Categories
Bike Share London OpenLayers OpenStreetMap Technical

All the Docks: Technical Notes on the Routes and Map

Routes

I created GPX route files for the challenge. These were created manually in QGIS, using the OpenStreetMap standard “Mapnik” render as a background, by drawing lines, with Google Street View imagery used to check restrictions.

I split each team’s route into 12 stages (so 36 altogether), which were initially each just over 10km and ended at a docking station. Each stage contained between 10 and 40 sequential legs to docking stations. I’m not sure I would trust proper routing engines (based on Google Maps or OpenStreetMap, normally) to have found better routes on each leg between each docking station, than me and Google Street View, largely because many London boroughs have been experimenting a lot recently with Low Traffic Neighbourhoods (LTNs) and modal filters (e.g. two way for bikes/one way for cars). But I did run a TSP solver (RouteXL) on 3 of the stages and in 2 cases it did find a slightly shorter ordering of the legs, within the stage. So I would probably use a TSP solver more for a future iteration of the challenge.

The three route/team files were saved in British National Grid (EPSG27700) GeoJSONs (technically not allowed by the spec) so I could get proper metre distances ($length) auto-updated into a column, for each stage, during planning. The stages had a number column, and were numbered sequentially. Having a number column results in LineStrings in the GeoJSONs and GPX routes/routepoints rather than single MultiLineStrings and GPX tracks/trackpoints. They were then saved as WGS84 GPX files. I (mis-)used a very limited set of column names (name, number, src, desc, cmt), due to the restrictions with the GPX specification – I didn’t want to use GPX extensions.

It was important to have three separate GPX files so that each team would need to load in just a single file to their navigation device and not see docking stations/routes from other teams). But it did make preparations a bit harder for the online map.

The docking stations were imported in via a TSV file, then saved as GPX waypoints (column names again restricted to src, desc, name, and cmt), and the relevant ones were manually appended to the GPX team files. The GeoJSONs were retained as my master editing files, as QGIS cannot easily edit GPX files due to them containing multiple geometry types.

I would certainly like to try a more automated approach to the routing. It did take a substantial amount of time – probably two evenings for each of the three routes, and a further evening for each route to enumerate the docking stations, fine-tune the routes and reorder any sliced up GeoJSON LineString segments (part-stages) back into the correct sequence. The reordering was needed as QGIS would incorrectly reorder parts of the route that crossed over itself, when it was sliced up.

But an automated approach would require a method that deals with docking stations that are just 10m down a no-entry street (so you’d just walk it), which is hard. Currently they are represented as a point defined by TfL through their API (and separately in OpenStreetMap) which may be the location of the “totem pole” kiosk but not the docking points themselves. In routing or GIS systems, the docking station needs to be represented as an area (within which you would walk the bikes) plus a (multi-)line (representing the line of dock points – some of these are quite long – some have significant gaps, and sometimes they are split on either side of a road). Potentially, the point representing a docking station really needs to be an area, and that area can extend up to the nearby road junction to deal with the one-way issue.

Future Improvements

In terms of the general design, a few things could be changed for a future challenge (some of these I mentioned in my previous blog post):

  • Ensuring that participants are well away from the finish at around the 60-80% stage, so that they are less likely to bail at that difficult time of the day, because the remainder of the challenge is then a kind of “run in” to the finish, rather than routing them away at a late stage.
  • When participants pass by another docking station twice, they should visit it on the first occasion, not the second time. (An exception is when it is on the wrong side of a dual carriageway, particularly one with a median barrier). Otherwise there is a danger of it being missed on the return.
  • Build specific meal stops in.
  • Maximum of 200 docking stations/10 hours per team.

The Web Map

By comparison, building the web map was straightforward, probably just one evening’s work to build the map page itself as a basic OpenLayers map reading in GPX files and with simple browser-based geolocation, and one further evening to build a “team” version of the map that allowed ticking off the stations, the action being stored in a database, and a time string echoed back to the web map (and other viewers, on a Javascript timer) as confirmation. The database had two tables, a summary table with a row per docking station, and an action log which recorded the dock’s TfL ID, timestamp, event type and the submitter’s browser user agent string ($_SERVER[‘HTTP_USER_AGENT’]) in lieu of logins/IDs. It was fairly easy to assign a manually assign each user agent to team, post-event.

Each docking station ended up with 4 identifiers which feels a bit too many, but it kind of made sense:

  • an integer TfL ID (e.g. 761)
  • the TfL Name that appears on the totem pole (e.g. Gower Place, Bloomsbury)
  • a shortcode which was the sequence number and the initials of the first part of the TfL Name (e.g. 37.GP). There were some duplicates across the team. FIN.HS was a special shortcode for the finish for the two teams that didn’t have that as a docking station in their “zone”. One newly added docking station had “A” appended to the sequence number of the previous, rather than having to renumber everything.
  • a unique sequence code which was the team, stage and docking station order within that stage, (e.g. W02.15). This was used as a logical ordering of the file and to help with assigning each docking station to its stage on the online map.

I also listed an “actual sequence” post-event ordering, e.g. W038, in the final results file.

I could have used the sequence code on the map but felt the shortcode was the most useful concise way of identifying each station to the team as they approached it, and hopefully the simple number would result in any missing out being spotted quickly.

I built a special “diff” webpage that compares our docks file with the live data (via BikeShareMap) every 2 minutes and this alerted us of any new, closed or zero-capacity docking stations, plus a list of full ones. There was one that opened a few days before, but none on the day, thankfully!

Future Improvements

I do think that using fewer intermediate routing points on each leg would be better and would allow for turn-by-turn satnav directions. Having said that, having street names called out is of limited use as they are often hard to spot on the ground, so the breadcrumb trail approach we used worked well.

We had paper maps (just screenshots of the website) as a backup. I never used them, and I think Team South used the website. Team West used them exclusively, with a separate person using the website to tick off.

I would have liked to have had a single source of docking station locations. In the end, they were:

  1. on TfL’s API, which is fed through to a CSV on BikeShareMap every two minutes,
  2. on a CSV file on Github,
  3. as GPX waypoints appended to each team’s GPX routes file, and
  4. in my database for recording times on the ATDMap website.

1 and 2 were automatically compared (see above), 2 could be added to QGIS to compare and generate GPX for 3, and also imported into the database table (4) but this would all be manual steps.

Links

Website map with the timings: https://misc.oomap.co.uk/atdmap/

Route GPX files and timings CSV: https://github.com/oobrien/allthedocks

Strava link (Team East): https://www.strava.com/activities/7908548122

Categories
Bike Share London

All the Docks: How it Went

On Monday I spent a lot of time (over 13 hours) cycling between 268 docking stations in London. It was for the All the Docks challenge, as part of Team East, with Joe (Be.EV CCO, and ex-ofo) and Jeyda (fettle CEO). There was also an all-stars Team West and Team South (including Voi, TIER, Zwings, and CoMoUK people – see this blog post for the announcement), and, across the three teams, we aimed to visit all the docking stations in London in a day.

Black = done. Green = not done. From the web map.

Team East: By the numbers

  • Three challengers: two on Santander Cycles (one docking at every point) and one on their own bike with navigation mount.
  • Started at 08:51, after getting breakfast nearby.
  • Two stops for food (at 13:30 and 20:15) plus a shorter stop to buy snacks (at 16:30).
  • Three lifts (which weren’t big enough for three bikes!)
  • Finished at 22:21 – 13.5 hours later
  • GPS says 119km although it added a lot 0f noise around Canary Wharf and a few other places, so I think the actual distance was more like ~113km.
  • 268 docks visited (the 266 assigned to Team East, plus the common finish docking station, plus a short bonus leg to the docking station outside the finish pub).
  • This works out as visiting a docking station, on average, almost exactly every 3 minutes, for 13.5 hours.
Team East’s actual route, on Strava.

What went wrong

  • It did take a bit longer than predicted. The target time had been 12 hours (11.5 hours + 30 minutes in breaks) and our average moving speed of 11.9kph was quite close to the 12.5kph in a prediction algorithm I put together. The two hour difference was due to food stops and comfort breaks (75 minutes in total), along with that 0.6kph speed difference (30 minutes extra) and the three legs we I had to jog (15 minutes). Our dock/undock speed got pretty good after Joe (who did 80% of the docks/undocks) got into a rhythm.
  • My personal bike (which I had planned to ride as a support to the team leader on the bikeshare bike, to do the navigation) had a flat tyre right at the start, which meant I had to hop on a Santander Cycles bike for the entire route. I had a big freak-out when I discovered this (no bike shops in Westfield Stratford City, challenge starting in half an hour) but it was OK in the end – I bought a £20 monthly membership in the app, on the spot, and the ride was more comfortable than I expected, but it did mean I needed to keep fishing my phone in and out of pockets at every docking station.
  • I also twice forgot to dock at least once an hour, twice, so got two £1.65 overage charges).
  • A result of my phone (with map) not being mounted on my bike, was I was constantly pocket-tapping the team version of the map as I kept grabbing my phone. This mean I kept ticking off other teams’ docking stations by mistake, particularly Team West’s list. The team version needed a UX tweak so the checkboxes’ labels were not tickable, or have separate tick-pages for each team.
  • The only significant routing error was at Import Dock in Canary Wharf (no regular Google Street View allowed there, so I couldn’t see in advance) where we ended up at road level, but the docking station was below us, at water level. Taking the bikes down an escalator in the new Crossrail/Elizabeth line station, got us to where we wanted to be.
  • Proper food stops need to be built in to the schedule, rather than hoping we accrue time and then spend it when we need it. We got hungry in places were there weren’t any quick eateries.
  • Three legs had to be jogged by some rather than cycled by all, due to infrastructure problems, although we still docked or undocked at each. At the first one, both Joe’s keys stopped operating and the dock was full so I couldn’t dock (with my third account) either. So I cycled to the next docking station, docked, ran back and undocked. A later problem dock wouldn’t release any bikes so I handed mine over and jogged to the next station to get another one. Finally, three from the end, the terminal disconnected after docking successfully, so I ran back to the previous one and went from there to the penultimate one.
  • One or both of our pair of keys got temporarily blocked several times. With one blocked, using the other, single key resulted in a mandatory 30-second delay before you are allowed to start another journey. Each time, a call to Santander Cycles support fixed the blocked key quickly. Santander Cycles does have a responsive and effective telephone support operation.
  • One docking station appeared to have been vandalised, with the “slot” on most docks crushed so that the bike couldn’t be docked. Eventually we managed to find one where we could squeeze it in.
  • Routing people near the finish, then up a hill and away, 10 hours in to the challenge, is demotivating, and coupled with the late time, I think this is what made Team West’s decision for them. A long, clear run into the finish line without big loops away, is preferable! In general, my design for West and East was a long wiggly route up and down, towards the finish, from the outermost parts of the network. By contrast, Team South went near the finish quite early on, before a long tour out to Putney, finally coming back along the river, back into town. I think this latter overall shape of the route probably is better for keeping people going to the end.
  • A few of awkward wrong-side-of-road docking stations on dual carriageways had to be visited, although generally with traffic lights, we got across OK. The worst link was a short section of The Highway followed by a right turn. This is a horrible road, and the others in Team East took the pavement instead (but were further encumbered by barriers left up from the London Marathon the day before). In retrospect, a walk-bikes route back across a new private development’s plaza would have been better.
  • A few roadworks made getting to some docking stations tricky. In the end, Team East had four blocked links – resurfacing by the Orbit sculpture in the Queen Elizabeth Olympic Park (where we just cycled through the construction site), park re-modelling in Shoreditch Park (which necessitated using park paths to get around it), Angel Street was closed for building construction (so we went through Postman’s Park instead) and finally St Bride’s Street was completely blocked for resurfacing, but the Poppin’s Court tiny alley diversion was a lot of fun.
  • The low point was at around 7pm, as the sun set, calculations suggested all three teams were well behind a nominal 9pm finish, and it looked like we would have to bail to make it to the pub. There was also some concern about what it would be like doing this kind of frantic point-to-point riding at night in London traffic, with tired legs, although in the end the traffic levels died down quickly after rush-hour. We also hadn’t had dinner and a proposed food stop at Angel was still 90 minutes away. A conference call between teams was held and a final decision at 9pm would be taken.
  • We approached the Somers Town Bridge at around its historic 9pm closing time (not sure if it actually does still close) so decided to take a long diversion around.
  • In the end, just after 9pm, we passed by our team lead’s home (25 from the end) and, with one eye on a very early start the following day, he opted to stop there. Team West had already quit and were arriving at the pub. Team South decided to double down and keep going. Their final stage along the spectacular Embankment at night, with views across the Thames, may have helped with their decision! We carried on for a final section around King’s Cross and, in the end, quite quickly down to the finish at LSE.

What went well

  • By and large my manual routes worked pretty well. For Team East, there were only a couple of banned turns and one wrong-way street encountered, easily fixable on-the-fly. The teams were pretty happy with my routes, which is good!
  • Careful planning tried to minimise the number of docking stations on the other side of busy roads, even if this slightly lengthened the route.
  • I was pleased I could include some of London’s best cycle infrastructure without lengthening the routes. The Olympic Park, Victoria Park, Regent’s Park, Hyde Park, Kensington Gardens, Lower Thames Street and Victoria Embankment (CS3). It was nice, on the day, to unexpectedly discover some of London’s newer protected cycling infrastructure on roads I knew well from pre-protected days.
  • After a while, we honed our docking/undocking technique and Joe got it down to around 15 seconds. Every 10 seconds saved per dock is 45 minutes saved on the challenge as a whole.
  • Considering the amount of docking/undocking operations we did, we had very few failed locks/unlocks or disconnected terminals.
  • My gadget batteries worked out OK. My old Garmin GPS wristwatch lasted 9.5 hours (albeit with no HR or Bluetooth), and then the last bit of route recording was done directly on my phone using Strava in the background. I only used GPS on my phone sparingly, to occasionally locate myself on the web page, but after 11.5 hours my phone’s battery had got down from 95% to 3% so I kept it plugged into a power bank on a cable, for the remainder, and it was fine. Jeyda’s Wahoo’s battery was absolutely fine throughout.
  • We did visit all 268 docking stations, even if it took us nearly two hours longer than planned.
  • We all stayed in good spirits as a team, and generally stuck together, although we did split up a bit near the end as different people drove forward to keep the pace going.
  • I thought we might need an operations person at a desk, checking for changes, handling social media and directing/motivating teams, but actually it worked fine with everyone on a bike.
  • We crossed the finish feeling fine – it’s the day after that I felt shattered.

Notes for a next time

  • General consensus in the pub was that having four teams (N, E, S, W) doing around 200 docking stations each, would be more fun and would allow more pub time, food time etc. Team West ended their challenge after around 200 docking stations when it was clear they would struggle to get to the pub before closing time if they continued (and as they had to loop away from near finish at that point). Team South made it just after last orders so Team West bought a round for them in advance. But a decent length social after such an exhausting day is important.
  • Finishing at the docking station outside the pub would have been better (I had decided against it because the distances across the three teams wouldn’t have matched as well).
  • Hopping on and off the bike for each dock gets tiring. Particularly as so many of the docking stations are on pavements and facing away from the road, resulting in many kerb hops, jolts and awkward manoeuvres. Possibly alternating the docking between two leads would make this better?
  • You definitely need one person to have a bike-mounted smartphone or navigation device (Jeyda’s Wahoo device worked pretty well) to do efficient navigation on a mounted stand rather than in/out of pocket.
  • Having two keys (on two accounts) is essential. As well as cutting down the dock/undock time, it can deal with full docking stations.
  • Santander Cycles finally launched electric bikes into their fleet, a few days after our challenge. These would be good for support riders, if too expensive for the lead rider (£1 surcharge per leg!)
  • I/we would definitely invite people to accompany us for a stage or a few legs. We did have Ilma from Fettle along for the City of London legs which was motivating (and she filmed a mini-movie/montage of us)
  • I’m glad we missed the morning rush-hour and the evening rush-hour while we were in the City was pretty intense too.
  • Some routing tweaks would be good. See a future blog post here for some technical details on how it was routed and how it could be made better.
  • Finally, I think the mapping/recording could be automated more. I liked my live-updating map, it was the result of a few evening’s simple Javascript coding, but there’s definitely more that I could do – leaderboards, current location pin, ETAs etc.

One note on helmets – normally I would always wear a helmet on my own bike, but not on bikeshare bikes – we shouldn’t be encouraging it for bikeshare bikes as it significantly reduces their utility and appeal for spontaneous journeys. However – I’m glad I did wear one, because we were on the bikes for 12+ hours, occasionally taking some quite aggressive manoeuvres to get across to the other sides of streets. We had no incidents or even any beeps from drivers, but one person in one of the other teams got bumped by a van. You do feel pretty secure on a Santander Cycle even without a helmet, as they are 25kg, feel incredibly sturdy, and you can never go that fast on them. But for this kind of challenge, hazards were definitely higher than normal and so the extra security of a helmet was welcome.

The Pashley-made bikes (bike numbers starting with 5) make up around 20-30% of the fleet and are definitely better than the older bikes still available, as they are newer. They are slightly lighter, have better lights, a more solid seat adjustment mechanism, and generally just feel nicer. We generally opted for those bikes, and typically stayed on the same bike for hours at a time.

I’ll have one more blog post about the challenge soon, some technical notes about how I put together the routes and some of the issues I faced doing so.

Links

Website map with the timings: https://misc.oomap.co.uk/atdmap/

Route GPX files and timings CSV: https://github.com/oobrien/allthedocks

Some photos courtesy of Jeyda and Joe. Background mapping © OpenStreetMap contributors.

Some tricky legs in bow. East India Dock (38.EID here) is in a particularly tricky location.
Categories
Bike Share London

All the Docks

[Update: How it went]

On Monday I will be attempting to visit every Santander Cycles docking station in east London by bike, starting at 9am outside the velodrome in the Lea Valley VeloPark (the “Pringle” from the London 2012 Olympics), cycling over 70 miles and hopefully finishing sometime that evening close to the London Transport Museum in the centre of the city.

It’s the result of an idea by Stephen Bee (of Zwings, an e-scootershare company), Joe Seal-Driver (a mobility expert who formerly ran the ofo bikeshare in London) and Matthew Clark (Chair of CoMoUK, the UK’s bikeshare industry group). They have assembled three teams of three people – the teams will leave east, west and south London at the same time on Monday, each team travelling as a group and docking one Santander Cycles bike at each docking station in the east, south of west part of the network. That’s around 263 docking stations per team – or one every 2-3 minutes, as the plan is, 12 hours later, for everyone to meet on Aldwych.

Why are we doing this? Because it is there to be done, and to see if it is possible to do – perhaps with an eye to a possible single continuous round in the future.

How? Each team will have a lead rider, who has to dock and undock a Santander Cycles bike at every intermediate station, plus two supports on their own bikes (or other hire bikes) – one to navigate and one to tick off the list and update everyone else. TfL was due to launch some pedelecs (electric bikes) into the fleet in September – this got delayed, but if they do appear quietly on Monday, it will be a welcome boost.

The Routes

I’ve created a suggested route for each team – have a look – and the markers should gradually turn green on the day as the teams progress. Some of the teams may be marking progress a different way – but look out for live updates here from at least Team East – subject to battery life and other practicalities. The “official” record of each visit will be compiled by Santander Cycles operations, using their hiring transaction logs, after the event.

Tech considerations – we were hoping to be using routing apps. However – these have proven to be a bit of a challenge. Some have restrictions on the total numbers of waypoints/routepoints, and some insist on rerouting you the long way around… we are aiming to cycle as much of the route as possible, but there are short pavement sections and one-way roads when we’ll need to wheel bikes in one direction to or from certain docking stations. The only long walking section is through Holland Park. So, a more manual approach has been taken. A website with a pre-planned route, and paper backups of the map in case of failing smartphone batteries.

Another issue with routing applications is they aren’t up-to-date with the many one-way/two-way signage from the local authorities. Some areas have introduced Low Traffic Neighbourhoods, and some borough in particular are keen on having one-way roads allow two-ways by bike. Neither OpenStreetMap nor Google Maps is fully up to date with these changes.

There is also the issue of automatic routing between 260+ locations. This is a so-called “Travelling Salesman Problem (TSP)” (the best route between multiple points) which can only be done automatically with heuristics. So, ultimately, the routing has been done manually. Local knowledge, Google Street View and OpenStreetMap have all been useful, plus I’ve visited a couple of links to check their current state. I’ve split each of the three routes into 12 section, each approximately 10km or 1 hour. I did then use an online TSP engine – RouteXL – on some of these sections to see if it could beat my “manual” route planning, and in a couple of places it did spot something clever. But I think my three routes – each around 116km long – will be pretty close to the optimum routes.

The second section “Bow” for Team East.

My preparation is limited – I haven’t even hired one of the bikes for many years – but my commute to work by bike is over an hour each way, which helps. I will also be a doing couple of hours cycling to help at the London Marathon on Sunday, and also (albeit not quite the same type of exercise) I waited 9 hours in The Queue earlier in September. Technical preparation has included buying a Santander Cycles monthly membership, a phone mount, some protein bars and a spare battery pack! Stephen and Joe have also done a test hour. Their rate then suggests it is possible but will be a considerable challenge to have completed our third by the evening. Luck will need to be on our side.

All the Docks should be responsible for 2-3% of all hires on Santander Cycles on Monday.

If all goes to plan, Team East will be heading through Canary Wharf just after noon, through the City of London just before the evening rush-hour, and King’s Cross at around 7:30pm. We haven’t quite decided how/where/when we will be stopping for food – it might have to be on-the-go snacking.

You can view the map here and download GPX files containing the routes and waypoints, from GitHub. Here’s Stephen’s introduction to the project.

On Monday, keep an eye out on Twitter – at @allthedocks and also my own account (@oobr).

& here’s what happened.

Categories
CDRC Geodemographics

Introducing Mapmaker

I’ve been based at the ESRC Consumer Data Research Centre, a multi-university (UCL/Liverpool/Leeds/Oxford) lab focused on research and provision of specialist UK consumer datasets, since 2015. One of my first outputs was to adapt DataShine, which I’d created in 2013 as part of a previous UCL project, to produce CDRC Maps – to map some of the open datasets we held, and aggregates of some of the more interesting socioeconomic datasets that we produced from the controlled collections.

CDRC Maps is an OpenLayers-based “slippy” (pan/zoomable) map website consisting of pre-rendered raster tiles of choropleth maps of consumer metrics, layered under another raster “context” layer containing roads and labels, and a mask which results in only building blocks being coloured by the underlying choropleth. It served its purpose of showing impactful, pretty and effective maps of our UK socioeconomic datasets, but being a raster based map, with billions of tiles sitting on one of our old servers, it has been showing its age for a while.

The modern web mapping toolstack has moved on, with the rise of powerful web browsers with fast vector rendering, responsive design for smartphones and tablets, and comprehensive GUI frameworks that elevate regular Javascript. CDRC’s requirements have evolved too, with a desire for map visualisation that includes downloadable snapshots, basic analytical functions and filters, rather than the simple view-only concept of CDRC Maps, and a need to embed the map in stories and dataset records, rather than only sitting standalone.

CDRC Maps has also long been hosted directly at UCL, on a local development server. CDRC is a data research centre not a technology centre and there is a desire for use to our server infrastructure for data primarily. The website has long been the most popular public website for CDRC and also is prone to usage spikes due to mass media often finding that maps are a quick way to illustrate a story – or be the story – compared with raw datasets that are less immediately accessible with media deadlines. It was clear that an external host for the sites itself, and ideally the data that powers the site, would be preferable.

To address this and bring CDRC Maps up to date with the new data platform, the centre commissioned Carto and Geolytix to produce CDRC Mapmaker during late 2020. The developers created a Node.js based website that uses the Vue templating framework. Mapbox GL JS 1 is used for the map controls/canvas and the vector tile rendering. The map framework has recently become non-open but there is an open fork, MapLibre, which we will take a look at in due course. The development toolchain has also been brought up to date with industry practice, with proper source code management, continuous integration, rapid development/testing on localhost, and deployment through GitHub.

Map config is in Javascript but this component is separated from the templating Vue/Javascript allowing configuration and setup of new maps to be discrete from the main code itself.

Data is completely separated from the code and there is no server-side processing element for the code. (We do also use an external service, Google Analytics, for our stats). The data is hosted on Carto’s data platform, where a number of datasets are loaded, and also a postcode lookup table. Carto is in fact built on PostgreSQL/PostGIS and provides a management GUI to allow these to be managed independently of the map code.

While the complete (albiet minified) code, config, fonts, images and stylesheets are less than 4MB, the datasets themselves use approximately 7GB of space on the Carto servers. Each geography used (MSOA, LSOA, OA, local authority) has four spatial data files, representing the unmasked choropleth along with three levels of clipping – urban extent (towns/cities), detailed urban (village level) and individual building blocks.

The application is structured around presenting two types of maps – metric maps (which show a various continuous variables associated with a particular dataset, sliced into groups) and classification maps which categorise areas into a single value (sometimes with a hierarchy of levels) and generally include a pen portrait description of the category.

We were delivered six functioning maps and I have gradually worked on extending the codebase and GUI functionality to encompass the wider variety of maps that were on CDRC Maps and that are listed in CDRC Data. Quirks of each additional map have actually meant minor changes to the code in each case to accommodate them, but I am hopeful now that the codebase is broad enough to allow for additional maps to be added in the future with minimal effort.

For this first release of Mapmaker, there are around 30 maps, covering CDRC classifications such as Consumer Vulnerability and the Internet User Classification (IUC), CDRC metric products such as Access to Healthy Assets and Hazards (AHAH) and Residential Mobility (Churn) and some popular government datasets like the Index of Multiple Deprivation (IMD), VOA building ages and Ofcom broadband speeds/availability.

Users can filter maps based on one or more classification categories or on multiple metric value ranges, and a PDF report can be easily produced with a view of the current map, a key and accompanying text and direct link. Clicking many of the maps will not only present the metrics or portrait, but include statistics on proportions in the current administrative area or a custom drawn region. The user interface is deliberately simple with standard pan/zoom controls, map selector, postcode search and layer toggles – that’s it. Planned development in the short term will include an even simpler UI to allow for easily embedding the map in CDRC Data and other CDRC data-led outputs.

CDRC Maps is currently still available for the limited number of maps that show datasets not included on CDRC Data, and it does have the advantage of a pure raster display meaning that some of our controlled datasets which require limited dissemination can be included in this way – on CDRC Mapmaker we would be delivering the dataset to the user’s browser, which is not ideal. Our plan is to de-brand CDRC Maps to provide a home, outside of the core CDRC output, for these legacy maps, in the same way that we have a GitHub repository storing some of our older datasets no longer on our main sites. CDRC is now nearly 8 years old and as the centre’s focus has been refined, not all our older assets have remained central to its mission, but for research reproducibility and historic linking purposes, it is important to preserve these.

We hope CDRC Mapmaker forms a useful visualisation tool for some of CDRC’s many data assets, and its filtering and reporting functionality allow CDRC’s data to be viewed and used in new ways.

Categories
Bike Share Data Graphics

There are .9 Million Shared Bicycles in Beijing

Recently I become part of the editorial team at the Bike-Sharing World Map (this is a new version, not yet launched) which is the world’s only comprehensive map of bikeshare systems, listing the approximately 2000 active systems along with another 1000 that are either in planning or already closed.

The Bike-Sharing World Map was compiled by the late Russell Meddin over the last 12 years and has recorded the gradual evolution of the capabilities of bikesharing systems, with Europe and Asian systems dominating, followed by a huge rise in American systems – but the massive change over the last four years has been the rise of dockless bikeshare systems, powered by smartphone apps, replacing the expensive fixed-docking-station systems, often publically financed and typically one-per-city. Instead, dockless is often entirely privately financed and the major operators run systems across hundreds of cities, often in direct competition with each other.

China invented the dockless concept and made it a “boom” industry by being able to manufacture the bikes very quickly – the timing was also perfect, with Chinese citizens, having previously cycled everywhere and quickly seen their cityscapes convert to the motorcar – perhaps were looking for a return to a simpler, cheaper and perhaps now quicker form of transport. There certainly was an investor boom-and-bust, with many cities being totally overwhelmed in 2017 with dockless bikes. Photos of huge, brightly coloured dockless bicycle graveyards became popular. Almost none of the systems were making money though, and the industry rapidly consolidated – a number went bust or were bought in 2018, the trigger being a snowballing of users requesting deposit refunds.

More recently still, city authorities started to address the problem and many of the larger ones have now introduced operator assessment and the awarding of quotas of bike numbers based on this. This means that, on the assumption that operators obey the quota directives and also maintain the largest fleets they are allowed to, it is possible to calculate the approximate number of dockless bikes in each city and by extension across the world. The operators themselves don’t typically announce their fleet sizes, for commercial reasons, and generally don’t provide public APIs either, so this is typically the most effective way to understand the numbers. The authorities don’t always publish these quotas either, but China’s local press often conducts investigations into and their local journalists are occasionally allowed access into city operations centres where sharing bicycle fleets – amongst other transport assets, are monitored.

This graphic, from a QQ article, shows a screen in such a centre in Chengdu, on which are live statistics for dockless bikeshare – one of my Chinese-speaking colleagues at UCL translated it and this is the source that Bike-Sharing World Map is using for Chengdu:

Chengdu’s transport operations centre, showing their real-time view of the competing dockless bikeshare systems in the city and surrounding area. Photo © Red Star News.

It is possible to mine Mobike’s undocumented API for bike locations, although at the centre of the densest cities, even this exhaustive approach will miss many of the bikes. Here is a map showing a snapshot of 152,300 Mobike bikes available for rent – around 1/3rd of the estimated ~500,000 strong fleet in Shanghai, earlier this month (N.B. quirks with the China datum mean the locations don’t match perfectly with the underlying OpenStreetMap map):

Some of the Mobikes in Shanghai, superimposed on a misaligned OpenStreetMap map. In the central section, the regular grid pattern is an artifact of the technique, revealing that there are many more Mobikes in this region than are shown here.

Beijing’s totals peaked in September 2017 with 2.35 million dockless bikes. In 2018 a quota of 1.91 million bikes was introduced, more recently authorities have reduced this to 900,000. The Chinese “big 3” as of 2020 are all in the capital city – Mobike (morphing into Meituan Bikes having been bought by them), Hellobike (bought by Youon, the biggest operator of docked public systems in China) and Didi’s Qingju brand (Didi is China’s Uber, it bought the assets from Bluegogo when they went bust). There is also a residual ofo presence – the app remains live and there are bikes rentable though it – although they have been largely unmanaged for a while now, the company having been embroiled in a deposit refunds scandal.

Beijing is behind just Chengdu, and possibly Shanghai, in terms of total numbers of bikes.

The industry itself continues to innovate and organise itself, with the increasing pressure from city authorities combining with the need to properly start making money. Hellobike has been one of the most nimble. It has largely avoided the investor bloat and scandals of the others by concentrating on only its home market, China, and also initially concentrating on second-tier Chinese cities, where there is less likely to be competition from Mobike/ofo/Qingju. As it has grown, it is now moving into the biggest cities and taking on all comers.

Recently, Hellobike has started to roll-out dockless hubs, which are enforced by beacons which sweep the designated areas and interact with RFID chips on the bikes. The bikes’s wheel locks will nosily unlock if a user tries to lock and end their journey outside of them. Generally, this beacon approach is much more accurate and immediate than the traditional use of GPS (or the Chinese equivalent) to enforce geofences or understand where the free bikes are for the benefit of app units and redistributors. Other organisations in China are looking at combining the extensive public CCTV camera network in many cities with China’s AI advances and machine object-detection routines, to help authorities detect which bikes are parked where and when, to help with operator scoring for future quotas.

Bike-Sharing World Map currently estimates there are 9.1 million bikeshare bikes in the world, of which at least 8.6 million (over 94%) are in China – and most of these are dockless. We are still compiling and updating the China part of the map – and the actual number could be quite a lot higher (although not as high as in mid-2017 when it was believed there were 16 million dockless bikeshare bicycles in China (10 million ofos, 5 million Mobikes & 1 million Bluegogos). The fleets may have probably halved since then, but the story of bikeshare in the world is far from complete without up-to-date numbers from China.

Terminology note: China generally refers to dockless bikeshare bicycles as “shared bicycles” or “internet bicycles” while the older dock-based systems are generally called “public bicycles” reflecting their publically owned and specified status.

Categories
Bike Share London

Test Cycle: HumanForest

There’s a new bikeshare in London – HumanForest launched yesterday (Wednesday 24 June 2020) with 63 pedelec bicycles. They are planning on rolling out up to 200 bicycles in their Islington trial operation, before hopefully expanding to central London later this summer with up to 1000 in their fleet.

HumanForest’s technology platform and equipment provider is Wunder Mobility, based in Germany. This is the first UK system using these bicycles, so I was keen to try one out in the wild.

HumanForest’s bikes are painted dark green so are a little harder to spot than the late JUMP bikes, which were luminous red, and may or may not make a return under their new owners Lime soon, or the flureoscent yellow Freebikes. They are rather sleekly built, with the battery well integrated into the frame rather than bulging out of it:

The big selling point of the bikes is their electric capabilities and price point – these are pedelec bikes with a top speed of 15mph (you can pedal faster than that but you won’t have any electric assistance). The bikes are free for your first 20 minutes each day, then 12p/minute thereafter. This is broadly comparable with Freebike’s price offering, and much cheaper than Lime’s £1/start+15p/minute pricing. (London’s Santander Cycles did demo a pedelec version last year but have yet to announce a launch date or pricing.)

HumanForest looks extremely affordable, I presume their plan is that the average user will take their 20 minute free journey to get into town, and then HumanForest will collect £2.40 for the 20 minute equivalent return journey. They should also, if they are able to expand quickly into adjacent boroughs, take advantage of the current huge surge in leisure cycling in London. Such users will typically be much less price sensitive and also likely to use the bikes for a longer time.

The HumanForest bikes ride nicely – as you would hope for brand new. European-designed bikes – with more of a power kick than Lime and Freebike, but not quite as much as JUMP offered. As ever, it’s nice to get across junctions from a standing start quickly, and to get up hills with little effort, but for longer journeys, the only very marginal battery boost above ~10mph will be frustrating.

I had a couple of technical issues – the first bike I tried refused to unlock with a “Get closer to the vehicle” message on my phone app despite being right beside the bike. The second worked fine, but had an issue with the adjustable saddle height clamp – it was a little loose, so I kept sliding down. The seat-posts do however come with a nice indication of which setting is needed, based on your own height (in cm):

Overall though, the build quality is good, the bike feels solid to use and has some nice design elements, including the saddle, which has a nice two-tone colour and a flat top, and a handlebar twist-bell.

In a sign of the times, the baskets are all fitted with a cable lock to which is attached hand sanitizer, and the HumanForest app asks you to check you have applied it before hiring:

HumanForest asks users to take a photo of the bicycle once parked at the end of the journey, this is good practice as it will help users “self police” their parking locations. I parked beside another HumanForest bike which was parked across the pavement on an inside bend – not great:

I moved it to the side of the pavement, but this off the weediest alarm I had ever heard. After three rounds of electric buzzing, all was silent again!

As always with bikeshare in London, HumanForest will live or die based on the vandalism and wear-and-tear rates, and how the operation teams deals with these. It is a small fleet, in one London borough, but there is definitely space for a third pedelec fleet in London, so the best of luck to HumanForest and hopefully we’ll see them expand far and wide.

Categories
Bike Share London

Lockdown and Bikeshare

I earlier this week spoke at a Cycling@Tea-Time seminar, on the impact of lockdown on bikeshare, looking at London, the UK, and the world in general. The talk was based on some very preliminary crunching through some CDRC datasets to see how usage has changed, both in volume and time-of-day, for how people are using bikeshare systems.

I also offered some thoughts on bikeshare’s role in a post-lockdown world, where social distancing concerns about public transport may result in a spike in bikeshare usage but also more congestion.

The talk also paid tribute to Russell Meddin, the “godfather” of bikeshare, who sadly passed away last month.

I met up with Russell regularly over the last 10 years to talk bikeshare, and we would typically spend hours over a hot chocolate, catching up on what was happening in the industry, in the USA, the UK and elsewhere. Russell also was the driving force behind many of the changes to Bike Share Map I made over the years. He will be greatly missed.

Amongst many other societal contributions, Russell spent the last 11 years curating the Bike-Sharing World Map, a huge Google Maps site showing the latest news and status of around 2100 active bikeshare systems around the world, along with notes on the 400 proposed and 500 closed systems.

There is no other resource that comprehensively maps bikeshare throughout the world, including my own Bike Share Map that only shows the larger systems with live data. I am sure I am not alone in wanting this resource to live on and continue to be the definitive source of bikeshare’s world “footprint” and would like to explore some ideas about this could happen.

My talk only touched about the impact of lockdown and there is much data that needs to be crunched so I am hoping to spend further time on looking at this shortly.

My presentation:

Categories
London OpenLayers

London’s Poverty Profile 2020

Trust for London (TFL), a charity and themselves a major funder of charitable projects in London to address poverty and inequality, has this week launched the London Poverty Profile (LPP) 2020. There is an updated data-driven website with over 100 different indicators of poverty and inequality, compiled by WPI Economics, along with a PDF report snapshotting the indicators as at early 2020.

With the ongoing Covid-19 pandemic and resulting lockdown likely to cause a significant impact on London’s social economics and community wellbeing throughout this year and going forward, the LPP 2020, which was compiled with pre-Covid-19 data, acts as an important baseline, looking at London’s poverty and inequality profile towards the beginning of the year.

As one of the world’s most international and wealthy cities, it is easy to overlook that London also has areas of extreme poverty and deprivation. The luxury apartments of Knightsbridge and Chelsea are often in the headlines but less obvious are the endemic poverty that has persisted in areas such as much of Newham borough in east London, parts of Tower Hamlets close to the glittering lights of Canary Wharf, or even North Kensington in the west. The recent political focus may have been on “rebalancing the North” (of England) away from London as a whole, but treating London as a single unit of the wealthy South is over-simplistic. The London Poverty Profile acts to ensure that all of London is understood and its challenges, when considered at detail, are not overlooked.

The Consumer Data Research Centre (CDRC)’s London hub has been involved with the LPP 2020 and will continue to work with Trust for London going forward. Our role has been two-fold. First of all, I was seconded to Trust for London periodically over the last year to overhaul the mapping system that appears on the LPP webpages. Previously using a heavily simplified representation of London boroughs, it has now been rewritten to use OpenLayers 6 (in Javascript ES6 form) which is integrated with the Content Management System used to publish the data and indicators by WPI and TFL. Secondly, CDRC will be contributing and mapping “experimental” datasets, from time to time. These will utilise CDRC’s own datasets and its ability to cross-tabulate datasets from other source, open and non-open, to provide further innovative insight into spatial aspects of poverty and inequality across the capital’s 9 million population.

Geographies that can now be used extend beyond the London boroughs, to include LSOAs, MSOAs and (shortly) Wards. This allows more detailed maps. Poverty does not stop at London borough boundaries (although there are a number of cases where there is a big change, for example Redbridge to Waltham Forest), and some boroughs, such as Haringey, are well known for having a considerable east-west split, with a major railway line acting as a physical and socioeconomic split between wealthy Highgate and Muswell Hill to the west, and poorer Wood Green and Tottenham to the east.

Sometimes, other political boundaries do show a step-change in deprivation, as seen here between Ilford South and Barking constituencies (which is also a Redbridge/Barking & Dagenham borough boundary):

In addition, the maps use a selection of ColorBrewer colour ramps to ensure that spatial trends in the datasets are easily seen. ColorBrewer is widely used in the digital cartography field to ensure visually fair and effective use of colour in showing quantitative data.

All maps include a postcode search widget, and ones showing data at a final resolution than London boroughs include a toggle between borough outlines and Westminster political constituencies. Maps are zoomable and pannable, and PDFs and images can be quickly produced.

For launch, the new maps on London Poverty Profile include:

In addition, a number of existing maps on the LPP have been brought over to the new system, and other datasets, typically those split by borough and with some slight of spatial autocorrelation, will also gain maps in due course.

We hope to introduce additional experimental datasets, and corresponding maps, to the London Poverty Profile, on an approximately monthly basis this summer. Possible examples, based on current maps on CDRC Maps, include mapping on access to broadband, rate of household composition turnover, and consumer vulnerability to marketing practises.

Understanding the spatial characteristics of London’s poverty, inequality and other social challenges, is vital, and our hope is that these maps will help inform and better navigate the data available.

Categories
Bike Share Conferences

Walking & Cycling Innovations

I was invited by organiser Landor LINKS to speak at the Walking and Cycling Conference which took place in Manchester last month. The conference included a good focus on bikeshare, and it was a good time for the UK-focused bikeshare industry to pause and take stock of a busy 2019. Three UK-focused bikeshare operators – Freebike, Beryl and Nextbike UK – were present, and it was good to chat with the respective teams and find out how the year had gone and their thoughts for the following year.

MicroMAAS and the UK

I presented on “MicroMAAS” data – first defining MicroMAAS as mobility share services that you can pick up (i.e. bikeshare and escootershare) and outlining the different types of bikeshare popularly available:

I then talked about the “why” of open/standardised data in the sector:

and the “where” – Europe is well behind the US here:

I mentioned CDRC’s excellent and huge collection of largely dock-based bikeshare dock data, available through the CDRC Data Service:

The last part of my talk touched on managing such systems, including key players in analytics platforms:

I also outlined and bemoaned and the (little) progress towards fourth generation bikeshare systems where payment is fully integrated into how other transport modes are paid for, rather than being app-siloed. Right now we are in a commercial battle, with providers looking to integrate vertically rather than horizontally – largely due to the weak management of the sector by local authorities here in the UK – who seem happy to take money and less happy to regulate the sector properly and effectively so that MicroMAAS will actually be a net benefit to the wider UK streetscene:

Beryl Update

Of the other talks, I was particularly interested in Beryl’s – especially they included some data on their first half-year of operations. UK bikeshare usage data is still rather sparse so it was good to see these numbers in a public presentation. The London operation is very small – they quickly moved out of Enfield after the system was heavily abused and little used there – and the City of London “square mile” only has limited need for journeys within it:

Slide © Beryl Bikes (from their presentation)

London’s on-street available fleet is typically around 144 (and around 100 currently) rather than the 400 mentioned here. With approx 5 months between launch in July and the early December presentation, this suggests around 30 rides a day or just 0.2 rides/bike/day (as a rule of thumb, for a non-electric system, over 1 is just about OK, over 2 is good and over 3 is really good – for electric you need 2+ due to the extra costs of the bikes and retrieving them to charge). As you can’t really do a point-to-point journey in the City that is longer than a mile and a bit, this would explain the average journey being just over a mile – half that of Bournemouth.

This may improve with their extension to Hackney that is happening now – so far they have moved into Shoreditch and Hoxton in the south of the borough, but in time if they move into parts unserved by Santander Cycles then they become the cheap, manual alternative to Uber’s JUMP here.

However their numbers for Bournemouth and Hereford – the latter helped by a generous public subsidy – are much more positive. Bournemouth launched in mid-June and averages around 300 bikes (although 140 bikes currently) – so 1 t/b/d, and Hereford launched at the end of July, averaging around 160, or 1.3 t/b/d. Bournemouth is suffering from theft though.

JUMP

I’m also hearing good numbers coming out of Uber’s JUMP system in London – so it is possible for commercially-led bikeshare systems to work here in the UK, it just takes a lot of experimentation, effort and investment.

See also Bikesharp, which is my blog exclusively dedicated to the minutiae of the UK bikeshare market.

Categories
Bike Share London

Consolidating Dockless Cycles in London

This is a draft piece of commentary and I will evolve it in response to any feedback and further analysis I am performing.

A bylaw is being drafted between the 32 London borough councils (and the City of London) to introduce a coordinated approach to managing dockless micromobility sharing, such as bikeshare and (should future national legislation permit it) escootershare, across London.

Currently, each council sets its own policy with regards to dockless cycle operators in their area, making running a pan-London system painful for operators, and resulting in a number of inconsistencies. The matter is further complicated by the parking of a bicycle on a pavement not actually being illegal currently, as long as it is not obstructive, and by “red route” roads in London – the larger roads, which are generally managed by Transport for London and not the councils – and which in some cases have good segregated cycle lanes installed by the transport authority which is more focused on getting people travelling efficiently throughout London, rather than entirely within small borough boundaries – some councils tend not to consider than someone would ever want to leave the borough, as evidenced by mandating max/minimum bike numbers on operators who then watch as their users head, like everyone else, in the direction of the City/Westminster/Canary Wharf, in the morning.

At the same time, there are currently 7 operators in central London (3 free-floating, 2 hub-based and 2 dock-based), a mix of bike types (3 electric systems and 4 manual ones) and yet, while some areas have 5 operators, a third of boroughs have none.

The bylaw will ask each council to outline its policy of where parking of dockless bicycles is allowed, the policy then applied consistently to all operators who want to be in that borough. This potentially could result in huge variations – some, like Islington, may be happy to allow parking whereever, as long as basic sensible parking considerations are taken into account. Some may designate only a small number of hubs, perhaps far away from their local commercial centres and bus/rail stations, where they are out of sight and with little impact, but not useful for the great majority of people. And some may take a balanced approach, like the City of London which has designated (and marked) a number of hubs throughout its area.

My personal view is that one size does not fit all, and in fact there are five distinct categories of publically accessible “realm” in London which all need different approaches to how dockless micromobility should be parked on them.

  • For outer London boroughs (Z5-6), with low population density, the designation of hubs is I think vital for a bikesharing service to ever be viable. But these should be recommended rather than mandated. There should not be any specified exclusion areas, instead, users should follow “common sense” principles.
  • For inner London boroughs (Z3-4) where cycling to the centre of London is viable – on a pedelec at least – it is important to allow the operators to position their bikes where they feel they can provide a service that is viable for them. Councils should publish geo-files containing exclusion areas, such as the busiest pavements in their urban centres, while still allowing the parking of free-floating bicycles close enough to them. If an inner borough is very keen on having designated hubs, then they should either exist on an optional basis (like for the outer boroughs) or at the density of the city centre (i.e. with no part of the borough more than a ~400m walk from one). Hubs must be outlined in brightly coloured paint and with a generic caption like “dockless parking”, and ideally with a metal sign to increase visibility. As below, hoops/fences are an alternative.
  • For the city centres (the area covered by Santander Cycles, roughly Z1-2) free-floating will not work – there just isn’t enough pavement space. A high density of hubs should be made available – these should – as a minimum – include the ends of all the existing Santander Cycles docking stations, as these have a good density throughout the city centres and almost always have space at either end for at least 3 or 4 dockless bicycles – parked at right angles to the Santander Cycles. I regularly see them being used in this way already. Other hubs should either be as rectangles taped/painted on the ground, or designated fences, cycle hoops and other structures to which the bicycles can be secured (using cable locks present in the JUMP system – other operators would need to adapt their bikes to have cable locks).
  • Royal parks (and other urban parks) should adopt the city centres approach of having mandated docking areas within each park (although not at city centre density) – a suitable number around the perimeter of each park, but also one at all their park car parks. If people can drive into a Royal Park car park, why shouldn’t they also be allowed to start or finish a bicycle journey there?
  • Canal towpaths (and the Thames path) are generally linear and cramped, and the adjacent water is always a tempting target for vandals, so bicycles should continue to be not be parked on these – although allowed to move along them. Generally, the nearest designated hub will only be a short distance away from the tow path. Similarly for railway stations and markets.
Building densityDocking station/hub density
Suburbia, Urban parksHubs, ~ max 500m walk.
Inner CityDockless.
Some hubs in retail/office areas.
City centres,
Railway stations
Existing docks (where present)
plus “infill” hubs, max ~300m walk.
Canal towpaths/
river walks/
highwalks
Not allowed.

Other thoughts:

  • Operators should pay a fully refundable deposit for each bike, to the body managing the bylaw, which should be refunded when the bike is withdrawn from operation. This would ensure that operators, to the best of their abilities, retrieve broken bikes and remove them from circulation. If an operation folded, then the deposit can be used by the councils to remove the bikes themselves.
  • Operators should not be charged by the councils (i.e. should not have to pay for permits to operate), except on a cost-incurred basis.
  • Operators must publish the live locations of their available bicycles (when they are not in active use or transport), regardless of whether they are in a hub or not, on a timely basis (e.g. updating every minute) as open data. A suggested specification would be GBFS.
  • Councils must publish the spot locations, names, geographical extents and capacities of their hubs (where designated) and their exclusion zones, as open data. A suggested specification would be GeoJSON. These should be published to a central location, e.g. the GLA Data Store, and kept up to date.
  • A standard way of reporting mis-parked bikes should be adopted, such as FixMyStreet.
  • Councils should have the right to fine operators for mis-parked bikes but only if they have been demonstrably not made an effort to retrieve a bike after it is reported to them by the council, that it is a legitimate report, and after a reasonable amount of time (at least 12 hours from the report being passed on), and on a per-issue basis. The level of the fine should be two-tier based on whether the bike is in an obstructive position or just in an excluded area.
  • Boroughs should fund the cost of marking hubs.
  • Hubs can be on both streets and pavements – if the former, they should be protected from errant car tyres by using “armadillos” or similar equipment.
  • If operators want to fund hubs, that’s OK, but there should not be operator-branded hubs.

Finally – London’s bikeshare operators are actually, generally, providing a good service now. We aren’t seeing the huge levels of complaints about poor parking which were seen when the larger Mobike, ofo and oBike operations were running. JUMP are reporting great usage rates, and the smaller hub-based operators (Freebike and Beryl) have tightly managed fleets. Even Mobike’s much reduced fleet seems to be operating in a less intrusive way, and although data on Lime is difficult to get, it too appears to be operating effectively, in terms of rides vs complaints.