route-optimization

name	route-optimization
description	Deploy the Route Optimization demo including Marketplace data and notebook. Use when: setting up the route optimization demo after ORS app deployment. Do NOT use for: fleet intelligence demos (use fleet-intelligence-car), route deviation analysis (use route-deviation), or retail catchment analysis. Triggers: deploy route optimization demo, setup route optimization demo, run route optimization demo.
depends_on	["install-fleet-apps"]
metadata	{"author":"Snowflake SIT-IS","version":"1.0.0","category":"route-optimization"}

Deploy Route Optimization Demo

Deploys the complete Route Optimization demo including Snowflake Marketplace data and the exploration notebook. The interactive VRP simulator is served via the shared React Demo Dashboard app.

Prerequisites

• OpenRouteService Native App deployed and activated
• Active Snowflake connection with a role that has privileges listed in the Required Privileges section below
• For preset-driven demos, run Data Studio for the target (region, vehicle_type) first. The Route Optimization page now reads FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.V_PLACES_CURRENT and the active dataset's UNIFIED V_*_CURRENT views.

Required Privileges

Privilege	Scope	Reason
CREATE DATABASE	Account	Creates FLEET_INTELLIGENCE database
CREATE WAREHOUSE	Account	Creates ROUTING_ANALYTICS warehouse
IMPORT SHARE	Account	Acquires OVERTURE_MAPS__PLACES from Marketplace
USAGE ON DATABASE FLEET_INTELLIGENCE	Database	Uses the setup database
CREATE SCHEMA	Database (FLEET_INTELLIGENCE)	Creates ROUTE_OPTIMIZATION schema
CREATE TABLE	Schema (FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION)	Creates CONFIG, PLACES, LOOKUP, JOB_TEMPLATE
USAGE ON DATABASE OVERTURE_MAPS__PLACES	Database	Reads Marketplace POI data
USAGE ON DATABASE OPENROUTESERVICE_APP	Database	Calls ORS routing functions
EXECUTE MANAGED TASK	Account	Enables ALTER ACCOUNT SET CORTEX_ENABLED_CROSS_REGION (optional)

Note: ACCOUNTADMIN is NOT required. Create a custom role with the above privileges, or use any role that has them.

All snow stage copy commands use --connection <ACTIVE_CONNECTION>. Replace <ACTIVE_CONNECTION> with the name of your currently active Snowflake connection.

Optional Dependencies

Skill	Used By	Behavior if missing
dwell-analysis	Asset Velocity page	Page renders a friendly empty state pointing the user to deploy dwell-analysis. The core Route Optimizer (VRP) keeps working.

Asset Velocity (Non-Moving Vehicle Detection & Action Engine)

This skill ships a second React page in the control app, Asset Velocity, that materialises an industry-standard ghost-trailer detection workflow. It is fully additive - the existing Route Optimizer (VRP) page is untouched.

It reuses the dwell-analysis Dynamic Tables (no new DTs) and adds four thin views in FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION:

View	Purpose
VW_IDLE_VEHICLES	Latest dwell session per HGV, with idle duration metrics, deterministic dispatcher mapping, and an exception filter that drops MAINTENANCE statuses and OUTLIER driver profiles.
VW_LANE_DEMAND	Net outbound trips per terminal over the most recent 30 days of FACT_TRIPS. High DEMAND_SCORE = trailer-short terminal.
VW_FLEET_VEHICLE_PROFILE	(v1.1) Resilient HGV-attribute view (subtype, weight, height, length, axleload, hazmat). Coalesces against deterministic defaults so the page works even after Data Studio regenerates DIM_FLEET.
VW_VEHICLE_COST_OF_IDLENESS	Joins VW_IDLE_VEHICLES with CONFIG.DAILY_RENTAL_RATE_AVOIDED_USD and CONFIG.RENTAL_CAPTURE_RATE to compute cost-of-idleness, projected savings, and severity bucket. (v1.1) Also exposes per-vehicle profile attrs and CONFIG.MAX_REPOSITION_MINUTES / CONFIG.AVOID_FEATURES so the React page can build vehicle-specific ORS profile_params.

Full use case framing, cross-vertical applicability, and risk mitigations live in references/asset-velocity-use-case.md.

Smart-reposition (v1.1)

The Asset Velocity page now uses real ORS + VROOM features instead of Euclidean math:

Feature	Underlying call	Effect
Road-network shortlist	OPENROUTESERVICE_APP.CORE.MATRIX('driving-hgv', options, region) with profile_params.restrictions envelope	Replaces Math.hypot(dLng, dLat) with HGV-aware road duration.
Reachability gate	Matrix durations[r][c] vs CONFIG.MAX_REPOSITION_MINUTES	Terminals outside the shift are excluded with reason OUT_OF_SHIFT.
Reachability polygon	OPENROUTESERVICE_APP.CORE.ISOCHRONES('driving-hgv', lng, lat, range, region)	Selected trailer's polygon overlays the deck.gl map.
Multi-constraint VROOM	OPENROUTESERVICE_APP.CORE.OPTIMIZATION(challenge, region) with time_windows, skills, multi-dim capacity, service, breaks, costs.fixed, max_travel_time	Real bipartite assignment under driver shift, EU 561/2006 break, and trailer-subtype skill matching.
HGV restrictions	options.profile_params.restrictions (weight/height/length/width/axleload/hazmat) + options.avoid_features	Routes avoid weight-restricted bridges, low overpasses, hazmat-banned roads, and (configurable) tollways/ferries.

Known limitations (synthetic data):

• The wrapped ISOCHRONES(...) UDF does not yet pass profile_params through, so the polygon is profile-only (the matrix gate is the authoritative filter).
• DIM_POIS has no OPEN_FROM/OPEN_TO, so terminal time windows default to 06:00-22:00 UTC.
• LANE_PROFILE does not exist on terminals; skill-mismatch heuristics treat RESTAURANT POIs as REEFER-required and everything else as DRY-friendly.

Deploy the Asset Velocity views

This is a REQUIRED step of the standard workflow (see Step 5b below), not an optional aside. Without it the Asset Velocity page in the control-app sidebar renders empty. It is preset-agnostic: VW_IDLE_VEHICLES pulls VEHICLE_TYPE from ROUTE_OPTIMIZATION.CONFIG, so on the default SanFrancisco/ebike install it surfaces idle ebikes (no HGV data required).

Prerequisites: dwell-analysis skill deployed (the views reference FLEET_INTELLIGENCE.DWELL_ANALYSIS.DT_DWELL_ENRICHED, which Snowflake validates at CREATE VIEW time).

snow sql -f .cortex/skills/route-optimization/references/extend-dim-fleet-hgv.sql -c <connection>
snow sql -f .cortex/skills/route-optimization/references/asset-velocity-views.sql -c <connection>

Verify:

SELECT 'VW_IDLE_VEHICLES' AS V, COUNT(*) AS CNT FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_IDLE_VEHICLES
UNION ALL
SELECT 'VW_LANE_DEMAND',         COUNT(*) FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_LANE_DEMAND
UNION ALL
SELECT 'VW_VEHICLE_COST_OF_IDLENESS', COUNT(*) FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_VEHICLE_COST_OF_IDLENESS;

The page will gracefully render an empty state with deployment instructions if DWELL_ANALYSIS.DT_DWELL_ENRICHED is missing.

Configuration

Parameter	Default	Description
DATABASE	FLEET_INTELLIGENCE	Database for demo objects
SCHEMA	ROUTE_OPTIMIZATION	Schema for VRP tables and notebooks
WAREHOUSE	ROUTING_ANALYTICS	Warehouse for queries
MARKETPLACE_CARTO	CARTO Academy	CARTO Academy Marketplace listing name
CONFIG.DAILY_RENTAL_RATE_AVOIDED_USD	80.00	Daily $ saved per trailer hour returned to the network.
CONFIG.RENTAL_CAPTURE_RATE	0.600	Fraction of theoretical idle-cost the operator believes they can capture (60%).
CONFIG.MAX_REPOSITION_MINUTES	600	Driver shift cap (minutes). Drives the matrix reachability gate, the isochrone range, and VROOM time_window / max_travel_time.
CONFIG.AVOID_FEATURES	tollways,ferries	Comma-separated ORS avoid_features list (passed via Matrix options).

Error Logging

Follow the Error Logging convention in AGENTS.md. Log file prefix: route-optimization.

Execution Rules

1. Never use bulk sed or replace_all on .ipynb files - notebooks are JSON with structured cell arrays. Use targeted replacements on specific cells identified by name.
2. Replace longer phrases before shorter ones when editing notebook prompts to avoid garbled text.
3. Replace complete prompt strings, not individual words.
4. Always validate JSON validity of modified .ipynb files before uploading.

Workflow

Step 1: Set Query Tag

Pre-check: If data already exists, skip to Step 6. Run:

SELECT COUNT(*) AS cnt FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.PLACES;

If cnt > 0, the data pipeline has already run. Skip to Step 6 (Claude model check) or Step 7 (AISQL notebook) as needed.

Goal: Set session query tag for attribution tracking.

Execute:

ALTER SESSION SET query_tag = '{"origin":"sf_sit-is-fleet","name":"oss-route-optimization","version":{"major":1, "minor":0},"attributes":{"is_quickstart":1, "source":"sql"}}';

Step 2: Verify ORS Services

Goal: Confirm all 4 ORS services are active (OPENROUTESERVICE, ROUTING_REVERSE_PROXY, VROOM, DOWNLOADER).

Execute:

SHOW SERVICES IN DATABASE OPENROUTESERVICE_APP;

If any services are SUSPENDED, resume them:

CALL OPENROUTESERVICE_APP.CORE.RESUME_ALL_SERVICES();
SELECT OPENROUTESERVICE_APP.CORE.CHECK_HEALTH();

STOP if ORS Native App is not installed.

Step 3: Read ORS Configuration and Gather Preferences

Goal: Detect current map region and routing profiles, gather customization preferences from the user.

1. Read and follow .cortex/skills/routing-customization/read-ors-configuration/SKILL.md
2. Determine the demo city:
   • City map (e.g., "SanFrancisco"): use that city name
   • Region/country map (e.g., "great-britain"): ask user which city
3. Ask: "Do you want to customize industries? Default industries are: Food, Healthcare, Cosmetics."
   • If YES: gather specs per references/industry-customization.md
   • If NO: use defaults
4. Store for later steps: <REGION_NAME>, <NOTEBOOK_CITY>, <ENABLED_PROFILES>, <CUSTOM_INDUSTRIES>

Output: Map Region, Demo City, Vehicle Profiles, Custom Industries (YES/NO) confirmed with user.

Step 4: Get Carto Overture Dataset

Goal: Acquire Overture Maps Places dataset for POI data.

Execute:

CALL SYSTEM$ACCEPT_LEGAL_TERMS('DATA_EXCHANGE_LISTING', 'GZT0Z4CM1E9KR');
CREATE DATABASE IF NOT EXISTS OVERTURE_MAPS__PLACES FROM LISTING GZT0Z4CM1E9KR;

Requires IMPORT SHARE privilege. If profile error occurs, update user profile with first/last name and email. Full details in references/sql-setup.md Step 4.

Output: OVERTURE_MAPS__PLACES database available.

Step 5: Run Seed Data Script

Goal: Create database, schema, warehouse, CONFIG, PLACES, JOB_TEMPLATE, and LOOKUP tables from Overture Maps.

1. If region is NOT SanFrancisco, update the SET variables at the top of references/seed-data.sql:
   • $REGION_GEOHASH: see geohash table in references/notebook-deployment.md
   • $REGION_NAME: the city/region name (e.g., 'NewYork', 'London')
2. If the user requested custom industries in Step 3, update the LOOKUP INSERT section in references/seed-data.sql per references/industry-customization.md.
3. Run:

   snow sql -f .cortex/skills/route-optimization/references/seed-data.sql -c <connection>
   

4. Verify:

   SELECT 'PLACES' AS TBL, COUNT(*) AS CNT FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.PLACES
   UNION ALL SELECT 'LOOKUP', COUNT(*) FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.LOOKUP
   UNION ALL SELECT 'JOB_TEMPLATE', COUNT(*) FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.JOB_TEMPLATE;
   

   Expected: PLACES 50K-500K, LOOKUP 4, JOB_TEMPLATE 29. STOP if any table has 0 rows.

Output: Standing data populated for <REGION_NAME>.

Step 5b: Deploy Asset Velocity Page Views (required for the Asset Velocity page)

Goal: Create the Asset Velocity views (VW_IDLE_VEHICLES, VW_LANE_DEMAND, VW_VEHICLE_COST_OF_IDLENESS, VW_FLEET_VEHICLE_PROFILE) that power the Asset Velocity sidebar page. Preset-agnostic - shows idle vehicles of the active preset (e.g. ebikes on the default SF install).

Dependency: dwell-analysis must be deployed first - the views reference FLEET_INTELLIGENCE.DWELL_ANALYSIS.DT_DWELL_ENRICHED, which Snowflake validates at CREATE VIEW time. If Dwell Analysis is not yet deployed, skip this step and run it after Dwell Analysis; the page renders a friendly empty state with deployment instructions until then.

Runtime owner: the control-app init.ts is the source of truth for these four views (VW_IDLE_VEHICLES, VW_LANE_DEMAND, VW_FLEET_VEHICLE_PROFILE, VW_VEHICLE_COST_OF_IDLENESS) and CREATE OR REPLACEs them on every container boot. The .sql files below are the keep-in-sync source and the manual-repair path (run them when a boot recreate failed silently, e.g. DT_DWELL_ENRICHED was absent at boot). The active-preset pointer they filter on lives in ROUTE_OPTIMIZATION.CONFIG, seeded by datasets/load-seed-data.sql and by this skill's seed-data.sql.

snow sql -f .cortex/skills/route-optimization/references/extend-dim-fleet-hgv.sql -c <connection>
snow sql -f .cortex/skills/route-optimization/references/asset-velocity-views.sql -c <connection>

Verify (all should return > 0 on a seeded install):

SELECT 'VW_IDLE_VEHICLES' AS V, COUNT(*) AS CNT FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_IDLE_VEHICLES
UNION ALL SELECT 'VW_LANE_DEMAND', COUNT(*) FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_LANE_DEMAND
UNION ALL SELECT 'VW_VEHICLE_COST_OF_IDLENESS', COUNT(*) FROM FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_VEHICLE_COST_OF_IDLENESS;

Output: Asset Velocity page views created and populated for the active preset.

Step 6: Check Claude Model

Goal: Verify latest Claude Sonnet model is available in Snowflake Cortex.

See references/notebook-deployment.md (Step 7) for the test SQL and update instructions.

Step 7: Deploy AISQL Notebook

Goal: Deploy the AISQL exploration notebook, customized for <NOTEBOOK_CITY>.

Required for full demo: The AISQL notebook provides the interactive route optimization experience in Snowsight. Without it, only the seed data tables are deployed and the Route Optimization page in the control app will have its VRP simulator but no notebook-driven workflow. If you skip this step now, you can add it later by following references/notebook-deployment.md.

See references/notebook-deployment.md (Step 8) for cell-by-cell update tables, text replacement rules, post-replacement validation, and upload/create commands.

If city references already match <NOTEBOOK_CITY>, skip modification and upload directly.

Output: AISQL notebook deployed with AI prompts customized for <NOTEBOOK_CITY>.

Dashboard Schema Contract

The React Demo Dashboard page queries these exact tables and columns. If the pipeline changes column names, the React page must be updated to match.

CONFIG

Column	Type	Used By
VEHICLE_TYPE	VARCHAR	Global vehicle type selector
REGION	VARCHAR	Global region selector (updated by server on region switch)

PLACES

Column	Type	Used By
REGION	VARCHAR	RouteOptimization (region filter)
NAME	VARCHAR	RouteOptimization (place display)
CATEGORY	VARCHAR	RouteOptimization (filtering)
GEOMETRY	GEOGRAPHY	RouteOptimization (ST_X/ST_Y, ST_DWITHIN radius filter)

JOB_TEMPLATE

Column	Type	Used By
REGION	VARCHAR	RouteOptimization (region filter)
ID	NUMBER	RouteOptimization (job assignment)
SLOT_START	NUMBER	RouteOptimization (VRP time windows)
SLOT_END	NUMBER	RouteOptimization (VRP time windows)
SKILLS	NUMBER	RouteOptimization (VRP skills constraint)
PRODUCT	VARCHAR	RouteOptimization
STATUS	VARCHAR	RouteOptimization (active filter)

LOOKUP

Column	Type	Used By
REGION	VARCHAR	RouteOptimization (region filter)
INDUSTRY	VARCHAR	RouteOptimization (industry selector)
PA	VARCHAR	RouteOptimization (POI category filter)
PB	VARCHAR	RouteOptimization
PC	VARCHAR	RouteOptimization

VW_IDLE_VEHICLES (Asset Velocity)

Column	Type	Used By
VEHICLE_ID	VARCHAR	AssetVelocity (trailer id)
REGION	VARCHAR	AssetVelocity (region filter)
LAST_LOCATION_NAME	VARCHAR	AssetVelocity (table + tooltip)
LAST_LOCATION_TYPE	VARCHAR	AssetVelocity (table)
LAST_LOCATION_GEOM	GEOGRAPHY	AssetVelocity (deck.gl)
LAST_LNG / LAST_LAT	FLOAT	AssetVelocity (deck.gl getPosition)
IDLE_SINCE	TIMESTAMP	AssetVelocity (tooltip)
IDLE_HOURS / IDLE_DAYS	NUMBER	AssetVelocity (KPIs, sort, severity)
ASSIGNED_DISPATCHER	VARCHAR	AssetVelocity (table)

VW_LANE_DEMAND (Asset Velocity)

Column	Type	Used By
TERMINAL_ID / TERMINAL_NAME	VARCHAR	AssetVelocity (tooltip + VRP jobs)
TERMINAL_LAT / TERMINAL_LNG	FLOAT	AssetVelocity (deck.gl + VRP)
NET_OUTBOUND_TRIPS / DEMAND_SCORE	NUMBER	AssetVelocity (sort + VRP priority)

VW_VEHICLE_COST_OF_IDLENESS (Asset Velocity)

Column	Type	Used By
COST_OF_IDLENESS_USD	NUMBER	AssetVelocity (KPI + sort)
PROJECTED_SAVINGS_USD	NUMBER	AssetVelocity (KPI)
IDLE_SEVERITY	VARCHAR	AssetVelocity (color + badge)

ORS Functions (cross-app)

Function	Used By
OPENROUTESERVICE_APP.CORE.ISOCHRONES	Catchment preview (TABLE function)
OPENROUTESERVICE_APP.CORE.OPTIMIZATION	VRP solver
OPENROUTESERVICE_APP.CORE.DIRECTIONS	Per-vehicle route geometry (TABLE function)
SNOWFLAKE.CORTEX.COMPLETE	AI geocoding

---

Step 8: Verify

Goal: Confirm tables exist and Demo Dashboard shows the page.

1. Verify PLACES, LOOKUP, JOB_TEMPLATE tables have rows
2. Check Demo Dashboard loads Route Optimization page

Stopping Points

• Step 1: STOP if OpenRouteService Native App is not installed
• Step 2: Wait for user to activate app if services not running
• Step 3: Confirm detected region, city, and industry choices with user
• Step 4: Verify Marketplace dataset accessible
• Step 5: Verify PLACES, LOOKUP, JOB_TEMPLATE tables are populated
• Step 6: Verify Claude model is available
• Step 8: Verify Demo Dashboard shows the Route Optimization page

Troubleshooting

Issue	Symptom	Solution
Stale config file	Wrong region detected	Run rm -rf /tmp/ors* /tmp/*ors* before downloading config
Marketplace access denied	CALL SYSTEM$ACCEPT_LEGAL_TERMS fails	Requires IMPORT SHARE privilege (see Required Privileges section)
Notebook execution fails	EXECUTE NOTEBOOK errors	Check logs in Snowsight; verify OVERTURE_MAPS__PLACES accessible and warehouse active
Cortex model unavailable	"model not found" error	Try fallback model or set CORTEX_ENABLED_CROSS_REGION = 'ANY_REGION'
Services not starting	SUSPENDED or FAILED status	CALL OPENROUTESERVICE_APP.CORE.RESUME_ALL_SERVICES(); check compute pool capacity
Dashboard shows no data	Verify PLACES, LOOKUP, JOB_TEMPLATE tables are populated
Stage upload fails	Permission error	Verify WRITE privilege on stage and correct --connection
Wrong POI region	PLACES has wrong city data	Fix geohash in Step 5, re-run notebook
Custom industries missing	Dropdown shows old industries	Verify LOOKUP table; re-run from Step 5

Recovery

Re-running is safe: all statements use IF NOT EXISTS or OR REPLACE, and snow stage copy uses --overwrite. No manual cleanup needed.

Output

Complete Route Optimization demo with:

• Carto Overture Places dataset for POI data
• Exploration notebook with AISQL examples
• React VRP simulator in Demo Dashboard
• 3 configurable vehicles with skills
• Real-world points of interest for routing scenarios

Cleanup

To remove all objects created by this skill:

DROP NOTEBOOK IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.ROUTING_FUNCTIONS_AISQL;
DROP VIEW IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_VEHICLE_COST_OF_IDLENESS;
DROP VIEW IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_LANE_DEMAND;
DROP VIEW IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_IDLE_VEHICLES;
DROP VIEW IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.VW_FLEET_VEHICLE_PROFILE;
DROP TABLE IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.CONFIG;
DROP TABLE IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.LOOKUP;
DROP STAGE IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION.NOTEBOOK;
DROP SCHEMA IF EXISTS FLEET_INTELLIGENCE.ROUTE_OPTIMIZATION;

-- v1.1 also added HGV columns to DIM_FLEET. They are non-destructive (NULL for
-- non-trucking modes) and the column-add is idempotent, so cleanup is optional.
-- If a fully clean DIM_FLEET is required (e.g. before regenerating via Data
-- Studio), drop them with:
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS WEIGHT_TONS;
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS HEIGHT_M;
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS LENGTH_M;
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS WIDTH_M;
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS AXLELOAD_T;
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS HAZMAT;
ALTER TABLE SYNTHETIC_DATASETS.UNIFIED.DIM_FLEET DROP COLUMN IF EXISTS VEHICLE_SUBTYPE;

Tip: Use the cleanup skill to auto-discover all tagged objects via COMMENT tracking.