MicroTransit on Blockchain

Innovation Tagline:  

Reimagine contract management for micro transit that is lean, scalable and environment friendly

Project Keywords:  #microtransit #toronto 

Project Members

1. Name: Vaibhav Sharma

   Email: vbdevgan@gmail.com

   Linked in: https://www.linkedin.com/in/vaibhav-sharma-2ab46621/

   Project Keywords: #microtransit #blockchain #hypderledger #hyperledgerfabric #Ttc #torontotransit

   
   

   
   

   2. Name: Sarfraz Hooda

   Email: sarfrazhooda@gmail.com

   Linked in: https://www.linkedin.com/in/sarfrazhooda/

Project Description (no more than 1,000 words including graphics)

COVID-19 has produced the worst economic downturn since the Great Depression.

Like any other big city, the City of Toronto's transit system has not been able to escape the effects of COVID-19. The revenue has plummeted and has given a challenge to the staff to look for efficient ways to run the transit system. Just a mere glance over the pre and post covid numbers give a clear picture of the dramatic drop in the ridership.

With being the most heavily used transit system in Canada and the third largest in North America, at times ridership went as low as 15 per cent, but the service levels were kept at about 90 per cent.

With the continued service and the significant drop in ridership, there has been enormous financial stress put on the TTC. During the pandemic, the TTC has been experiencing an average loss of revenue of $90 million per month and 1200 temporary layoffs.

Adding to the challenges, the COVID-19 crisis has decimated ridership, funding sources have evaporated, and the recovery is progressing slowly. Against this backdrop, the need for public transportation agencies to evolve and innovate on their service delivery model has never been higher.

Operating Models in Transit

The current ‘Owned and Employee Run’ model for TTC has more than 2000 buses, owned and operated by the transit agency. With over 2000 buses having financial commitment of 12 to 15 years, the major risks are revenue and cost. Ownership of such a large fleet, comes with service infrastructure of its own including garages, skilled labour for repairs and huge inventory of parts. With this large infrastructure, it is also difficult to adapt to the changing pace as the ability to scale up or down could take years.

Alternative models which can be looked are following: 

Outsourced Model : An outsourced model such as in London, which is run largely by contracted services to various private sector vehicle (ex. bus) operators. All bus operations are undertaken under a tendering system in which operators bid for routes in return for a set price per route operated. Contracts are normally for five years, with two-year extensions available if performance criteria are met. With this model, transit agency takes on the risk of revenue however cost of maintaining the service is fixed, as agency doesn’t own any bus infrastructure. There is no flexibility to scale down the operation as per commitment to tendering agreements. It is also time consuming and costly to go through tendering process every 5-7 years and high compliance cost to manage the vendors. 

Leased and Employee run: In this model, which is suitable for a smaller sub-urban cities, the vehicles are leased by the agency and are employees operated. The financial commitment for the lease cycle can be 5-7 years. The risks for revenue and cost are handled by the transit agency.

In this model agency doesn’t keep huge bus maintenance infrastructure as majority of repairs are covered under lease/warranty agreements. There is not much financial commitment upfront however in long term, it costs more compared to bus ownership model. In terms of scalability, this model provides no flexibility.

When it comes to moving a large number of people along dense corridors, there is no more efficient alternative than the high-density trunk lines such as subways, streetcars and buses. 

For the vast majority of trips in high and medium density areas, conventional public transportation is very efficient at moving high number of riders from point A to B, at a low cost. However, in low density areas when the demand drops during off-peak hours, conventional modes often face very high costs per trip as agencies are mandated to maintain minimum service levels. At the same time, there are low-density areas where the travel patterns do not allow public transit agencies to run efficiently resulting in such routes with less than half of capacity required to be efficient. 

Our Proposal : 

In order to get around this challenge, just like many cities, Toronto should also look into the possibility of a Ride-Sharing Microtransit system. 

Microtransit is a form of Demand Responsive Transit and it fits somewhere between private individual transportation and public mass transit. With Microtransit, comes an ability to expand the range of vehicles with different capacities, accessibility options and cost structure which allow the transit agencies to match the right vehicle with the right passenger at the right time. 

Ride-sharing Micro transit enables transit agencies to reallocate resources from inefficient and low density routes, to high demand areas in the network. Adding the ride sharing micro-transit approach to the current fixed route system has great potential to lower operating costs as well as provide access to the areas which were previously inaccessible. It can also build resilience to the existing public transit and make it most robust in case of demand fluctuations. 

Microtransit typically operates on a small scale within a geofenced area. The fleet size is often fixed, typically with around 10-15 vehicles (but this can be higher or lower). 

Traditionally, transit agencies around the world has been dealing with first and last mile challenges where the distance a commuter needs to travel from transit stop to their destination is more than a mile. With ride sharing services connecting commuters from their homes or destination to a transit hub would solve this problem.

Problem

Different Operating Models have significantly different cost. According to our research and interviews conducted we have identified that the transit ‘owned and employee run’ operations are the most expensive. If operations are outsourced cost can be reduced by up to 40%. We believe further cost savings of up to 30%, can be achieved by eliminating the third party vendor and using the ride share model.

Here are the details:

Employee Run Model

In an employee based model, transit agency would spend significant amount on the infrastructure such as owning the vehicles and supporting/maintenance infrastructure. Employee run agencies are responsible to manage the following, which put a huge impact on the agencies financials:

• Capital Investments
• Fare Management and Collection
• Planning and forecasting
• Employee Salary and Benefits
• Vehicle Operations (Dispatching, scheduling, Driver compliance)
• Vehicle maintenance
• Customer Management 
• Drivers Recruitment and Training

Outsourced Model

In an outsourced model, where operations are outsourced, the cost is distributed between vendor and agency to perform various tasks:

Solution

Ride Sharing Microtransit Model 

Ride-sharing based Microtransit requires significant amount of vendor management and compliance. Following are some of the processes that transit needs to take on when managing Ride-sharing based contracts:

• Driver’s qualification (License Verification)
• Driver’s background checks
• Driver’s vulnerability checks
• Trip based recording of data
• Payment management
• Trip issue/complaint management
• Issuing refunds
• Schedule management
• Real time logging of GPS coordinates
• Trip modifications
• Dispatch Management

Ride-Share Model

In the Ride-Share model, vendor cost can be completely eliminated by leveraging the blockchain technology which would result in up to 30% of savings

Minimum Viable product

Minimum viable product would include two core processes that would implement smart contracts for driver qualification and trip booking. We can capitalize on Saas based services for trip optimization and scheduling, while block chain will purely manage the contract and compliance.

Drivers can be added to the transit network through smart contracts having pre-defined conditions. As soon as the driver meets the conditions of having a valid driver’s license and passing the background and vulnerability check, smart contract between the transit agency and the driver will activate, allowing drivers to pick the commuters in a pre set geo fenced area. 

Commuters on the other hand will be requesting for a driver, the moment they request for a driver, a third party route optimization engine will be handling the requests based on the GPS coordinate of the request origin and the nearest available driver. Once driver accepts the trip, a smart contract will be registered. Various data key points such as GPS coordinates, Passenger pickups and drop-offs, customer feedback etc. can be registered as part of the contract. Finally, the contract can be closed once the payment has been disbursed based on the distance travelled during the trips and the pre set rate. 

Accomplishment and Team

Both, Sarfraz and Vaibhav are currently working in the public transit sector for over a decade and have strong knowledge of transit based processes and business models. Given that both of us have degrees in computers, we both have expertise in building front end applications and database management.

We would require infrastructure, training and support in building prototype for ride sharing smart contracts on block chain with Hyperledger fabric. 

Project Plan

Goals for Prototype

Prototype Phase

• Driver qualification process to be implemented with smart contract with transit agency, where documents can be uploaded and verified. This will allow ride sharing driver to have access to trips assignment.
• Trip Booking that initiates a smart contract and ability to log trip related information against the contract such as customer pick ups and drops.

Launch Phase

• Customer qualification process to be implemented with smart contract with the transit agency, where customer will have to qualify based on the pilot project’s location and co-ordinates.
• Customer pick up routes will be optimized through 3rd party tool.
• Pitch the idea to transit agency who is willing to take on the business idea.

One year goal

• Identify low density areas closer to transit hubs to apply the model.
• Payment management features to be introduced via smart contract.
• Extend the smart contracts to para-transit.

Project Plan

Risks

• Limited expertise in Hypderledger development.
• Unavailability of full time resources that would be required to complete the project.

Mitigation

• Collaborating with linux academy for support on educational and mentoring resources.
• Partner with experts/companies (dominant in transit based solutions) to add resources that could facilitate pilot and launch phases.

References:

https://www.toronto.ca/wp-content/uploads/2020/09/9133-torr-covid19-impacts-opportunities-2020.pdf

www.ttc.ca