This paper presents an agent-based model (ABM) to simulate and compare two different operation strategies of a public transport service in small-sized cities, namely a fixed-route transit (FRT) and a demand-responsive transport (DRT) service, under varying demand rates and supply configurations. The ABM builds upon a previous work by the Authors, where flexible and feeder services of a Mass Rapid Transit system were simulated. In this paper, instead of a many-to-one pattern typical of a feeder service, we considered a many-to-many one. The objective is to investigate the conditions that make a DRT more attractive than a FRT in small-sized cities and guide its design considering the demand fluctuation, land-use pattern, service constraints and passenger preferences. A dispatching algorithm for the DRT allows to assign each new trip request to a vehicle, and a couple of origin and destination stops, updating the vehicle schedule in real time. The service includes fixed and virtual stops, allowing request consolidation and balancing operator-related (cost of the service) and user-related (quality of service) needs. The model is applied to Vittoria (Italy), a small city with 60,000 residents in Southern Italy where most trips are made by car, also due to the absence of an urban public transport service. First results highlight the benefits of providing a flexible service compared to a fixed one to minimize detours, waiting times and walking distances experienced by passengers while allowing for a higher shareability and efficiency of the service.

Designing demand responsive transport services in small-sized cities using an agent-based model / Calabro, G.; Le Pira, M.; Giuffrida, N.; Inturri, G.; Ignaccolo, M.; de Correia, G. H. A.. - In: TRANSPORTATION RESEARCH PROCEDIA. - ISSN 2352-1457. - 69:(2023), pp. 759-766. (Intervento presentato al convegno 3rd International Conference on Transport Infrastructure and Systems, TIS ROMA 2022 tenutosi a ita nel 2022) [10.1016/j.trpro.2023.02.233].

Designing demand responsive transport services in small-sized cities using an agent-based model

Giuffrida N.;
2023-01-01

Abstract

This paper presents an agent-based model (ABM) to simulate and compare two different operation strategies of a public transport service in small-sized cities, namely a fixed-route transit (FRT) and a demand-responsive transport (DRT) service, under varying demand rates and supply configurations. The ABM builds upon a previous work by the Authors, where flexible and feeder services of a Mass Rapid Transit system were simulated. In this paper, instead of a many-to-one pattern typical of a feeder service, we considered a many-to-many one. The objective is to investigate the conditions that make a DRT more attractive than a FRT in small-sized cities and guide its design considering the demand fluctuation, land-use pattern, service constraints and passenger preferences. A dispatching algorithm for the DRT allows to assign each new trip request to a vehicle, and a couple of origin and destination stops, updating the vehicle schedule in real time. The service includes fixed and virtual stops, allowing request consolidation and balancing operator-related (cost of the service) and user-related (quality of service) needs. The model is applied to Vittoria (Italy), a small city with 60,000 residents in Southern Italy where most trips are made by car, also due to the absence of an urban public transport service. First results highlight the benefits of providing a flexible service compared to a fixed one to minimize detours, waiting times and walking distances experienced by passengers while allowing for a higher shareability and efficiency of the service.
2023
3rd International Conference on Transport Infrastructure and Systems, TIS ROMA 2022
Designing demand responsive transport services in small-sized cities using an agent-based model / Calabro, G.; Le Pira, M.; Giuffrida, N.; Inturri, G.; Ignaccolo, M.; de Correia, G. H. A.. - In: TRANSPORTATION RESEARCH PROCEDIA. - ISSN 2352-1457. - 69:(2023), pp. 759-766. (Intervento presentato al convegno 3rd International Conference on Transport Infrastructure and Systems, TIS ROMA 2022 tenutosi a ita nel 2022) [10.1016/j.trpro.2023.02.233].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/266060
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