Performance analysis and fleet requirements of automated demand-responsive transport systems as an urban public transport service

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جزئیات بیشتر

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۲۰۲۱

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scopus – master journals – JCR

ایمپکت فاکتور

۴٫۲۷۶ در سال ۲۰۲۰

شاخص H_index

۲۶ در سال ۲۰۲۱

شاخص SJR

۰٫۹۰۱ در سال ۲۰۲۰

شاخص Quartile (چارک)

Q1 در سال ۲۰۲۰

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ندارد

پرسشنامه

ندارد

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رفرنس

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Performance analysis and fleet requirements of automated demand-responsive transport systems as an urban public transport service


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Performance analysis and fleet requirements of automated demand-responsive transport systems as an urban public transport service

Abstract

The  introduction of public transport services by  fully automated  vehicles can  potentially change the way public transit services will  be  operated, as  they allow shifting from rigid scheduled and route-bound  services towards flexible, demand-responsive  services. This study examines the potential performance of an  Automated Demand Responsive Transport Service  (ADRTS) as  a replacement for  scheduled bus services and simulates the effects of demand levels, vehicle capacity, vehicle dwell time and the initial vehicle distribution on system performance in terms of fleet size  and system costs. The simulation tool allows sim- ulating the operation of the ADRTS in a complete graph and is applied to the case study of Arnhem, the Netherlands. For this case study it has been shown that for  a minimum fleet size  following the imposed constraints, the operational costs range between 0.84 and 1.22

Euros and the average passenger wait time ranges between 2 and 6 min, according to the assumptions made on  demand and operational parameters. The  operational costs of  the ADRTS showed to be  in  the same range of  the current bus system, while providing a demand-responsive transport service with an  average waiting time of  around 4 min per passenger-trip. The  economies of scale, which play an  important role in  public transport, are  also apparent in  the simulated ADRTS operations.

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  1. Introduction

The  development of  automated  driving technology advances rapidly and automated  vehicles (AVs)  are   commonly assumed to  play   a  significant role  in  transport systems of  the future (Alessandrini et al.,  ۲۰۱۵; Benevolo et al.,  ۲۰۱۶; Correia et al., 2016; Lam,  ۲۰۱۵; Wang, 2015). The  advancement of AVs potentially poses both opportunities and threats to conventional public transport systems. On one  hand, if AVs rapidly enter the private car  market, offering greater comfort and potentially productive travel time, public transport ridership may decline leading to efficiency losses. On the other hand, AVs pave the way  for significantly reducing the operational costs of public transport services which are  often dominated by driver labour costs. Moreover, the introduction of AVs into public transport services have the potential to revolutionize the way  in which public transport services are  provisioned and consumed by facilitating a shift into more flexible and demand

responsive modes of operations. Conventional public transport systems offer  scheduled services in rigid networks, in which passengers have to  adjust their travel plans accordingly.

In this paper we envision an Automated Demand Responsive  Transport System (ADRTS) which dynamically responds to tra- vel requests using a centrally dispatched fleet of highly automated vehicles. The flexible and lower-capacity service enabled by ADRTS can  potentially substitute conventional public transport in networks characterized by low  to  moderate levels of many-to-many demand pattern  and where labour costs make the network-wide provision of  DRT services prohibitive. Hitherto, demand-responsive services have proven to be exceptionally cost-intensive and therefore not  economically viable beyond very  low-demand or except for premium services, and usually require exceptionally high subsidy levels in developed countries which are  characterized by high labour costs (Ferreira et al., 2007; Fu, 2002; Sayarshad and Chow,  ۲۰۱۵).

The  operation of an  ADRTS is evaluated using a simulation model that allows assessing operator and passenger costs under alternative system specifications and scenarios. The main contributions of this study are: (1) determining the fleet size that will  minimize ADRTS system (i.e.  passenger and operational) costs under given constraints on  maximum passenger waiting time; (2)  determine the minimum fleet size  for  operating an  ADRTS as  a  substitute to current public transport, and; (3) benchmark the passenger and operational costs to the existing bus  system as well  as a non-automated DRT system. To the best of our  knowledge, ADRTS have not  been modelled as a substitution for an  existing urban public transport net- work. Previous studies have either assumed ADRTS to  serve all  demand for  mobility and offer  a door-to-door  service (i.e. automated taxi) or considered a single corridor or feeder service operations.

The  ADRTS is  simulated for  a  case  study based on  the city  of Arnhem in  the Netherlands, for  which the influence of demand, vehicle capacity, vehicle dwell time and the initial vehicle location on the system performance is analysed in terms of operational costs as  well  passenger generalized travel costs. Given  the novelty of AV, assumptions made on  the opera- tional and cost  parameters are  of a speculative nature and the results presented in this paper should be  therefore viewed as a first  glimpse on  the impact the introduction of AV might have on  public transit services.

The  paper is organized as  follows: In Section 2, we  review the automated public transport landscape with respect to emerging mobility solutions, taxonomy of ADRTS and the literature on modelling ADRTS. In Section 3, the ARDTS envisioned in this study is described along with the approach adopted in this study for modelling its operations. The case  study and the scenario design are  described in Section 4, followed by the results. We conclude with a discussion of the results, the limita- tions of the study and suggestions for further research.

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