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Smart city article details
| Title | A Predictive Compact Model Of Effective Travel Time Considering The Implementation Of First-Mile Autonomous Mini-Buses In Smart Suburbs |
|---|---|
| ID_Doc | 3744 |
| Authors | Udal A.; Sell R.; Kalda K.; Antov D. |
| Year | 2024 |
| Published | Smart Cities, 7, 6 |
| DOI | http://dx.doi.org/10.3390/smartcities7060151 |
| Abstract | Highlights: What are the main findings? A general mathematical methodology and calculation model have been proposed, which allow taking into account most of the important factors that determine the impact of the introduction of first-mile autonomous vehicles on the daily time use of suburban residents. Following the compact modelling approach, an easily understandable and definable set of source data with a minimum volume has been proposed, which allows to reach the desired result. What is the implication of the main finding? A practical tool for shaping transport solutions and local government decisions: Thanks to the transparency of the model and the easy-to-understand input data, the transport planners and local governments can perform estimation calculations without long and complex scientific studies. Predictive capability of the model: a minimalistic and easy-to-understand input data set enables preliminary assessments of the implementation of autonomous vehicles for various local governments and suburbs located near metropolitan centres. An important development task for the suburbs of smart cities is the transition from rigid and economically inefficient public transport to the flexible order-based service with autonomous vehicles. The article proposes a compact model with a minimal input data set to estimate the effective daily travel time (EDTT) of an average resident of a suburban area considering the availability of the first-mile autonomous vehicles (AVs). Our example case is the Järveküla residential area beyond the Tallinn city border. In the model, the transport times of the whole day are estimated on the basis of the forenoon outbound trips. The one-dimensional distance-based spatial model with 5 residential origin zones and 6 destination districts in the city is applied. A crucial simplification is the 3-parameter sub-model of the distribution of distances on the basis of the real mobility statistics. Effective travel times, optionally completed with psycho-physiological stress factors and psychologically perceived financial costs, are calculated for all distances and transportation modes using the characteristic speeds of each mode of transport. A sub-model of switching from 5 traditional transport modes to two AV-assisted modes is defined by an aggregated AV acceptance parameter ‘a’ based on resident surveys. The main output of the model is the EDTT, dependent on the value of the parameter a. Thanks to the compact and easily adjustable set of input data, the main values of the presented model are its generalizability, predictive ability, and transferability to other similar suburban use cases. © 2024 by the authors. |
| Author Keywords | autonomous shuttle vehicle; autonomous vehicle acceptance; compact model; distance distribution function; effective travel time; first-mile transport; psycho-physiological stress factor; smart city suburb; travel time model |
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