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Record W7110794648 · doi:10.13189/cea.2025.130638

Enhancing Wayfinding in Chennai Metro: Insights from Passenger Feedback

2025· article· en· W7110794648 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCivil Engineering and Architecture · 2025
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsnot available
Fundersnot available
KeywordsSignagePublic transportUsabilityDigital signageUniversal designPoint (geometry)Digital mappingBorder crossingUrbanization

Abstract

fetched live from OpenAlex

Metro systems are now essential for urban mobility due to the rapid urbanization of the world, but many users still find it difficult to navigate these complex environments. Clear and inclusive wayfinding is not only critical for improving passenger ease of commuting. It is also for certifying security, effectiveness, and reasonable access to public transport. In Chennai, like in other cities where the transit usage has increased rapidly in recent years, user-centered navigation design remains unknown. In order to categorise design limitations and recommend user-centered improvements, this study examines passenger feedback to investigate the wayfinding experience in Chennai Metro stations. The research builds on international frameworks such as Metrolinx (Canada), APTA (USA), and MTC (USA), while positioning results within the local socio-cultural context. Using a mixed-methods approach, the study evaluates overall navigation satisfaction through integrating quantitative survey data with qualitative responses from 88 respondents. The investigation apprehended demographic variations across age, gender, and travel frequency. The open-ended responses delivered understandings into signage clarity, digital tools, and accessibility. The results show serious deficiencies in real-time navigation assistance, digital integration, multilingual signage, and accessibility for people with disabilities. Starting from the mobile apps, interactive kiosks, restroom signage, and multilingual guidance, the need varies by age and gender. These results point to demographic-exact needs that should inform design revisions. The study highlights the need for inclusive design principles by comparing Chennai Metro's current practices to international standards like Metrolinx (Canada), APTA (USA), and MTC (USA). The use of universally recognizable symbols, enhanced station mapping, tactile and Braille signage, and participatory design—which involves passengers in the evaluation of signage—are among the recommendations. By providing scalable methods for improving wayfinding in expanding metropolitan networks, the study adds to the broader conversation on transit accessibility and user experience.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.181
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it