Planning for demand responsive bus service as a feeder using simulation case study: Pune

Abstract

The aim of this research is to evaluate the potential benefits of Demand Responsive Transport (DRT) or Dial-a-Ride Transit (DART) or Flexible Transport Services (FTS) for bus over conventionally fixed route bus service in the Indian context. The need for such a study is raised on the problem statement that the existing fixed route bus services are capable of addressing only the static demand whereas demand for public transport is always dynamic in nature and depends on user behaviour and choice whether to use service or not within a specific time window at a specific location. Thus providing fixed service on static routes will not solve the problem of capturing user’s dynamic demand. Existing public transport bus services provided has many problems such as longer commuting time due to fixed route, low ridership in non-peak hours, low frequency in high demand, congested buses during peak-hours, longer waiting time, non-availability of a seat, poor customer experience, lack of the use of technology. This study is an attempt to minimize shortcomings in the existing fixed route of bus services in the Indian context and overcome the challenge of demand responsive transport practiced worldwide by studying various similar projects of flexible transport services. With the advancement in shared mobility in the form of cabs from private sector and its huge acceptance from the public in India, it is a way forward to take such a study on shared mobility for the mass urban transport system. Demand responsive transport is innovative large scale technology based user focused form of public transport preferred as shared ride service renowned due to its flexibility in routes and schedule based on user’s preference at convenient pick up and drop off points. Demand responsive transport is On-demand Bus model characterized by fixed routes with flexible timings, seat reservation, convenient boarding points, real-time tracking, and smartphone application. A study area is Pune city in Maharashtra State where Metro rail has been proposed and delineated area is catchment area of last Metro station Ramwadi in northeastern part of city which is selected on basis of nature of successes and failures of existing similar DRT practices. This study will develop 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. Sampling technique used is systematic clustering to get the distribution of demand. The working of demand responsive transport service for feeder buses will be based on geosimulation techniques using agent-based modelling software Matsim (MultiAgent Transport Simulation) and its extensions like DVRP (Dynamic Vehicle Routing Problem) to generate DRT scenarios of future complex traffic flows based on few assumptions and visualization software is Via Simunto used to observe how the simulation is progressing. The simulation building is for one day for the same time window for which existing public bus service run. The scenarios building will be based on and permutation and combination of various assumptions i.e. fleet size of vehicles, capacity of vehicle (16 seater), time window setting (vehicle stopping time and waiting time or pick up the passenger), locations of convenient pick up and drop off locations, zoning effect (decentralization of area to form microcatchments and assigning vehicles to this micro zones) for real network. The main challenge in the study will be the assumption of appropriate fleet size which is on trial and error method and estimating future demand for existing fixed route service. Work will proceed with estimating total future feeder demand based on Assumptions i) future demand for DRT service will be the same as demand for fixed route public bus service ii) total number of passengers willing to shift to DRT service, followed by apportioning total estimated demand into micro-catchments at convenient stopping points based on road width and landuse then running simulation for all possible scenario based on assumptions and identifying efficient service based on the comparison of resultant simulations. To measure the efficiency of DRT services the indicators used for Service provider are - Fleet utilisation, Vehicle capacity, Vehicle productivity (km/day), Passengers carried per bus per day (number), Operating Cost (Rs), and Passenger Earnings (Rs); for Commuter are - Average travel time duration (minutes), Average waiting time, Average in vehicle time (minutes), Average journey time, Average per person distance travelled, Passenger travel 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.