Driving Safe Transportation Using Digital Solutions

This information was sourced from "Artificial Intelligence in Action: Selected ADB Initiatives in Asia and the Pacific," Asian Development Bank, 2024, https://www.adb.org/sites/default/files/publication/963831/artificial-intelligence-action-asia-pacific.pdf. Licensed under Creative Commons Attribution 3.0 IGO (CC BY 3.0 IGO).

Public transport was heavily affected by COVID-19 not only because of the lockdowns that were imposed by governments across Asia and the Pacific grounded vehicles, but also because more people used private transport to protect themselves from infection. However, not all can afford to buy vehicles.

Mass public transport remains a key driver of the economies in the region. Thus, it was important to find a way to help the public transport sector adjust to the new normal. To this end, ADB launched the “Driving Safe Transportation Using Digital Solutions” challenge in August 2020 to crowdsource a digital solution to help public transport operators and users stay safe while traveling. ASafeRide, which was pitched by a team from Arup, was selected out of the proposals from 30 teams that participated in the challenge.

ASafeRide was envisioned as a mobile application that uses crowdsourced data to provide passengers with real-time recommendations (e.g., what routes to take, which public transport vehicles are less crowded) to make their commute safer and faster. As such, it came with an e-wallet and payment option for cashless transactions. It was also envisioned to provide public transport operators with information to make vehicle deployment more efficient and responsive to demand. The app was intended to help resolve not only the issues brought about by the pandemic, but also the public transport problems that already existed even before COVID-19, such as unorganized fleets, unpredictable human and vehicle traffic, overcrowding in public transport vehicles, long queues, and arbitrary transportation fares.

The intent was to use AI, global positioning system (GPS), and big data to power the ASafeRide app. GPS could enable tracking the locations of passengers and public transport vehicles. The idea was to have data provided by public transport operators, along with publicly available information to be used by the app, to make route and vehicle recommendations to travelers. In addition, the data could be useful for contact tracing. The app also was meant to feature traffic calculation modules that could estimate travel times and lengths of queues.

ADB supported the development of the app’s prototype. The support allowed the Arup team to fine-tune their concept, including clearly defining the problem they wanted to address, who their target market was, and what alternatives were available in the market that were similar to their envisioned product. The team also further refined the technical and digital components and the business model of their proposed solution. In addition, they consulted with stakeholders from Davao City (e.g., local government and public and private groups in the health and transport sectors) to get their feedback on the prototype.

A beta version was then developed based on the results of these consultations and the data. The beta prototype was designed to perform live vehicle tracking of jeepneys, which are a type of public transport vehicle in the Philippines, and provide users with estimates of their time of arrival when taking public transport. It was also intended to generate live data on the passenger count per public transport vehicle and automatically reflect changes in public transport options, e.g., routes and fare prices.