Planning for Demand Responsive Bus Service for Limited Area using Simulation

EasyChair Preprint 3102, version 1

Abstract

This research aimed at evaluating the potential benefits of Demand Responsive Transport (DRT) for bus service over conventionally fixed route bus service operated over small area. This study is based on developing a hypothetical model for building a future scenario, resembling the working of flexible transport model by estimating total demand and assigning the estimated demand by dynamic routing of buses to different time window setting between pickup and drop off locations by extrapolating the collected samples to total demand. The working of demand responsive transport service for feeder buses is be based on geosimulation techniques using agent-based modelling software Matsim (Multi-Agent Transport Simulation) and its extensions and visualization software is Via Simunto to generate DRT scenarios of future complex traffic flows. The efficiency of DRT services is measured through the indicators that are- Vehicle productivity (km/day), Passengers carried per bus per day (number), Average travel time duration (minutes), Average waiting time, Average in vehicle time (minutes), Passenger usage i.e. Rides per vehicle revenue hour, Operating Cost and Passenger cost. Thus this study will be analytical and generate a simulation model for transport operators to select between existing fixed route bus services and flexible transport services for feeder buses. As a result of research it is observed significant reduction in passenger travel time and also reduction in operating cost of service when operated for mini buses.

Keyphrases: Demand Responsive Transport, Dynamic Vehicle Routing, Fixed route feeder bus, Simulation Modelling., operating cost, public transport

@booklet{EasyChair:3102,
  author    = {Sharmeela Kale and Premjeet Das Gupta},
  title     = {Planning for Demand Responsive Bus Service for Limited Area using Simulation},
  howpublished = {EasyChair Preprint 3102},
  year      = {EasyChair, 2020}}