Within the discourse of public transport and population growth, we have examined the implications of variants of accessibility on a wide variety of users. We aim to outline an adaptive service which extends to all members of the population equivalently, and which diminishes effort required in the use of the mobility chain. In doing so, we have integrated aspects such as the duration, cost, and physical length of the journey, as well as the different modes of transport and linkages between different modes. We have considered appropriate procedures for accessing resources, an account of the efforts required in reaching a specific destination, and the nature of the individual being transported.

Location and context-aware smartphone applications provide the potential for increased spontaneity and flexibility for public transport users. The Toronto-area population has outpaced Canada’s national growth rate for five years. Burgeoning population density will place and increasing burden on existing transportation systems, and impact employment based on accessible geography, resulting in increasing travel between municipalities and an increasingly dispersed employment geography within the city of Toronto and surrounding suburban employment areas. In coming years, navigating vehicle and foot-traffic congestion and providing constructive avoidance strategies in Toronto and surrounding employment areas will be imperative.

 Prioritizing the expenditures, schedules, and dignity of transport system users, we propose an app-based service which will provide accessibility for commuters by reducing traffic congestion. The system will do so by incorporating real-time data and live updates for passengers, transportation service representatives (vehicle operators) and transportation systems (dispatch), leveraging multi-modal services, and providing personalized route suggestions. Data collected from the system will also provide a milieu for strategic infrastructure and traffic system foresight for future improvement.

Our solution employs an aggregation of existing mobile-sourced data to facilitate planning for commuters and provides access to and awareness of optimal routes. Through personalized profiles and qualitative data, understanding the user and their activity records will enable feasible predictions about likely future scenarios. Interpretations of data will provide dispatch and administration foresight in improving future system infrastructure.  In order to provide features that are accessible to the greatest number of individuals, we have taken into account the Seven Universal Design Principles and Part III of the Accessibility for Ontarians with Disabilities Act (2005). By performing preliminary usability testing on a wide range of users and understanding user patterns and user goals through personalization measures, we would ensure the development of a widely accessible user interface.