RouteSense: A Dual-Interface Architecture for Advance Journey Planning and Economic Traffic Governance on Bengaluru Corridors

RouteSense is a research project presenting a dual-interface urban traffic intelligence and journey-planning platform for Bengaluru corridors. The system combines a Citizen Journey Planning Portal with a Traffic Authority Command Center through a shared FastAPI backend and SQLite database. The research discusses historical and live-condition journey planning, traffic forecasting, road-hazard reporting, incident management, priority scoring and economic impact estimation. The paper describes the system architecture, implementation methodology, functional testing and limitations. The reported evaluation includes 22 integration test cases. The forecasting model and economic estimates require further real-world validation. AI assistance was used in preparing the manuscript. The authors are responsible for verifying the technical content, references, results and conclusions.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-09
DOI
https://doi.org/10.5281/zenodo.24085865
Primary Topic
Transportation Planning and Optimization
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

RouteSense: A Dual-Interface Architecture for Advance Journey Planning and Economic Traffic Governance on Bengaluru Corridors

Kushwaha Anushka Ramnaryan
Zenodo (CERN European Organization for Nuclear Research)
Transportation Planning and Optimization
preprint

RouteSense: A Dual-Interface Architecture for Advance Journey Planning and Economic Traffic Governance on Bengaluru Corridors

Kushwaha Anushka Ramnaryan
preprint en

Abstract

RouteSense is a research project presenting a dual-interface urban traffic intelligence and journey-planning platform for Bengaluru corridors. The system combines a Citizen Journey Planning Portal with a Traffic Authority Command Center through a shared FastAPI backend and SQLite database. The research discusses historical and live-condition journey planning, traffic forecasting, road-hazard reporting, incident management, priority scoring and economic impact estimation. The paper describes the system architecture, implementation methodology, functional testing and limitations. The reported evaluation includes 22 integration test cases. The forecasting model and economic estimates require further real-world validation. AI assistance was used in preparing the manuscript. The authors are responsible for verifying the technical content, references, results and conclusions.

Zenodo (CERN European Organization for Nuclear Research)
Transportation Planning and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon