🧭 Overview Indian Traffic VQA is a real-world Visual Question Answering (VQA) dataset focusing on Indian road traffic signboards. The dataset is designed for training and evaluating Vision-Language Models (VLMs) and VQA systems in the traffic and transportation domain. This dataset bridges a gap between real-world Indian traffic conditions and machine understanding — ideal for research in autonomous driving, smart city AI, and traffic sign recognition under natural environments.

📦 Dataset Summary • Images: 1,085 real-world traffic signboard images • Questions: 4,341 unique questions • Answers: Short, ground-truth textual responses • Source: All images were collected using a mobile phone in real Indian road environments • Format: .csv file with the following columns: o image_name — name of the image file o question — text-based query o answer — corresponding ground-truth answer

🧠 Task Definition Given an image of a traffic signboard and a related question, the model must predict a short text answer. Example: image_name question answer imag_00001.jpg What does this sign indicate? Speed Limit img_00002.jpg What does this sign show? Stop img_00003.jpg Is U-turn allowed here? No

🧩 Applications • Visual Question Answering (VQA) • Vision-Language Model (VLM) Fine-tuning • Multimodal classification of traffic signs • Dataset for benchmarking model reasoning in domain-specific visual data

🧰 Data Collection Details • Captured in diverse Indian traffic conditions (urban, rural, highways) • Includes varying lighting, occlusions, and view angles • All images are real photographs, not synthetic

⚖️ License You may distribute, modify, or use this dataset for non-commercial research purposes. Please give appropriate credit by citing this dataset.

The .zip file contains all the 1085 images with 512x512 resolution. There are two .csv files attached. traffic_vqa_1085.csv contains one question and one answer, traffic_vqa_4341.csv contains multiple questions and answers per image. The first .csv file can be used for low resource computational environment.

🚀 Future Work Future releases will include: • Regional signboard subsets (state-specific) • Video-based question answering • Multilingual question support (English + Hindi)

👥 Contributors 🧠 Data Curators 🧩 Chandra Mohan Bhuma 🧩 CH.V.M.S.N. Pavan Kumar 🧩 T. Krishna Chaitanya 🧩 Miriyala Suneel

📷 Data Collectors 📸 Perumalla Himasri 📸 Vallapuneni Venkata Siva Kumar 📸 Ratna Seethal Saripalli 📸 Somanapalli Hindu

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