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napo committed Oct 10, 2024
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8 changes: 8 additions & 0 deletions code/graphhopper_start.sh
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@@ -0,0 +1,8 @@
if ! [ -d graph-cache/ ];
then
wget -c https://osmit-estratti.wmcloud.org/output/pbf/comuni/022205_Trento.osm.pbf;
wget -c https://repo1.maven.org/maven2/com/graphhopper/graphhopper-web/9.1/graphhopper-web-9.1.jar;
wget -c https://raw.githubusercontent.com/napo/geospatial_unitn_2024/refs/heads/main/data/config/config_trento.yml;
fi
java -jar graphhopper*.jar server config_trento.yml
https://osmit-estratti.wmcloud.org/output/pbf/comuni/022205_Trento.osm.pbf
144 changes: 78 additions & 66 deletions data/config/config_trento.yml
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Expand Up @@ -14,46 +14,45 @@ graphhopper:
#
# In general a profile consists of the following
# - name (required): a unique string identifier for the profile
# - vehicle (required): refers to the `graph.vehicles` used for this profile
# - weighting (required): the weighting used for this profile like custom,fastest,shortest or short_fastest
# - turn_costs (true/false, default: false): whether or not turn restrictions should be applied for this profile.
# - weighting (optional): by default 'custom'
# - turn_costs (optional):
# vehicle_types: [motorcar, motor_vehicle] (vehicle types used for vehicle-specific turn restrictions)
# u_turn_costs: 60 (time-penalty for doing a u-turn in seconds)
#
# Depending on the above fields there are other properties that can be used, e.g.
# - distance_factor: 0.1 (can be used to fine tune the time/distance trade-off of short_fastest weighting)
# - u_turn_costs: 60 (time-penalty for doing a u-turn in seconds (only possible when `turn_costs: true`)).
# Note that since the u-turn costs are given in seconds the weighting you use should also calculate the weight
# in seconds, so for example it does not work with shortest weighting.
# - custom_model_file: when you specified "weighting: custom" you need to set a json file inside your custom_models.directory
# or working directory that defines the custom_model. If you want an empty model you can also set "custom_model_file: empty".
# You can also use th e`custom_model` field instead and specify your custom model in the profile directly.
# - custom_model_files: when you specified "weighting: custom" you need to set one or more json files which are searched in
# custom_models.directory or the working directory that defines the custom_model. If you want an empty model you can
# set "custom_model_files: []
# You can also use the `custom_model` field instead and specify your custom model in the profile directly.
#
# To prevent long running routing queries you should usually enable either speed or hybrid mode for all the given
# profiles (see below). Or at least limit the number of `routing.max_visited_nodes`.

profiles:
- name: car
vehicle: car
weighting: custom
custom_model:
distance_influence: 70
# turn_costs: true
# u_turn_costs: 60

- name: bike
# to use the bike vehicle make sure to not ignore cycleways etc., see import.osm.ignored_highways below
vehicle: bike
weighting: shortest
# # the custom model in bike.json is defined to avoid hills
# custom_model_file: bike.json
- name: foot
vehicle: foot
weighting: shortest
- name: car
# turn_costs:
# vehicle_types: [motorcar, motor_vehicle]
# u_turn_costs: 60
custom_model_files: [car.json]

# specify the folder where to find the custom model files
custom_models.directory: custom_models
- name: foot
# custom_model_files: [foot.json, foot_elevation.json]
#
# - name: bike
# custom_model_files: [bike.json, bike_elevation.json]
#
# - name: racingbike
# custom_model_files: [racingbike.json, bike_elevation.json]
#
# - name: mtb
# custom_model_files: [mtb.json, bike_elevation.json]

# instead of the inbuilt custom models (see ./core/src/main/resources/com/graphhopper/custom_models)
# you can specify a folder where to find your own custom model files
# custom_models.directory: custom_models

# Speed mode:
# Its possible to speed up routing by doing a special graph preparation (Contraction Hierarchies, CH). This requires
# It's possible to speed up routing by doing a special graph preparation (Contraction Hierarchies, CH). This requires
# more RAM/disk space for holding the prepared graph but also means less memory usage per request. Using the following
# list you can define for which of the above routing profiles such preparation shall be performed. Note that to support
# profiles with `turn_costs: true` a more elaborate preparation is required (longer preparation time and more memory
Expand All @@ -73,22 +72,14 @@ graphhopper:
profiles_lm: []


#### Vehicles ####

# The vehicle defines the base for how the routing of a profile behaves. It can be fine tuned using the options:
# name=mycustomvehicle,block_private=true,turn_costs=true,transportation_mode=MOTOR_VEHICLE (only for the roads vehicle)
# Still, it is recommended to avoid changing the vehicle settings and change the custom model instead.
# graph.vehicles: car|block_fords=true,turn_costs=true,bike|turn_costs=true
# Other standard vehicles: foot,bike,mtb,racingbike,motorcycle,wheelchair


#### Encoded Values ####

# Add additional information to every edge. Used for path details (#1548) and custom models (docs/core/custom-models.md)
# Default values are: road_class,road_class_link,road_environment,max_speed,road_access
# More are: surface,smoothness,max_width,max_height,max_weight,hgv,max_axle_load,max_length,hazmat,hazmat_tunnel,hazmat_water,
# lanes,osm_way_id,toll,track_type,mtb_rating,hike_rating,horse_rating
# graph.encoded_values: surface,toll,track_type
# More are: surface,smoothness,max_width,max_height,max_weight,max_weight_except,hgv,max_axle_load,max_length,
# hazmat,hazmat_tunnel,hazmat_water,lanes,osm_way_id,toll,track_type,mtb_rating,hike_rating,horse_rating,
# country,curvature,average_slope,max_slope,car_temporal_access,bike_temporal_access,foot_temporal_access
graph.encoded_values: car_access, car_average_speed

#### Speed, hybrid and flexible mode ####

Expand Down Expand Up @@ -122,8 +113,11 @@ graphhopper:
# graph.elevation.edge_smoothing: ramer
# removes elevation fluctuations up to max_elevation (in meter) and replaces the elevation with a value based on the average slope
# graph.elevation.edge_smoothing.ramer.max_elevation: 5
# A potentially bigger reduction of ascend/descend is possible, but maximum slope will often increase (do not use when average_slope and maximum_slope shall be used in a custom_model)
# Using an averaging approach for smoothing will reveal values not affected by outliers and realistic slopes and total altitude values (up and down)
# graph.elevation.edge_smoothing: moving_average
# window size in meter along a way used for averaging a node's elevation
# graph.elevation.edge_smoothing.moving_average.window_size: 150


# To increase elevation profile resolution, use the following two parameters to tune the extra resolution you need
# against the additional storage space used for edge geometries. You should enable bilinear interpolation when using
Expand All @@ -135,6 +129,14 @@ graphhopper:
# graph.elevation.way_point_max_distance: 10


#### Country-dependent defaults for max speeds ####

# This features sets a maximum speed in 'max_speed' encoded value if no maxspeed tag was found. It is country-dependent
# and based on several rules. See https://github.com/westnordost/osm-legal-default-speeds
# To use it uncomment the following, then enable urban density below and add 'country' to graph.encoded_values
# max_speed_calculator.enabled: true


#### Urban density (built-up areas) ####

# This feature allows classifying roads into 'rural', 'residential' and 'city' areas (encoded value 'urban_density')
Expand All @@ -143,10 +145,10 @@ graphhopper:
# Use higher/lower sensitivities if too little/many roads fall into the according categories.
# Using smaller radii will speed up the classification, but only change these values if you know what you are doing.
# If you do not need the (rather slow) city classification set city_radius to zero.
# graph.urban_density.residential_radius: 300
# graph.urban_density.residential_sensitivity: 60
# graph.urban_density.city_radius: 2000
# graph.urban_density.city_sensitivity: 30
# graph.urban_density.residential_radius: 400
# graph.urban_density.residential_sensitivity: 6000
# graph.urban_density.city_radius: 1500
# graph.urban_density.city_sensitivity: 1000


#### Subnetworks ####
Expand All @@ -158,13 +160,16 @@ graphhopper:
prepare.min_network_size: 200
prepare.subnetworks.threads: 1


#### Routing ####

# You can define the maximum visited nodes when routing. This may result in not found connections if there is no
# connection between two points within the given visited nodes. The default is Integer.MAX_VALUE. Useful for flexibility mode
# routing.max_visited_nodes: 1000000

# The maximum time in milliseconds after which a routing request will be aborted. This has some routing algorithm
# specific caveats, but generally it should allow the prevention of long-running requests. The default is Long.MAX_VALUE
# routing.timeout_ms: 300000

# Control how many active landmarks are picked per default, this can improve query performance
# routing.lm.active_landmarks: 4

Expand All @@ -180,24 +185,19 @@ graphhopper:
# motorized vehicles. This leads to a smaller and less dense graph, because there are fewer ways (obviously),
# but also because there are fewer crossings between highways (=junctions).
# Another typical example is excluding 'motorway', 'trunk' and maybe 'primary' highways for bicycle or pedestrian routing.
import.osm.ignored_highways: footway,cycleway,path,pedestrian,steps # typically useful for motorized-only routing
# import.osm.ignored_highways: motorway,trunk # typically useful for non-motorized routing
# import.osm.ignored_highways: footway,cycleway,path,pedestrian,steps # typically useful for motorized-only routing
import.osm.ignored_highways: # typically useful for motorized-only routing

# configure the memory access, use RAM_STORE for well equipped servers (default and recommended)
graph.dataaccess.default_type: RAM_STORE

# will write way names in the preferred language (language code as defined in ISO 639-1 or ISO 639-2):
# datareader.preferred_language: en

# Sort the graph after import to make requests roughly ~10% faster. Note that this requires significantly more RAM on import.
# graph.do_sort: true


#### Custom Areas ####

# GraphHopper reads GeoJSON polygon files including their properties from this directory and makes them available
# to all tag parsers, vehicles and custom models. All GeoJSON Features require to have the "id" property.
# to all tag parsers and custom models. All GeoJSON Features require to have the "id" property.
# Country borders are included automatically (see countries.geojson).
# custom_areas.directory: path/to/custom_areas

Expand All @@ -215,6 +215,8 @@ server:
port: 8989
# for security reasons bind to localhost
bind_host: localhost
# increase GET request limit - not necessary if /maps UI is not used or used without custom models
max_request_header_size: 50k
request_log:
appenders: []
admin_connectors:
Expand All @@ -224,14 +226,24 @@ server:
# See https://www.dropwizard.io/en/latest/manual/core.html#logging
logging:
appenders:
- type: file
time_zone: UTC
current_log_filename: logs/graphhopper.log
log_format: "%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
archive: true
archived_log_filename_pattern: ./logs/graphhopper-%d.log.gz
archived_file_count: 30
never_block: true
- type: console
time_zone: UTC
log_format: "%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
- type: file
time_zone: UTC
current_log_filename: logs/graphhopper.log
log_format: "%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
archive: true
archived_log_filename_pattern: ./logs/graphhopper-%d.log.gz
archived_file_count: 30
never_block: true
- type: console
time_zone: UTC
log_format: "%d{yyyy-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
loggers:
"com.graphhopper.osm_warnings":
level: DEBUG
additive: false
appenders:
- type: file
currentLogFilename: logs/osm_warnings.log
archive: false
logFormat: '[%level] %msg%n'

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