Despite the emergence of many new mobility options in cities around the world, fixed-route public transit remains the most efficient form of mass transportation. Bus operations are subject to vicious and virtuous circles. The proof can be seen in New York.
Since 2007, travel speed reductions and increased congestion due to more mobility options competing for road space have resulted in a vicious cycle of reduced ridership and increasing congestion as former transit riders switch to less efficient modes of transportation. In Brooklyn, bus ridership fell 21% during this period. Although the decline in ridership has been steady throughout this period, there are growing concerns that it will only get worse as car rental services like Uber and Lyft add more rides to the road network.
Intervention in the form of an overhaul of the network is necessary to promote a virtuous circle and make the bus more competitive, particularly in the face of increased competition from ride-hailing services. This can be done by redesigning the bus network in a way that reduces operating and usage costs while increasing accessibility for more passengers.
Now, new research from Joseph Chow, professor of computer science and engineering at NYU Tandon School of Engineering and member of the C2SMART Tier 1 University Transportation Center at NYU Tandon; and PhD student Ziyi Ma propose a simulation-based transit network design model for bus frequency planning in large-scale transit networks with activity-based behavioral responses. The model is applied to evaluate Brooklyn’s existing bus network, other network redesign projects, and used to develop an alternative design based on the researcher’s methodology.
The MATSim-NYC model designed by Chow and Ma is able to simulate models similar to the existing bus network in Brooklyn with some calibration. This model was used to confirm a plan by another group to increase ridership, but was also able to refine it even further. The increase in ridership comes mainly from the use of private cars (nearly 75%), with a small 2.5% coming from public transport services and an additional 5% from taxis. This suggests that the redesigns should be effective in moving people away from less efficient modes of transport.
The researchers are now looking to refine their model so that it becomes a key tool for policy makers planning the future of transportation in the city.
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Quote: Transit Network Design Model for Bus Frequency Planning (2021, November 24) Retrieved January 15, 2022 from https://techxplore.com/news/2021-11-transit-network-bus-frequency .html
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