Heterogeneity in marginal value of urban mobility: evidence from a large-scale household travel survey in the Greater Toronto and Hamilton Area

Hawkins, Jason; Habib, Khandker Nurul

doi:10.1007/s11116-019-10041-7

Cited by 10 publications

(7 citation statements)

References 15 publications

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“…For instance, in the real-world MaaS practice, on-demand service, such as the community transport service (Mulley et al, 2018), is found to improve the travel convenience of suburban and rural areas where regular bus service is not considered as economically proﬁtable (Campisi et al, 2021; Qiao and Yeh, 2021), and can provide services for particular categories of users, such as those with disabilities (Campisi et al, 2021) and the elderly (Aberle, 2020). That is, these, to some degree, avoid the social exclusion (Hawkins et al, 2020) and the tech-gentrification (Pangbourne et al, 2020) problem of MaaS.…”

Section: Overview Of the Infrastructurementioning

confidence: 99%

Mobility as a Service and urban infrastructure: From concept to practice

Qiao

Huang

Yeh

2022

Transactions in Urban Data, Science, and Technology

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The debate about how Mobility as a Service (MaaS) will revolutionize individual and collective mobility is gaining increasing attention from researchers, industries, and public sectors. MaaS is expected to create a techno-utopia with a new organization and operation of transport systems where residents have equal access to instant and ubiquitous mobility services. However, transport service is an artifact that is highly dependent on the construction of urban infrastructure. The success of MaaS requires the support of urban infrastructure that we categorize as (1) transport-flow infrastructure, (2) information-flow infrastructure, and (3) computing-flow infrastructure. The connotation of urban infrastructure here includes not only conventional concepts, such as transportation infrastructure, but also intelligent transportation concepts, such as high-speed communication networks and autonomous fleets. Moreover, travel behavior data collected by city sensors, communication networks, and intelligent vehicles require appropriate infrastructures to dynamically compute for fleet dispatch and demand-supply match. Based on the degree of integration of these infrastructures, MaaS projects will have different results in varying cities. From concept to practice, given that a vast disparity in infrastructure exists between cities, we need an inclusive, mobile, and global understanding of the MaaS concept to make it successful in different parts of the world.

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Section: Overview Of the Infrastructurementioning

confidence: 99%

Mobility as a Service and urban infrastructure: From concept to practice

Qiao

Huang

Yeh

2022

Transactions in Urban Data, Science, and Technology

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“…[ 24,38,[58][59][60] The innovations often overlap to optimize the potential positive impacts. DRT systems and AV enabled by ITS technology are often referred to as real-time or dynamic FTS [61] and connected AV (CAV), respectively [55,62].…”

Section: Maasmentioning

confidence: 99%

“…By sharing information and resources across the transportation system MaaS can help facilitate this cross-subsidization to ensure maximum profitability and promote social equity [83]. Furthermore, since subsidies may make low density housing more attractive, planning interventions that promote walking, cycling, higher densities around employment and transit centers, and investment in high speed public transport remain important [59,102].…”

Section: Spatial and Temporal Dimensionsmentioning

confidence: 99%

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How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

2020

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Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.

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“…Despite extensive research, there is still much to be learned about the patterns of human mobility, particularly in the context of urban transportation. Investigating the mobility patterns of individuals within cities, also known as urban human mobility, holds significant implications for a wide range of disciplines, including path planning, urban planning, congestion management, and disease transmission [ 18 , 19 , 20 , 21 , 22 , 23 ]. As such, further exploration and analysis of this topic are of great importance in the academic community.…”

Section: Introductionmentioning

confidence: 99%

Identifying Important Nodes in Trip Networks and Investigating Their Determinants

Nie

Cai

et al. 2023

Entropy

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Describing travel patterns and identifying significant locations is a crucial area of research in transportation geography and social dynamics. Our study aims to contribute to this field by analyzing taxi trip data from Chengdu and New York City. Specifically, we investigate the probability density distribution of trip distance in each city, which enables us to construct long- and short-distance trip networks. To identify critical nodes within these networks, we employ the PageRank algorithm and categorize them using centrality and participation indices. Furthermore, we explore the factors that contribute to their influence and observe a clear hierarchical multi-centre structure in Chengdu’s trip networks, while no such phenomenon is evident in New York City’s. Our study provides insight into the impact of trip distance on important nodes within trip networks in both cities and serves as a reference for distinguishing between long and short taxi trips. Our findings also reveal substantial differences in network structures between the two cities, highlighting the nuanced relationship between network structure and socio-economic factors. Ultimately, our research sheds light on the underlying mechanisms shaping transportation networks in urban areas and offers valuable insights into urban planning and policy making.

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Heterogeneity in marginal value of urban mobility: evidence from a large-scale household travel survey in the Greater Toronto and Hamilton Area

Cited by 10 publications

References 15 publications

Mobility as a Service and urban infrastructure: From concept to practice

Mobility as a Service and urban infrastructure: From concept to practice

How Can Smart Mobility Innovations Alleviate Transportation Disadvantage? Assembling a Conceptual Framework through a Systematic Review

Identifying Important Nodes in Trip Networks and Investigating Their Determinants

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