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Appetite for on-demand transit technology has grown exponentially in recent years. Observing the potential benefits of a mixed fixed-route and on-demand system, the well-respected and innovative team at the Société de transport de Laval (STL) engaged Blaise. After several collaborative and exciting planning sessions, the STL commissioned a feasibility study from us to understand how to reduce costs on fixed bus lines with low ridership.
Blaise’s expertise provided valuable insight into the potential for on-demand transit in Laval and has paved the way for an on-demand pilot project in the fast-growing city.
The STL operates within Laval, Quebec, a growing city just north of Montreal. However, at 1,710 residents per square km, Laval’s population density – a key determinant of transit network design – is roughly one third of Montreal’s, at 4,662. Observing the combined challenges of serving an area of low-population density in a cost-effective way and attracting riders to multiple industrial regions, the STL engaged Blaise to perform an analysis and simulation project.
The goal: identify fixed bus lines that would be cost-effective to replace or complement with an on-demand service, using the STL’s existing fleet capacity, resources, and equipment, while maintaining existing bus stops and respecting existing riders.
On-demand public transit is exciting, but it is also novel. Consequently, two key challenges emerged.
The first was data availability. The available origin and destination data came from the STL’s OPUS smart card and their passenger counter. Combined, they provide a data set that offers both origins and destinations for passengers using the existing services. However, since users only tap onto the bus with their OPUS card, the destinations are an only estimate using the STL’s passenger counter data. This means that in certain cases, the destinations simply can’t be estimated. But because we needed to know the origins and destinations to simulate an on-demand service, we ran with the data we had and had to be innovative in our approach.
Second was the problem of designing a simulation that could credibly include demographics currently not using transit. Though smart card systems generate lots of data, it provides no details on non-transit users. Surely, there are drivers, cyclists, pedestrians, and even metro users who would convert to an on-demand system, especially if it took them from areas with infrequent fixed-line coverage to work or commercial hubs.
Before running simulations, Blaise selected several key criteria enabling the identification of ideal fixed bus lines to replace with an on-demand service. Our criteria included two core indicators: (1) number of bus stops used on a specific bus line and (2) how much their usage varies throughout the week. For example, a bus line could have between 45 and 55% stop usage between Monday and Sunday and have low variability. Another, however, could have 8% usage on Monday, but 81% stop usage on Tuesday, meaning it had high variability. Other key indicators, like population density, were also considered. After considerable research (and math), Blaise identified 3 corridors in Laval where on-demand could reduce costs while servicing the same number of passengers. And then we ran our simulation, observing the exciting effects of replacing fixed-bus lines.
Our findings were even more promising than we had anticipated. We demonstrated that, in the 3 corridors, which make up 10% of total weekly transit trips within Laval, a completely on-demand service could reduce trip duration by an average of 11% for passengers. What’s more, 99% of trips would still be served, and farebox recovery would increase by 34%. With this said, our encouraging findings remain the results of Blaise’s internal simulations and calculations and should be validated over the course of a pilot project with the STL.
All towns, suburbs, and cities contend with different public transit challenges. With generous support from the Société de transport de Laval, our case study demonstrated the promising cost-savings of on-demand transit. Additionally, because Blaise’s platform is universal, it can be adapted for a variety of on-demand models that work with any size of fleet or landmass. In the end, it’s a win-win for strategic transit organizations looking to not only reduce costs but increase ridership and service coverage.
