Value of time and reliability for urban pooled on-demand services

González, M.J. Alonso; Oort, Niels van; Cats, Oded; Hoogendoorn-Lanser, Sascha; Hoogendoorn, Serge P.

doi:10.1016/j.trc.2020.102621

Cited by 69 publications

(20 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Respondents are faced with scenarios, via stated preference experiments, and are asked to imagine their usage behavior. In one of these studies, Alonso-González et al [22] analyzed the time-reliability-cost trade-offs for a hypothetical pooled on-demand service in the Netherlands. Firstly, they discovered a higher willingness to pay for pooled on-demand services than for traditional public transit.…”

Section: Introductionmentioning

confidence: 99%

“…We would like to stress that, to date, ridepooling-user requirements are still fuzzy, as are current customers' characteristics. Among the few existing studies, several rely on research from small and/or short-term test operations [32], surveyed people who have not experienced ridepooling yet [22,30], or make a comparison to the MOIA ridepooling service difficult because the service level parameters differ significantly (e.g., prices, departure time windows, operating hours) [13,34]. These studies can provide initial relevant indications but validity for customers of a real service needs to be verified.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Usage and User Characteristics—Insights from MOIA, Europe’s Largest Ridepooling Service

Kostorz

Fraedrich²,

Kagerbauer

2021

Sustainability

View full text Add to dashboard Cite

New, i.e., shared and digitized, mobility services have been entering urban mobility markets around the globe. Among these new offerings is ridepooling, a mobility solution that bundles requests from passengers with similar routes in real-time and matches them with a vehicle. Ridepooling is quite novel in Germany and knowledge about users, changes in travel behavior, and impacts on the urban traffic system is scarce. To address this gap, we conducted an online survey among users and non-users of MOIA, a German ridepooling provider. Over 12,000 respondents completed the survey. The article presents results on ridepooling users’ characteristics and usage patterns. We found that MOIA users cover all age groups and are multimodal travelers—which leads us to assume that ridepooling enriches mobility portfolios and also serves as an alternative to the private car. MOIA is mostly used occasionally and, in particular, during the evening or the night. A specific focus of the article lies on users with mobility impairments as well as how and by whom ridepooling is used on work-related trips. Both topics are particularly relevant in light of changing travel patterns and transforming urban transport systems towards more sustainability.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Usage and User Characteristics—Insights from MOIA, Europe’s Largest Ridepooling Service

Kostorz

Fraedrich²,

Kagerbauer

2021

Sustainability

View full text Add to dashboard Cite

show abstract

“…We consider a system where a 30% discount is offered for sharing and we specify the private ride-hailing ride as an alternative . We employ behavioural parameters (value-of-time and willingness-to-share ’s) in-line with recent findings 36 , 37 and apply ExMAS algorithm 9 to reproduce a behaviourally rich shareability network connecting 3200 travellers to 11,000 feasible shared rides (see Methods for algorithm description). The size of travel demand sample is such that, on one hand, the critical mass needed to induce sharing can be attained and on the other hand, it represents a relatively low demand levels reached by ride-pooling services so far 38 .…”

Section: Application and Resultsmentioning

confidence: 99%

Modelling virus spreading in ride-pooling networks

Kucharski

Cats

Sienkiewicz

2021

Sci Rep

Self Cite

View full text Add to dashboard Cite

Urban mobility needs alternative sustainable travel modes to keep our pandemic cities in motion. Ride-pooling, where a single vehicle is shared by more than one traveller, is not only appealing for mobility platforms and their travellers, but also for promoting the sustainability of urban mobility systems. Yet, the potential of ride-pooling rides to serve as a safe and effective alternative given the personal and public health risks considerations associated with the COVID-19 pandemic is hitherto unknown. To answer this, we combine epidemiological and behavioural shareability models to examine spreading among ride-pooling travellers, with an application for Amsterdam. Findings are at first sight devastating, with only few initially infected travellers needed to spread the virus to hundreds of ride-pooling users. Without intervention, ride-pooling system may substantially contribute to virus spreading. Notwithstanding, we identify an effective control measure allowing to halt the spreading before the outbreaks (at 50 instead of 800 infections) without sacrificing the efficiency achieved by pooling. Fixed matches among co-travellers disconnect the otherwise dense contact network, encapsulating the virus in small communities and preventing the outbreaks.

show abstract

“…Furthermore, further research may include accommodating other modal combinations such as shared on-demand services, park and ride, kiss and ride, and car-sharing while considering supply adaptation in response to prevailing demand patterns. Future work may also enrich the model by incorporating the value of time and reliability in the behavioral modelling of passengers' preferences towards on-demand transport (Alonso-González et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Integrated route choice and assignment model for fixed and flexible public transport systems

Narayan

Cats

Oort

et al. 2020

Transportation Research Part C: Emerging Technologies

Self Cite

View full text Add to dashboard Cite

The recent technological innovations in various ICT platforms have given rise to innovative mobility solutions. Such systems could potentially address some of the inherent shortcomings of a line/schedule based public transport system. Previous studies either assumed that flexible ondemand services are used as an exclusive door-to-door service or offered as a feeder connection to high-capacity public transport services. However, users may combine line/schedule based public transport systems (Fixed PT) and on-demand services (Flexible PT) so that their travel impedance is minimized. To this end, we propose a multimodal route choice and assignment model that allows users combining Fixed and Flexible PT or use them as individual modes while demand for these services is endogenously determined. The model takes into account the dynamic demand-supply interaction using an iterative learning framework. Flexible public transport can be used to perform any part of the trip, ranging from a first/last mile service to an exclusive direct door-to-door connection. The developed model is implemented in an agent based simulation framework. The model is applied to a network centered around the city of Amsterdam, The Netherlands. Scenarios where Fixed PT and Flexible PT are offered as mutually exclusive modes or can be combined into a single journey, are analysed. Results indicate that Flexible PT is predominantly used for covering <30% of the trip length, indicating that it is mainly used as an access or egress mode to Fixed PT. This results with an overall increase in the share of public transport trips. Also, the average waiting time of Flexible PT users when used in combination with Fixed PT are lower than the scenario where each of them is used as an exclusive mode.

show abstract

Value of time and reliability for urban pooled on-demand services

Cited by 69 publications

References 44 publications

Usage and User Characteristics—Insights from MOIA, Europe’s Largest Ridepooling Service

Usage and User Characteristics—Insights from MOIA, Europe’s Largest Ridepooling Service

Modelling virus spreading in ride-pooling networks

Integrated route choice and assignment model for fixed and flexible public transport systems

Contact Info

Product

Resources

About