FOR MBSE AS A HOLISTIC AND SYSTEMATIC DESIGN OF URBAN AIR MOBILITY IN CASE OF DESIGN OF VERTIPORTS AND VERTISTOPS

AbstractThis paper will adopt the Munich Agile Concepts (MAGIC) on the design of Vertistops and Vertiports (Verti-X) for Urban Air Mobility (UAM) Systems. Vertiports and Vertistops are single or multi-landing spaces for air taxis, which are electric-powered vertical take-off and landing (eVTOLs) aircraft. The target of this paper is to apply a holistic approach how to design so called Verti-X in a holistic and system of system method from the Requirement-, Function-. Architecture- and the Implementation phase. The MAGIC approach contains all of the requierd phases which are necessary to build up such a complex design of Verti-X. Therefore, based on the literature survey, we have determined the key components of the Verti-X design with a thorough requirement analysis. Then, we have followed the existed criteria and regulations to design a valid and verified Verti-X which fulfills all the requirement. Furthermore, the focus of this paper is to apply the first four phases of MAGIC regarding the requirement, function, architecture and the implementation of such Verti-X Design.

Investigating socio-spatial differences between solo ridehailing and pooled rides in diverse communities

Transformative mobility services present both considerable opportunities and challenges for urban mobility systems. Increasing attention is being paid to ridehailing platforms and connections between demand and continuous innovation in service features; one of these features is dynamic ride-pooling. To disentangle how ridehailing impacts existing transportation networks and its ability to support economic vitality and community livability it is essential to consider the distribution of demand across diverse communities. In this paper we expand the literature on ridehailing demand by exploring community variation and spatial dependence in ridehailing use. Specifically, we investigate the diffusion and role of solo requests versus ride-pooling to shed light on how different mobility services, with different environmental and accessibility implications, are used by diverse communities. This paper employs a Social Disadvantage Index, Transit Access Analysis, and a Spatial Durbin Model to investigate the influence of both local and spatial spillover effects on the demand for shared and solo ridehailing. The analysis of 127 million ridehailing rides, of which 15% are pooled, confirms the presence of spatial effects. Results indicate that density and vibrancy variables have analogue effects, both direct and indirect, on demand for solo vs pooled rides. Instead, our analysis reveals significant contrasting effects for socio-economic disadvantage, which is positively correlated with ride-pooling and negatively with solo rides. Additionally, we find that higher rail transit access is associated with higher demand for both solo and pooled ridehailing along with substantial spatial spillovers. We discuss implications for policy, operations and research related to the novel insight on how pooled ridesourcing relate to geography, living conditions, and transit interactions.

Robust matching-integrated vehicle rebalancing in ride-hailing system with uncertain demand

With the rapid growth of the mobility-on-demand (MoD) market in recent years, ride-hailing companies have become an important element of the urban mobility system. There are two critical components in the operations of ride-hailing companies: driver–customer matching and vehicle rebalancing. In most previous literature, each component is considered separately, and performances of vehicle rebalancing models rely on the accuracy of future demand predictions. To better immunize rebalancing decisions against demand uncertainty, a novel approach, the matching-integrated vehicle rebalancing (MIVR) model, is proposed in this paper to incorporate driver–customer matching into vehicle rebalancing problems to produce better rebalancing strategies. The MIVR model treats the driver–customer matching component at an aggregate level and minimizes a generalized cost including the total vehicle miles traveled (VMT) and the number of unsatisfied requests. For further protection against uncertainty, robust optimization (RO) techniques are introduced to construct a robust version of the MIVR model. Problem-specific uncertainty sets are designed for the robust MIVR model. The proposed MIVR model is tested against two benchmark vehicle rebalancing models using real ride-hailing demand and travel time data from New York City (NYC). The MIVR model is shown to have better performances by reducing customer wait times compared to benchmark models under most scenarios. In addition, the robust MIVR model produces better solutions by planning for demand uncertainty compared to the non-robust (nominal) MIVR model.

Accelerating sustainable mobility and land-use transitions in rapidly growing cities: Identifying common patterns and enabling factors

Urban growth has been increasing rapidly across the globe, in particular in low and middle-income developing countries. As city populations and GDP per capita rise exponentially, cities tend to experience similar challenges related to urban development and transport/mobility.One of the most problematic issues emerges when urban growth drives car-oriented urban development. This is characterised by a range of unsustainable patterns such as low-density development, urban sprawl, lack of plans and infrastructure to accommodate collective transport and active travel, and significant efforts and investments to meet the demand for private motorised vehicle use. For emergent cities, the risk is that these developments lead to highly inefficient, unhealthy and unsustainable urban systems that are difficult to remedy.This paper aims to identify recurrent governance and policy factors across sectors, as well as macro factors, that tend to contribute to car-dependent urban mobility systems in rapidly growing cities. It draws on qualitative and quantitative research findings from five under-researched Eastern European and Middle Eastern cities: Tallinn, Bucharest, Skopje, Adana and Amman. Data examining the evolution of urban mobility in these cities were collected as part of the Horizon2020 EU funded project CREATE.The paper investigates the extent to which car-dependent urban development processes can be avoided in rapidly growing cities, to support transitions towards liveable and sustainable cities. Finally, it provides policy recommendations targeting growing cities with low levels of car-use, in particular in Sub-Saharan Africa. It highlights the importance of acting swiftly to achieve targets such as the Sustainable Development Goals, the New Urban Agenda or the Paris Agreement, by supporting policies fostering efficient, sustainable and inclusive urban mobility and land-use across sectors and levels of governance.

Review of Whole System Simulation Methodologies for Assessing Mobility as a Service (MaaS) as an Enabler for Sustainable Urban Mobility

Mobility as a Service (MaaS) is an emerging concept that is being advanced as an effective approach to improve the sustainability of mobility, especially in densely populated urban areas. MaaS can be defined as the integration of various transport modes into a single service, accessible on demand, via a seamless digital planning and payment application. Recent studies have shown the potential reduction in the size of automobile fleets, with corresponding predicted improvements in congestion and environmental impact, that might be realized by the advent of automated vehicles as part of future MaaS systems. However, the limiting assumptions made by these studies point to the difficult challenge of predicting how the complex interactions of user demographics and mode choice, vehicle automation, and governance models will impact sustainable mobility. The work documented in this paper focused on identifying available methodologies for assessing the sustainability impact of potential MaaS implementations from a whole system (STEEP—social, technical, economic, environmental, and political) perspective. In this research, a review was conducted of current simulation tools and models, relative to their ability to support transportation planners, to assess the MaaS concept, holistically, at a city level. The results presented include: a summary of the literature review, a weighted ranking of relevant transportation simulation tools per the assessment criteria, and identification of key gaps in the current state of the art. The gaps include capturing the interaction of demographic changes, mode choice, induced demand, and land use in a single framework that can rapidly explore the impact of alternative MaaS scenarios, on sustainable mobility, for a given city region. These gaps will guide future assessment methodologies for urban mobility systems, and ultimately assist informed decision-making.

Competition or cooperation: Relationship between carsharing and other travel modes

Carsharing is becoming an important member of urban mobility systems. The relationship between carsharing and other travel modes, is the base for deciding the proportional role of carsharing. This article defines the relationship, competition or cooperation, based on whether carsharing strengthening or weakening the expected function of other travel modes from the transport system perspective. It proposes the relationship should be studied under the specific characteristics of carsharing trips (e.g., the spatiotemporal distribution), and establishes a method for evaluating the coordination of carsharing with other modes. A survey about carsharing trips was conducted, and valid data generated by 1,330 carsharing users were obtained. The spatiotemporal characteristics of carsharing substituting for subway, buses, taxis, private cars, and nonmotorized vehicles have been analyzed, and the substitution benefits were also evaluated. The results indicate that carsharing in Shanghai was mainly used for long-distance trips in suburbs during off-peak hours, which generally formed a cooperative relationship with public transit, taxis, and nonmotorized vehicles. Phenomenon that carsharing substituting for public transit mainly occurred in long-distance trips in suburbs, with an average 40–50 min travel time saving. Carsharing also substituted for long-distance non-motorized vehicle trips, which improved the mobility of those travelers. To further enhance the coordination, the layout of carsharing stations and operation strategies need to be optimized to reduce the carsharing travel demands during peak hours within urban areas, and to promote carsharing as a substitute for private cars.

Social Network Approach to Analyze Stability and Variability of Travel Decisions

Large-scale changes are expected for urban mobility systems, triggered by digitalization and various other factors such as climate concerns or urbanization. For researchers and planners, it is therefore becoming increasingly important to understand the determinants of variability and stability of travel decisions. The motivation for the study is that, in transportation research and modeling frameworks, travel choices usually derive from individual traits and accessibility variables. What is underrepresented by such an approach is that decisions are also socially embedded. The authors postulate that mobility patterns are strongly interwoven with the way people configure their social networks. The paper introduces and discusses an empirical approach to investigate the social embeddedness of mobility decisions. The basic premise of the approach is that social network configurations provide an important setting for daily life in general and individual travel decisions in particular. Analysis is based on a three-phase interview study, conducted in Karlsruhe, Germany. The analytical approach reveals that a substantial part of travel is only loosely coupled to generalized costs of transport. Instead, the motivational degree linked to certain relationships largely influences willingness to travel and the relative stability of everyday life. Relationships that are internally satisfying or extremely familiar to people appear highly persistent. Furthermore, relationships that provide a certain degree of flexibility appear changeable, though not necessarily in all dimensions. Only a very small number of relationships appear both substitutable and changeable.