Microsimulation of Demand-Responsive Transit in Low-Population Districts of Dubai Shows 33 Percent Fewer Rejected Trip Requests Compared to Fixed Transit.
Researchers Used Three-Month Real-World Pilot Deployment Data from a Demand Responsive Service in Dubai and Compared it with a Ride-Sharing Service Using Traffic Simulation.
Dubai
On-Demand Flexible Transit in Fast-Growing Cities: The Case of Dubai
Summary Information
Flexible transit options in fast-growing cities are considered promising strategies to reduce the use of private cars. This study evaluated a demand responsive transit service, which was tested In September 2016 for three months, in some low demand districts in Dubai, United Arab Emirates. An agent-based model calibrated with real world data was used to simulate the service under different scenarios, comparing the demand responsive transit service with a ride-sharing service with smaller vehicles. The purpose of the model was to determine optimal configurations that balanced the interests of both the transport operator and the community.
METHODOLOGY
A geographic information system (GIS) dataset was used to build the actual road network and implement a georeferenced real dataset of origin destination (OD) requests for the demand responsive transit service, collected during the first weeks of the service. It was assumed that each vehicle started traveling along the fixed-route until it stopped where waiting users were loaded on a first-come-first-served basis. If waiting users’ or on-board passengers’ destinations were known, a demand responsive transit vehicle could shift to an optional route at diversion nodes according to the Route Choice Strategy (RCS). Specifically, the following microsimulation scenarios were considered:
- Scenario 1: Test of route optimization and system efficiency based on RCS.
- Scenario 2: Comparison to other Demand Responsive Shared Transport (DRST) services.
- Scenario 3: Optimization of vehicle capacity based on demand fluctuation.
FINDINGS
- Scenario 1 results showed 33 percent fewer rejected trip requests compared to fixed transit.
- Scenario 2 findings implied about 52 percent less total user cost for the flexible transit service, compared to ride share service.
- Scenario 3 demonstrates that a heterogeneous fleet, utilizing high-capacity vehicles on weekdays and low-capacity vehicles on holidays, optimizes efficiency by aligning capacity with demand fluctuations.
