UrbanPulse: A Multi-tenant Intelligent Bike Routing System using OpenStreetMap, Live Traffic Data, and a Modified A* Routing Algorithm
Keywords:
A* algorithm, Intelligent transportation systems (ITS), Micro-mobility, Microservices, Multi-tenancy, OpenStreetMap (OSM), Real-time trafficAbstract
With rapid global urbanization and a critical shift toward sustainable micro-mobility, the urgency for intelligent, bike-centric navigation has reached a pivotal point. Traditional routing systems primarily focus on motor vehicles, often utilizing static graphs that prioritize the shortest distance while neglecting cyclist-specific variables like traffic congestion, air quality, and safety. This paper provides an extensive literature survey (2018–2025) exploring the evolution of routing algorithms, specifically the transition from monolithic to microservice-oriented Geographic Information Systems (GIS). The study analyzes “UrbanPulse,” a system designed to overcome the limitations of current static routing by leveraging a modified A* algorithm that integrates live traffic data. The significance of the proposed multi-tenant architecture lies in its ability to serve diverse user groups from individual commuters to delivery fleets within a single, scalable cloud-native framework while ensuring strict data isolation. By synthesizing recent advancements, this survey identifies critical research gaps in multi-tenant scalability and bike-specific traffic integration. The analysis demonstrates that the future of urban navigation depends on adaptive systems that prioritize the cyclist’s experience, providing a foundational blueprint for developing resilient, intelligent transportation solutions that respond dynamically to the pulse of the city.
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