Tourroute planen

Planen and optimize a multi-stop tour route with time estimates, distance calculations, and points of interest along the way.

Wann verwenden

• Planning a road trip or walking tour with multiple destinations
• Optimizing visit order to minimize total travel time or distance
• Discovering restaurants, viewpoints, or cultural sites along a route
• Generating a day-by-day itinerary with realistic time budgets
• Comparing driving vs. walking vs. public transport options

Eingaben

• Erforderlich: Auflisten of waypoints (place names, addresses, or coordinates)
• Erforderlich: Travel mode (driving, walking, cycling, public transport)
• Optional: Starten and end points (if different from first/last waypoint)
• Optional: Time constraints (departure time, must-arrive-by, opening hours)
• Optional: POI categories to discover (food, viewpoints, museums, fuel)
• Optional: Preferred route type (fastest, shortest, scenic)

Vorgehensweise

Schritt 1: Definieren Waypoints

Sammeln and structure all stops the tour must include.

Waypoint Schema:
┌──────────┬────────────────────────────────────────────┐
│ Field    │ Description                                │
├──────────┼────────────────────────────────────────────┤
│ name     │ Human-readable label for the stop          │
│ address  │ Street address or place name               │
│ lat/lon  │ Coordinates (if known; otherwise geocode)  │
│ duration │ Time to spend at this stop (minutes)       │
│ priority │ Must-visit vs. nice-to-have                │
│ hours    │ Opening/closing times (if applicable)      │
│ notes    │ Parking, accessibility, booking required    │
└──────────┴────────────────────────────────────────────┘

Trennen fixed-order waypoints (e.g., hotel at start and end) from reorderable waypoints.

Erwartet: A structured list of all waypoints with at minimum a name and either an address or coordinates for each.

Bei Fehler: If a waypoint is ambiguous (e.g., "the castle"), use WebSuchen to resolve it to a specific location. If coordinates are needed but only a name ist verfuegbar, defer to Step 2 for geocoding.

Schritt 2: Geocode and Validate

Konvertieren all waypoints to latitude/longitude coordinates and verify they are reachable.

Geocoding Sources (in preference order):
1. Nominatim (OpenStreetMap) - free, no key required
   https://nominatim.openstreetmap.org/search?q=QUERY&format=json

2. Overpass API - for POI-type queries
   https://overpass-api.de/api/interpreter

3. Manual coordinates from mapping services

Fuer jede waypoint:

1. Query the geocoding service with the address or place name
2. Verifizieren the returned coordinates are in the expected region
3. Pruefen, dass multiple results are disambiguated (pick the correct one)
4. Speichern coordinates alongside the original waypoint data

Erwartet: Every waypoint has valid latitude/longitude coordinates, and all points fall innerhalb a plausible geographic region (no outliers on wrong continents).

Bei Fehler: If geocoding returns no results, try alternative spellings, add region/country qualifiers, or search for nearby landmarks. If a waypoint is in a remote area with poor OSM coverage, use WebSuchen to find coordinates from travel blogs or tourism sites.

Schritt 3: Optimieren Route Order

Bestimmen the visit sequence that minimizes total travel time or distance.

Optimization Strategies:
┌─────────────────────┬────────────────────────────────────────┐
│ Strategy            │ When to use                            │
├─────────────────────┼────────────────────────────────────────┤
│ Fixed order         │ Stops must be visited in given sequence│
│ Nearest neighbor    │ Quick approximation for 5-15 stops     │
│ TSP solver          │ Optimal ordering for any number        │
│ Time-window aware   │ Stops have opening hours constraints   │
│ Cluster-then-route  │ Stops span multiple days/regions       │
└─────────────────────┴────────────────────────────────────────┘

For the nearest-neighbor heuristic:

1. Starten at the designated origin
2. From the current position, select the unvisited waypoint closest by travel time
3. Move to that waypoint and mark it visited
4. Wiederholen until all waypoints are visited
5. Zurueckgeben to the designated end point (if round trip)

For multi-day tours, cluster waypoints by geographic proximity first, then optimize innerhalb each day.

Erwartet: An ordered sequence of waypoints that produces a route ohne excessive backtracking. Total distance sollte innerhalb 20% of the theoretical optimum for fewer than 10 stops.

Bei Fehler: If the nearest-neighbor result has obvious backtracking (later stops are closer to earlier ones), try reversing the route or use a 2-opt improvement: swap pairs of edges and keep the swap if it shortens the route. For time-window constraints, verify that arrival times at each stop fall innerhalb opening hours.

Schritt 4: Berechnen Times and Distances

Berechnen travel time and distance fuer jede leg of the route.

Time Estimation Methods:
┌──────────────┬────────────┬────────────────────────────────┐
│ Mode         │ Avg Speed  │ Notes                          │
├──────────────┼────────────┼────────────────────────────────┤
│ Highway      │ 100 km/h   │ Varies by country/road type    │
│ Rural road   │ 60 km/h    │ Add 20% for winding roads      │
│ City driving │ 30 km/h    │ Add time for parking            │
│ Walking      │ 4.5 km/h   │ Flat terrain; reduce for hills │
│ Cycling      │ 15 km/h    │ Touring pace with luggage      │
│ Hiking       │ 3-4 km/h   │ Use Munter formula for accuracy│
└──────────────┴────────────┴────────────────────────────────┘

Fuer jede consecutive pair of waypoints:

1. Berechnen straight-line (haversine) distance as a baseline
2. Anwenden a detour factor (1.3 for roads, 1.4 for urban, 1.2 for highways)
3. Schaetzen travel time from adjusted distance and mode speed
4. Hinzufuegen buffer time: 10% for driving, 15% for public transport
5. Sum leg times plus dwell times at each stop for total tour duration

Erwartet: A time/distance matrix for all legs, with a running cumulative time that accounts for both travel and dwell time at each stop. Total tour duration sollte realistic (not exceeding available daylight for walking tours).

Bei Fehler: If estimated times seem unrealistic (e.g., 2 hours for a 10 km city drive), check whether the detour factor is appropriate. For mountain roads, increase the detour factor to 1.6-2.0. For public transport, use WebSuchen to check actual timetables anstatt estimating.

Schritt 5: Generieren Itinerary with POIs

Compile the optimized route into a complete itinerary with discovered points of interest.

POI Discovery (Overpass API query pattern):
  [out:json];
  (
    node["tourism"="viewpoint"](around:RADIUS,LAT,LON);
    node["amenity"="restaurant"](around:RADIUS,LAT,LON);
    node["amenity"="cafe"](around:RADIUS,LAT,LON);
  );
  out body;

Recommended search radius:
- Along route corridor: 500 m for walking, 2 km for driving
- At waypoints: 1 km radius

Erstellen the itinerary document:

1. Header with tour name, dates, total distance, total time
2. Fuer jede day (if multi-day):
   • Day summary (start, end, total km, total hours)
   • Fuer jede leg: departure time, travel mode, distance, duration
   • Fuer jede stop: arrival time, dwell time, description, POIs nearby
3. Logistics section: parking, fuel stops, rest areas, emergency contacts
4. Abbilden reference (link to route on OpenStreetAbbilden or export as GPX)

Erwartet: A complete, time-budgeted itinerary document with realistic schedules, POI suggestions at each stop, and practical logistics information.

Bei Fehler: If POI queries return too many results, filter by rating or relevance. If the itinerary exceeds available time, mark lower-priority stops as optional or split into additional days. If no POIs are found in remote areas, note this and suggest the traveler research locally on arrival.

Validierung

• All waypoints are geocoded with valid coordinates
• Route order minimizes backtracking (no obvious inefficiencies)
• Travel times are realistic for the chosen mode
• Dwell times at each stop are accounted for
• Total tour duration fits innerhalb the available time window
• POIs are relevant and located near the route
• Opening hours of time-sensitive stops are respected
• Itinerary includes practical logistics (parking, fuel, rest stops)

Haeufige Stolperfallen

• Ignoring opening hours: Optimizing purely by distance can route you to a museum nach it closes. Always check time-window constraints for attractions.
• Underestimating urban travel: City driving and parking can double the expected time. Hinzufuegen generous buffers for urban stops.
• Over-packing the itinerary: Filling every minute leaves no room for delays or spontaneous discoveries. Erstellen in 30-60 minutes of slack per half-day.
• Straight-line distance fallacy: Haversine distance severely underestimates actual road distance, besonders in mountainous or coastal terrain. Always apply a detour factor.
• Forgetting return logistics: One-way routes need plans for returning rental cars, catching trains, or arranging pickup.
• Seasonal road closures: Mountain passes, ferries, and scenic routes kann closed seasonally. Verifizieren access dates vor routing.

Verwandte Skills

• create-spatial-visualization

  — render the planned route on an interactive map

• generate-tour-report

  — compile the itinerary into a formatted Quarto report

• plan-hiking-tour

  — specialized planning for hiking segments innerhalb a tour

• assess-trail-conditions

  — check conditions for any walking/hiking legs