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Mapping turn lanes for navigation in 30 cities in US #180

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abhisheksaikia opened this issue May 4, 2016 · 72 comments

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@abhisheksaikia
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commented May 4, 2016

Objective: Map missing turn lanes from secondary and up in 30 US cities.

turnlanes

Team: @mapbox/team-data

Features to map: Turn lanes (motorway, trunk, primary and secondary) from satellite imagery

Focus Area: 30 top cities in US as per population

Available data sources

Source Description Quality Coverage License
Mapbox Satellite Imagery Intermediate Good
Bing Imagery Imagery High Good
USGS large scale imagery Imagery High limited

Tasks

Location Start End(ETA) Validation
San Francisco 05/5/2016 05/11/2016 Done
Portland 05/16/2016 05/17/2016 Done
Dallas & Fort Worth 05/18/2016 5/23/2016 Done
New York 05/23/2016 05/30/2016 Done
Detroit 05/30/2016 06/02/2016 Done
Houston 06/03/2016 06/09/2016 Done
Philadelphia 06/08/2016 06/15/2016 Done
Baltimore 06/15/2016 06/16/2016 Done
Oklahoma 06/22/2016 06/22/2016 Done
Boston 06/22/2016 06/27/2016 Done
Denver 06/28/2016 06/29/2016 Done
Seattle 06/29/2016 07/01/2016 Done
Chicago 07/01/2016 08/05/2016 Done
San Diego 08/08/2016 08/10/2016 Done
Austin 08/10/2016 08/11/2016 Done
Phoenix 08/11/2016 08/18/2016 Done
DC 23/01/2017 30/01/2017 Done
LA_exterior 13/02/2017

JOSM Workflow

Setup

Mapping

  • Check the roads for turn lanes at exits and entry points
  • Split the road into segments based on the total number of lanes for the segment
  • For each road segment tag the turn lanes based on the road markings in the direction of the way. Eg. turn:lanes=left|through|right. See OSM turn:lanes
  • For bi-directional segments, use turn:lanes:backward= and turn:lanes:forward= to specify turn lanes in each direction.
  • Verify correct tagging using the Lane attributes style

Issues to keep in mind:

  • For QA and edge cases in turn lanes mapping and how to handle them**(parking lanes, splitting roads for start and end of turn lanes, handling of dual carriageways, etc)** look into the QA for turn lane data document.

Changeset Comment: Add missing turn lanes from satellite imagery https://github.com/mapbox/mapping/issues/180

Source: Bing/Mapbox/USGS Large Scale Imagery

Turn lane mapping tickets: #144, #153

@abhisheksaikia

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commented May 6, 2016

Capturing the initial estimates for turn lanes mapping sprint in top 30 US cities:

According to the statistics that we generated during the LA turn lanes mapping sprint, this is the estimated timeline for completing the turn lanes mapping sprint in the full 30 cities:

Total area to be covered in 30 US cities: 37,545 square kilometers
Estimated features to map: ~375,450 turn lanes in 30 US cities(~10 turn lanes per square kilometer)
Turn lanes per person per hour:~25
Total number of team members working full time(6 hours per day): 15
Total estimated working days: ~100 working days(5 months)

Optimizing the workflow and initial time estimates:

  • These statistics are heavily dependent upon our LA turn lanes mapping sprint. LA had a very high density of turn lanes in even primary, secondary and tertiary roads which is generally not the case in other cities. This will immediately lead to a reduction in our mapping effort.
  • Optimizing the JOSM toolset to help map turn lanes better: a knife tool for quick splitting of road segments in turn lanes mapping, a JOSM plugin that automatically sets the first lane as left and also automatically predicts the turn lane scheme for the next junction, once a junction has been tagged.
  • This time estimate also does not include the amount of time taken for validation. As 30 cities will be a huge mapping project, we need to find faster and better ways of validating turn lanes than the traditional method of validating tasks in the tasking manager.

Next actions:

  • @planemad to work with @samely and @Rub21 and create the turn lanes mapping tools to optimize our mapping effort.
  • @jothirnadh and me to capture and update daily statistics for turn lanes mapping in each city and consequently review our timeline based on the mapping speed by our team for the first 2 cities (Portland and San Francisco).

cc @mapbox/team-data

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commented May 12, 2016

@mapbox/team-data have completed adding turn lanes in SF Bay area.

Final Statistics in SF bay area turn lanes mapping sprint(excluding validation):

  • Total number of working days: 4
  • Average number of mappers working per day: 12 (average 6 hours per day)
  • Total number of personal hours by the team: 288
  • Total number of turn lanes mapped: 10,977
  • Turn lanes/mapper/hour: **~ 38 turn lanes**
  • Total existing turn lanes in SF bay in OSM: 15386
  • Total area covered in SF bay: 1925.66 square kilometers
  • Turn lanes density in San Francisco Bay area: ~8 turn lanes/square kilometer

Observations:

  • The mapping speed for @mapbox/team-data has increased from an estimated 25 turn lanes per mapper per hour to 38 turn lanes per mapper per hour.
  • The Turn lanes density in SF is ~8 turn lanes/sq. km, down from our initial estimate of 10 turn lanes per square kilometer.
  • This will immediately lead to a significant reduction in our initial mapping estimate of 100 working days for 30 cities. The estimate can be reviewed based on the average of density of turn lanes we get from the first three cities we map.

Next Actions:

@abhisheksaikia

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commented May 12, 2016

As part of our discussion with @planemad @maning @jothirnadh on optimization of workflow for adding turn lanes, the following changes are made to the workflow which we will follow while mapping turn lanes in Portland and all further tasks in the turn lanes mapping sprint.

  • We are going to map all turn lanes from secondary and up instead of tertiary and up.
    Use this inverse filter: highway=motorway|trunk|primary|secondary|*link|motorway_link
  • Use the knife tool for quick splitting of ways: Steps for activating the Knife tool

cc @mapbox/team-data

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commented May 12, 2016

Portland City coverage: missing highways, turn lanes coverage, satellite imagery coverage.

I did an overview of the roads mapped in Portland City. The city seems to be well mapped and the quality of the satellite imagery (Bing) is good for mapping turn lanes.

CC:/ @abhisheksaikia @maning

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commented May 16, 2016

Updating the statistics in SF bay (Stats excluding validation) from above, and providing a team wise breakup of the mapping stats between India and Peru teams:

Team Average hours per mapper/day Average number of mappers per day Turn lanes added by team Turn lane per mapper/hr
Bangalore 5 6.25 2071 ~17
Peru 8 5.75 8252 ~45

The statistics of turn lanes added during the SF bay sprint:

  • Turn lanes added by the Peru and India teams combined during the sprint: 10,323
  • Turn lanes added by the community during the sprint: 674

cc:/ @mapbox/team-data

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commented May 16, 2016

Updating the inverse filter to include all roads until secondary (including all road links), according to our revised workflow: highway=motorway|trunk|primary|secondary|*link|motorway_link

The reason is that we have a high density of tertiary roads to review but a low density of turn lanes per km that can be mapped.

cc @mapbox/team-data

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commented May 16, 2016

We're skipping adding turn lanes to situations where the lanes are marked by yellow lines on both sides. These are probably turn-lanes-bothways.

screen shot 2016-05-16 at 4 12 49 pm

screen shot 2016-05-16 at 4 13 00 pm

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commented May 16, 2016

Another Observation: Portland has pretty unclear satellite imagery (both Bing and USGS Large Scale Imagery).

screen shot 2016-05-16 at 4 24 56 pm

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commented May 18, 2016

The 🔪 tool is updated with the auto select way option as per this issue. Please do update your plugin with the following jar file and restart your JOSM to see the changes.

cc:/ @mapbox/team-data

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commented May 19, 2016

Portland Task Completion Summary

We wrapped up mapping turn lanes in the Portland area and added a total of 2,823 turn lanes. The approach to mapping in Portland was different from the work we did in San Francisco, and we only covered roads that were classfied as secondary and above. Here is a full summary of our approach, and results. We welcome feedback on our approach, and suggestions for improving this workflow.

Pre-mapping Checklist

  • We looked at satellite imagery coverage and assessed for clarity as this significantly impacts one's ability to clearly identify turn lanes 💯
  • We assessed the existing road network coverage to determine the number of roads under mapped 💯
  • We researched the presence of unmapped dual-carriageways to determine the extent to which roads need to be split so as to avoid creating conflicts when mapping turn-lanes 👍

Mapping roads classified as secondary and above

We decided to focus on adding turn lanes on roads classified as secondary or above after our research showed that a majority of turn lanes are present on such roads, and tertiary roads and residential streets have minimal to no turn lanes to map. This also helped us keep the scope of the mapping effort more focused.

Final Statistics in Portland turn lanes mapping sprint (excluding validation):

  • Total number of working days: 1
  • Number of mappers worked: 16 (average 6.5 hours per day)
  • Total number of people hours by the team: 104
  • Existing turn lanes before sprint: 193
  • Total number of turn lanes mapped during sprint: 2,823
  • Turn lanes/mapper/hour: ~24 turn lanes
  • Total area covered: 500.38 square kilometers
  • Turn lanes density: ~6 turn lanes/ square kilometer

Observations:

The overall mapping speed for adding turn lanes in Portland decreased from our experience mapping turn lanes in Los Angeles city. This decrease can be attributed to a higher density of turn lanes present in LA which made it faster to identify turn-lanes overall.

Going Forward

We'll be posting details here, and welcome whomever is interested to join us in mapping turn lanes 😄

@dobratzp

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commented May 19, 2016

Especially when doing large-scale editing of roads, be careful when splitting and combining Way objects. These Way objects may be members of road route relation and/or public transport route relations. The order of the Way objects within the Relation is significant.

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commented May 20, 2016

@dobratzp this is a really serious issue since we do get conflicts on route relation members when working across cities. Sadly the JOSM relation conflict mechanism does not make it very easy to properly resolve them and I suspect relations worldwide are breaking everyday since we do not yet have a usable conflict management and integrity checking interface for all relations on the map.

From our end, the team tries to be really careful when working on roads with relations, but we're lacking a good QA workflow to ensure nothing is broken once the task is complete. For starters, we will ticket out suggestions to improve the intelligence of conflict management in JOSM so that it can suggest a resolution. Would be great to hear your thoughts as well on how this could be done.

cc @mapbox/team-data

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commented May 20, 2016

I agree that it seems like JOSM doesn't always do the right thing when you are splitting Ways as far as bus routes and turn restrictions go. If all I had to do was fix a few bus routes by making them contiguous again, it wouldn't be so bad.

I started the process of fixing Portland area bus routes, but then I realized just how bad Changeset 39375345 is really is. There are few duplicate Way objects, which are fairly easy to remedy. However, there are a number of relations which are completely broken.

I'm not sure how you even managed to do this. Somehow, you've replaced the members of all of the following relations with the same members from Bus Route 52: Portland Community College Rock Creek => Beaverton Transit Center

Some of these are bus route relations and some of them are turn restriction relations.

Also, all of the members of Bus 52: Beaverton Transit Center => Portland Community College Rock Creek have been deleted.

Unfortunately, I can't cleanly revert Changeset 39375345, so I may have to ask for help with the Data Working Group.

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commented May 20, 2016

Before I got to the mess of Changeset 39375345, I did want to mention a few JOSM warning that you should definitely be paying attention to as they relate specifically to turn lanes:

Number of lanes greater than *:lanes

For example, if you have lanes=2, then you should have 2 items in your various turn:lanes tags

oneway=yes together with turn:lanes:forward

Use turns:lanes and not turns:lanes:forward for oneway streets

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commented May 20, 2016

I'm wondering if end up having multiple people editing different portions of the same route relation at the same time and you are getting conflicts. I would suggest making changeset that are much smaller than what you are currently doing:

  1. Download a short segment of road
  2. Edit the turn lanes
  3. Upload
  4. Restart JOSM
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commented May 20, 2016

@dobratzp Looking into https://www.openstreetmap.org/changeset/39375345 its really strange, would be useful to know how it might have happened, @poornibadrinath any ideas?

Validation

  • Number of lanes greater than *:lanes. We leave the lanes tag untouched and only focus on turn:lanes. The reasoning is that for a routing system the turn:lane information would override the lane information when present since they may not always be consistent as in this case. Its also an open question if turn lanes should be considered as a full width traffic lane as per the OSM wiki. This is also easily fixable via an automated edit at any point when required.
  • oneway=yes together with turn:lanes:forward. This is taken care of in our validation workflow. I just fixed 24 such cases in Portland using this overpass query.

Avoiding relation conflicts
Making small changesets will not completely eliminate the issue since two members working on some part of a long route relation is still quite high. The only way to guarantee no conflicts is for no one else to edit in the same city simultaneously. The long term solution maybe smarter conflict resolution on the software side since it is extremely easy for a human to break relations with the current tools, even for advanced mappers with no easy mechanism to restore them either.

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commented May 22, 2016

It seems like there is some inconsistency in how you are tagging turn lanes. Sometimes you use "none" and sometimes not. For example:
||left vs. none|none|left
Are these values equivalent for turn:lanes? If so, please standardize on one for consistency.

@osMatt

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commented May 22, 2016

While I was looking for some recently added left turns at intersections, I noticed a wrong turn lane tagging. It should be possible to check for these systematically with an overpass query. http://www.openstreetmap.org/way/419223674 is tagged with ||left|. Pattern to check: the turn lane string does not start with left, but there is some left turn after a pipe symbol. It is very unlikely to have a left turn lane that is to the right of a lane that is not tagged at a left turn lane.

@abhisheksaikia

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commented May 23, 2016

@dobratzp I have run a overpass query to determine the number of turn lanes that have none in the tag and it comes out to 278 in Portland.The query is: http://overpass-turbo.eu/s/gnF. Both left|| and left|none|none are used widely as seen here: http://taginfo.openstreetmap.org/keys/?key=turn%3Alanes&filter=ways#values. Also the Lane and road attributes style appears to take both these styles of tagging as equivalent. But thanks for bringing this up. From now on we will standardise this for consistency and stick to the style of left|| instead of left|none|none.

cc @mapbox/team-data

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commented May 23, 2016

@osMatt I have run a overpass query in Dallas for all the turn lanes containing left but not starting with left. At present it shows all the turn lanes that does not start with l. It can be modified to include only those turn lanes which start with |. For now, it's showing 196 suspicious ways, which will be eyeballed and validated during our validation work. Thanks for pointing this out. This and other common errors like oneway-yes with turn:lanes:forward and turn:lanes:backward` is definitely something we need to validate and correct en masse once each city is completed. Have opened a ticket documenting these issues here: osmlab/osmlint#109

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commented May 24, 2016

Dallas Task Completion Summary

We wrapped up mapping turn lanes in Dallas and Fort Worth and added and validated a total of 6,267 turn lanes in Dallas. The total turn lanes count in Dallas after the sprint is 6622 at present. Similar to our approach in Portland we only focused on adding turn lanes to roads classified secondary and above.

Improved Tooling

We regularly used the knife tool for quick splitting of ways while adding turn lanes. Give it a try and share any feedback you have for improving it.

Community participation

We got a lot of help from OpenStreetMap contributors for this sprint, especially when it involved validating the data we added. Here are a few examples of this:

We have tightened up our validation work based on feedback received to clean up two common errors en masse:

Observations

  • The satellite imagery quality in Dallas and Fort Worth was not of the highest quality for adding turn lanes. For this purpose, imagery had to be alternated frequently between Bing, Mapbox and USGS satellite imagery for verification and mapping missing turn lanes.
  • The density of turn lanes was the lowest among all the three cities mapped till now: ~2.5 turn lanes per square kilometer but this advantage was offset by the relatively poor image quality and the need to eyeball a huge area (~2,653 square kilometers)

Going forward

The team will continue adding turn lanes in New York. Join in if you are interested in mapping or let us know how we can improve the workflow at any time.

@jothirnadh

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commented May 31, 2016

New York task completion summary:

We wrapped up mapping turn lanes in New York and added a total of 7,509 turn lanes. The total turn lanes count in New York after the sprint is 7780 at present. Similar to our approach in Dallas and Fort Worth we only focused on adding turn lanes to roads classified as secondary and above.

Community participation

As per the community suggestions in our Portland task we tried to be more concrete wihile mapping turn lanes on the roads with pre existing relations.

Final Statistics in New York turn lanes mapping sprint (including validation):

  • Total number of working days: 6
  • Existing turn lanes before sprint: 49
  • Total number of turn lanes mapped during sprint: 7,731
  • Total area covered: 1827 square kilometers
  • Turn lanes density: ~4.5 turn lanes/ square kilometer

Observations

  • The Satellite imagery coverage in New York is good enough to map turn lanes. We stuck to Bing imagery for the entire task.
  • There are on an average of ~4.5 turn lanes per square kilometer in New York which is higher than the turn lanes in Dallas.
  • We encountered many missing highway links during the process of mapping turn lanes which can be covered in further mapping projects.

Going forward

The team will continue adding turn lanes in Detroit. Join in if you are interested in mapping or let us know how we can improve the workflow at any time.

@rickmastfan67

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commented Aug 23, 2016

Sounds like what happened here is that some of the Mapbox team didn't refresh the data on their end before continuing onto another road to add in turn lanes, thus creating the problems @drkludge mentioned above with the damaged relations. Looking at this screenshot that @samely posted above, it seems you aren't taking advantage of a major item in JOSM that helps to try to prevent stuff like this. The "Update Modified" tool (which I've personally pinned right beside the 'upload' button in the toolbar, Ctrl+Alt+M should be the shortcut for it) is something I ALWAYS use before even attempting to upload anything to the OSM database to help prevent any possible chance of a conflict. Normally, I never do get a conflict, but in the rare times I have, this has saved me from screwing anything up. And if what I did was a minor change, I just delete the layer, and restart with fresh data to prevent any problems. Otherwise, I do attempt to solve the conflict right there before attempting to upload.

Another tactic I've been using is whenever I have finished uploaded something (after of course doing the "Update Modified" before the upload), I always completely delete the data layer I was working on, and download a completely fresh copy of the area data before I continue on editing. This should always be done between uploads, and really should become second nature to ANY experienced OSM mapper using JOSM. This also helps prevents any problems when somebody else has uploaded a new version of a way/relation that they split since you downloaded the data from the OSM servers. For example, if somebody had just created a new relation that covers two ways, but it isn't in your copy of the data, and you split one of the ways in that relation? That's a great example of how the data can easily get broken and possibly create unintended gaps in relations that shouldn't be there. Sure, it might slow you down by 20 seconds or so between tasks, but would you rather spend an hour or more fixing relation data that got damaged because of not keeping the data synced on your end? I'd chose the 20 seconds over the hour myself. lol.

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commented Aug 23, 2016

@drkludge @Andygol @samely @rickmastfan67 lets move the broken relation conversation to #224

@jothirnadh

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commented Jan 20, 2017

Recently Mapbox satellite imagery in DC is rendered with 3-inch recent ortho imagery which will be a great spot to resume our turn lane mapping effort which we paused in August 2016. Created a turn lane mapping task for DC which we can target to hit next week. There is a total of 361 mapped turn lanes in DC.

Points to be noted:

  • Let's make sure to add missing streets at the junctions where we map turn lanes if we come across any 🙏.
  • Make sure the relation of the road is not broken before splitting the road for adding a turn lane
  • Let's stick to the same workflow which we followed to map turn lanes in Phoenix apart from adding missing streets at junctions.

cc:// @RichRico @maning @abhisheksaikia

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commented Jan 20, 2017

There is data set with Intersection Points on opendata.dc.gov with 18,276 features - http://opendata.dc.gov/datasets/4b4155ee7bb443aa9a37a3f8e22a8abc_35
intersection points 2017-01-20 19-12-10

There is a possibility to mark turn:lanes on the roads around ☝️ these points. For this purpose it is good to use https://osmlab.github.io/to-fix/.

@Rub21, is it possible to make to-fix task for one of DC neighborhoods for trial run?

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commented Jan 20, 2017

Doing turn lane mapping task for DC please pay attention on such cases 👇
and apply right oneway=yes tagging and direction for the way

java openstreetmap editor 2017-01-20 20-24-51

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commented Jan 23, 2017

is it possible to make to-fix task for one of DC neighborhoods for trial run?

@Andygol before we do this, some clarifications;

  • The way to-fix works is that a mapper will be assigned a random intersection to work for every task. We lose context on the area.
  • We may introduce conflicts when several people were assigned to an intersection that is part of a long road.
  • We don't map turn lanes on residential roads, the intersection you linked include all intersections regardless of highway type. How do we filter this out?

@jothirnadh @Rub21 @samely

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commented Jan 23, 2017

@maning

  • The way to-fix works is that a mapper will be assigned a random intersection to work for every task. We lose context on the area.

Only in case if we add not only turn:lanes but we add lanes=* tagging along the way between intersection

  • We may introduce conflicts when several people were assigned to an intersection that is part of a long road.

The same may happened even in standard workflow when way goes across two tasks

  • We don't map turn lanes on residential roads, the intersection you linked include all intersections regardless of highway type. How do we filter this out?

There is possible just to skip it as we do it in to-fix usually or before creating task in to-fix find nodes that is near Major roads

cc @jothirnadh @Rub21 @samely

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commented Jan 23, 2017

@Andygol @maning

There is possible just to skip it as we do it in to-fix usually or before creating task in to-fix find nodes that is near Major roads

I can help you filtering this data for Major Roads, 18,276 is a lot of items to do a skip.

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commented Jan 23, 2017

@RichRico @Rub21 @samely it would be great if @mapbox/peru-office can take up this DC turn lane mapping task and target to complete it as soon as possible 🚀

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commented Jan 23, 2017

@Andygol @maning , I just filtered the point for major roads, it reduces to 10,198 items. find all here, https://gist.github.com/anonymous/268daa5bd7f747c21d45a4cd1253a4f6.

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commented Jan 23, 2017

The knife tool is now part of the auto_tools plugin, which can easily be installed through the default plugin installation. No "activation" needed.
See http://wiki.openstreetmap.org/wiki/JOSM/Plugins/Knife-tool

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commented Jan 24, 2017

@jothirnadh @Andygol
Today the ayacucho office began to work on the task of turn lanes in Washington DC

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commented Jan 30, 2017

While validating turn lanes in DC, I found that the base data of DC is not aligning with new Mapbox 2015 imagery. Mostly in case of Major highways which are constructed recently.

screen shot 2017-01-30 at 2 59 22 pm

This might be because the existing data is traced from outdated Bing imagery (2011) which drastically changed in time.

mapbox-bing change

Mapbox-2015, bing-2011

It would be great if we can have a separate task to align major roads in DC city with Mapbox 2015 imagery to update the base map.

cc:// @maning @planemad @abhisheksaikia @RichRico @shvrm

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commented Jan 31, 2017

Washingtong DC task completion summary:

Great work @mapbox/team-data on adding and reviewing turn lanes in Washington DC 🎉 . Our team reviewed and added turn lanes based on the new 3-inch recent orthoimagery in DC. Do check it out.

During the course of this task, our team added ~2548 turn lanes in DC during a course of 3 mapping days with a total of 8 mappers working on the task. The total count of turn lanes in DC now is ~3200.

Final Statistics in Washington DC turn lanes mapping sprint (including validation):

  • Total number of working days: 3
  • Existing turn lanes before sprint: 806
  • Total number of turn lanes mapped durg sprint: 2548
  • Total area covered: 755.399 square kilometers
  • Turn lanes density: ~3 turn lanes/ square kilometer

Findings from the current task:

  • The major highways are not aligned with Mapbox imagery in core city area which should be fixed to improve base map in DC.
  • The existing road classification in DC looks a bit odd, should be cross verified once.
  • In general, the road with physical separation is mapped as a dual carriageway in OSM. While mapping turn lanes if we come across any roads mapped as single carriageway instead of dual carriageways we make sure to split the road. But if that road is having an existing relation, then we skip the road to make sure we don't break the relation. We are coming across such cases more often and it is good to get a solution for this problem. @Andygol and @samely and ideas on how we can solve this issue.
  • Turn lanes in tertiary roads are not being mapped as a part of the current workflow but found a couple of them existing in tertiary roads. Continuing from next task lets make sure to cross verify the ratio of turn lanes on tertiary roads before starting the task.
  • In this particular task turn lanes were mapped using Mapbox imagery for core city area and Bing imagery at city outskirts, going forward the task can be limited so the people don't need to cross verify with varying sources.

Please feel free to contribute and give feedback on our mapping processes on our mapping repo where we track all our ongoing mapping projects.

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commented Feb 13, 2017

Great work in mapping turn lanes in DC 👏 . Continuing turn lane mapping quest, let's hit missing turn lanes in outskirts of LA covering Pomona, San Bernardino, and Redlands. Created a mapping task for this region which has ~582 existing turn lanes.

Major blockers:

  • There are a lot of roads mapped as bi-directional roads, which are supposed to be mapped as dual carriageways, due to the presence of physical barrier in between them. Please make sure to split them into dual carriageways before mapping.
  • Don't split the roads having route relations as there is no proper workflow to fix them. Need help from local community members for fixing this issue.

Ex:
screen shot 2017-02-13 at 5 20 04 pm

Road mapped as bi-directional road with an existing relation

cc:// @mapbox/team-data

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commented Feb 15, 2017

You can find the description of the workflow "How to split a bidirectional road to the road with separate ways in each direction" here - https://gist.github.com/Andygol/a2ff609bb4d71274245d51b1c253b832


dealing with relations ☝️

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commented Feb 15, 2017

@mapbox/team-data if you are faced relation for a Public Transport route, ping me with links to it for extending workflow on such case.

@jothirnadh

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commented Feb 16, 2017

Thanks for sharing the ^^ workflow @Andygol, @chtnha and I will do a trial run and post our findings soon before including it into our regular workflow 🙇 .

Major findings from validation so far:

  • We are not mapping turn lanes/ splitting the road as dual carriageways if the road has an existingRoute relations, but finding roads not touched even if it is tagged with turn restrictions. Let's make sure the roads with turn restrictions are not skipped.
  • Don't touch roads with route relation for now, don't even map turn lanes in that roads.
  • In few blocks the bi-directional roads with physical separation are not mapped as dual carriageways even if they are not a part of any route relation.

@mapbox/team-data do invalidate the blocks which fail to fulfill the above criteria and let the mapper fix them.

@ridixcr

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commented Feb 16, 2017

Guys when I was validating turn lanes on # 81 - Turn Lanes in Los Angeles outskirts- Chino, San Bernardino & Redlands found this error and solved it, as follow, according to the turn restriction rules.

Gif

@Andygol @jothirnadh @RichRico

@maning

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commented Feb 17, 2017

When we create dual-carriageways, make sure to update lanes count for the created ways and not just in the way which has turn-lanes.

@Yurasi

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commented Feb 17, 2017

@mapbox/team-data do invalidate the blocks which fail to fulfill the above criteria and let the mapper fix them.

@mapbox/peru-office thinks that instead to invalidate the blocks, we shlould correct them, in this way we could reduce the time in finishing the task, because we aren't going to take extra time in reviewing by one person and validating again by another person. Also, instead to invalidate we could left a comment on the block with the kind of mistake we have corrected during the validation.

Some findings from validation so far:

  • The number of lanes not coincide with number of carriles. This because of that some aren't using the turnlanes plugin.
  • Some make a mistake of identify merge_to with slight.

@jothirnadh @maning @karitotp @RichRico @poornibadrinath

@RichRico

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commented Feb 20, 2017

Turn Lane LA exterior task completion summary:

Great work @mapbox/team-data on adding and reviewing turn lanes in LA Exterior 🎉 . that were missing turn lanes in outskirts of LA covering Pomona, San Bernardino, and Redlands.

During the course of this task, our team added ~9,075 turn lanes in LA Exterior during a course of 5 mapping days with a total of 22 mappers working on the task. The total count of turn lanes in LA exterior now is ~9,657.

Final Statistics in LA turn lanes mapping sprint (including validation):

  • Total number of working days: 5
  • Existing turn lanes before sprint: 582
  • Total number of turn lanes mapped during sprint: 9,075

Findings from the current task:

  • In the process we find the way to solve relations of turn restriction #180 (comment)
  • The best way to validate the blocks is not to invalidate them but to leave a note and finish the correction of the block, in this way it will reduce the validation time, and some people aren't using the turn lanes plugin #180 (comment)
@maning

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commented Nov 12, 2017

Paused. Wil revisit later.

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