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# app.py
# TripAI – Intelligent Four-Step Travel Demand Modelling
# Main Entry Point for the Multi-Page Streamlit Application
import streamlit as st
st.set_page_config(
page_title="TripAI – Intelligent Four-Step Travel Demand Model",
page_icon="🚦",
layout="wide"
)
# ==========================================================
# HEADER
# ==========================================================
st.title("🚦 TripAI")
st.markdown("### Intelligent Four-Step Travel Demand Modelling with AI, XAI, and Optimization")
st.markdown(
"""
TripAI is a **research-oriented platform** implementing a complete, synthetic
**four-step travel demand model**, augmented with:
- Classical **Trip Generation → Trip Distribution → Mode Choice → Route Assignment**
- **User Equilibrium (UE)** using Frank–Wolfe
- **Machine Learning** (Regression + Classification)
- **Explainable AI** (SHAP) for behavioural insights
- **AI Link Flow Emulator** for fast demand scaling
- **Policy Scenario Engine** with congestion charge, TOD, MRT improvements
- **Scenario Optimization** over policy parameters
Use the **left sidebar** to navigate between phases of the workflow.
"""
)
# ==========================================================
# SESSION STATUS PANEL
# ==========================================================
st.markdown("---")
st.subheader("📊 Current Session Status")
col1, col2, col3 = st.columns(3)
# ----- Column 1 -----
with col1:
st.markdown("**1. Synthetic City**")
if "city" in st.session_state:
taz = st.session_state["city"].taz
st.success(f"Generated ({len(taz)} TAZs)")
st.caption("Go to: `📊 Generate Synthetic City`")
else:
st.info("Not generated")
st.markdown("**2. Trip Generation**")
if "productions" in st.session_state and "attractions" in st.session_state:
st.success("Done")
st.caption("Go to: `🚶 Trip Generation`")
else:
st.info("Not run")
# ----- Column 2 -----
with col2:
st.markdown("**3. Trip Distribution**")
if "od" in st.session_state:
st.success("OD matrices available")
st.caption("Go to: `🌍 Trip Distribution`")
else:
st.info("Not run")
st.markdown("**4. Mode Choice**")
if "mode_choice" in st.session_state:
st.success("Mode choice available")
st.caption("Go to: `🚈 Mode Choice`")
else:
st.info("Not run")
# ----- Column 3 -----
with col3:
st.markdown("**5. Route Assignment**")
if "link_flows" in st.session_state:
st.success("Assignment complete")
st.caption("Go to: `🛣️ Route Assignment`")
else:
st.info("Not run")
st.markdown("**6. AI / Scenario / Visualization**")
status = []
if "ai_tripgen_model" in st.session_state:
status.append("AI TripGen")
if "ai_modechoice_model" in st.session_state:
status.append("AI ModeChoice")
if "link_flow_emulator" in st.session_state:
status.append("AI Emulator")
if "opt_results" in st.session_state:
status.append("Optimization")
if status:
st.success(" / ".join(status))
st.caption("See: `🤖 AI`, `🧠 Emulator`, `🎯 Optimization`, `📈 Visualization`")
else:
st.info("No AI/Scenario modules executed")
# ==========================================================
# WORKFLOW EXPLANATION
# ==========================================================
st.markdown("---")
st.subheader("🧭 Recommended Workflow")
st.markdown(
"""
1. **📊 Generate Synthetic City**
Build a 20-zone synthetic metro with socio-economic + land-use attributes.
2. **🚶 Trip Generation**
Compute productions & attractions for HBW, HBE, HBS.
3. **🌍 Trip Distribution**
Doubly-constrained gravity model with IPF.
4. **🚈 Mode Choice**
Multinomial Logit (Car / Metro / Bus).
5. **🛣️ Route Assignment**
AON or User Equilibrium (Frank–Wolfe).
6. **🤖 AI-Enhanced Models**
ML Regression + Classification + SHAP explanations.
7. **⚙️ Policy Scenario Engine**
Metro improvements, congestion charge, fare changes, TOD.
8. **🧠 AI Link Flow Emulator**
Predict link flows without running UE.
9. **🎯 Scenario Optimization**
Search policy space to minimize congestion or car use.
10. **📈 Visualization & 📦 Export**
Create research-grade figures & download complete datasets.
"""
)
st.markdown("---")
st.caption("TripAI – Developed by Mahbub Hassan, B’Deshi Emerging Research Lab.")
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