Carpool Connect: Bridging Commuters Through Web-Based Ride-Sharing Solutions

DOI

10.2991/978-94-6239-650-0_27How to use a DOI?

Keywords

Carpooling; Ride-sharing; Route Optimization; Machine Learning; Real-time Matching; Sustainable Transportation; Geolocation; Microservices Architecture

Abstract

As urban traffic congestion, pollution levels, and fuel costs have increased, sustainable transport solutions have become the need of the hour. This manuscript deliberates the in-depth conception, structural organization, and the progressive real-time implementation of an intelligent carpooling platform which allows record matching of rides of direction and schedules of drivers and passengers. In view of location-service, road-optimization, and machine-learning-based matching logic, the technology seeks to reduce the distance traveled to be able to fill the ride capacity to the maximum and thus ensure the overall efficiency of the system. This platform is also bolstered with a solid user authentication, a reputation-based trust mechanism, and an adaptive scheduling workflow that guarantees reliability and safety. Moreover, its architecture is modular and scalable and is hence supported by an interactive real-time ride management system through which users can post rides, search for rides, and manage ongoing trips without any hitch. In the same way, a metrics dash-board allows monitoring of the user activity, performance, and system estimations of traffic congestion and carbon emissions reductions. The outlined system thus, intends to solve paramount questions of urban mobility through the provision of a convenient, trustworthy, and environmentally conscious carpooling solution. The platform has been put to the test in different scenarios to check its usability, performance, and reliability and thus, it is highly probable that it can be further developed into mobile apps and connected with public transit networks.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Nikhil Maurya
AU  - Anurag Shetye
AU  - Chinmay Desai
AU  - Shravan Bishnoi
AU  - Shweta S. Ashtekar
PY  - 2026
DA  - 2026/04/20
TI  - Carpool Connect: Bridging Commuters Through Web-Based Ride-Sharing Solutions
BT  - Proceedings of the Conference on Technologies for Future Cities (CTFC 2025)
PB  - Atlantis Press
SP  - 383
EP  - 395
SN  - 3005-155X
UR  - https://doi.org/10.2991/978-94-6239-650-0_27
DO  - 10.2991/978-94-6239-650-0_27
ID  - Maurya2026
ER  -