Traffic Data Is Good for More than Just Streets, Sidewalks

Curated on Posted on by Stefaan Verhulst

Skip Descant at Government Technology: “The availability of highly detailed daily traffic data is clearly an invaluable resource for traffic planners, but it can also help officials overseeing natural lands or public works understand how to better manage those facilities.

The Natural Communities Coalition, a conservation nonprofit in southern California, began working with the traffic analysis firm StreetLight Data in early 2018 to study the impacts from the thousands of annual visitors to 22 parks and natural lands. StreetLight Data’s use of de-identified cellphone data held promise for the project, which will continue into early 2020.

“You start to see these increases,” Milan Mitrovich, science director for the Natural Communities Coalition, said of the uptick in visitor activity the data showed. “So being able to have this information, and share it with our executive committee… these folks, they’re seeing it for the first time.”…

Officials with the Natural Communities Coalition were able to use the StreetLight data to gain insights into patterns of use not only per day, but at different times of the day. The data also told researchers where visitors were traveling from, a detail park officials found “jaw-dropping.”

“What we were able to see is, these resources, these natural areas, cast an incredible net across southern California,” said Mitrovich, noting visitors come from not only Orange County, but Los Angeles, San Bernardino and San Diego counties as well, a region of more than 20 million residents.

The data also allows officials to predict traffic levels during certain parts of the week, times of day or even holidays….(More)”.

Stop the Open Data Bus, We Want to Get Off

Curated on Posted on by Stefaan Verhulst

Paper by Chris Culnane, Benjamin I. P. Rubinstein, and Vanessa Teague: “The subject of this report is the re-identification of individuals in the Myki public transport dataset released as part of the Melbourne Datathon 2018. We demonstrate the ease with which we were able to re-identify ourselves, our co-travellers, and complete strangers; our analysis raises concerns about the nature and granularity of the data released, in particular the ability to identify vulnerable or sensitive groups…..

This work highlights how a large number of passengers could be re-identified in the 2018 Myki data release, with detailed discussion of specific people. The implications of re-identification are potentially serious: ex-partners, one-time acquaintances, or other parties can determine places of home, work, times of travel, co-travelling patterns—presenting risk to vulnerable groups in particular…

In 2018 the Victorian Government released a large passenger centric transport dataset to a data science competition—the 2018 Melbourne Datathon. Access to the data was unrestricted, with a URL provided on the datathon’s website to download the complete dataset from an Amazon S3 Bucket. Over 190 teams continued to analyse the data through the 2 month competition period. The data consisted of touch on and touch off events for the Myki smart card ticketing system used throughout the state of Victoria, Australia. With such data, contestants would be able to apply retrospective analyses on an entire public transport system, explore suitability of predictive models, etc.

The Myki ticketing system is used across Victorian public transport: on trains, buses and trams. The dataset was a longitudinal dataset, consisting of touch on and touch off events from Week 27 in 2015 through to Week 26 in 2018. Each event contained a card identifier (cardId; not the actual card number), the card type, the time of the touch on or off, and various location information, for example a stop ID or route ID, along with other fields which we omit here for brevity. Events could be indexed by the cardId and as such, all the events associated with a single card could be retrieved. There are a total of 15,184,336 cards in the dataset—more than twice the 2018 population of Victoria. It appears that all touch on and off events for metropolitan trains and trams have been included, though other forms of transport such as intercity trains and some buses are absent. In total there are nearly 2 billion touch on and off events in the dataset.

No information was provided as to the de-identification that was performed on the dataset. Our analysis indicates that little to no de-identification took place on the bulk of the data, as will become evident in Section 3. The exception is the cardId, which appears to have been mapped in some way from the Myki Card Number. The exact mapping has not been discovered, although concerns remain as to its security effectiveness….(More)”.

Open Mobility Foundation

Curated on Posted on by Stefaan Verhulst

Press Release: “The Open Mobility Foundation (OMF) – a global coalition led by cities committed to using well-designed, open-source technology to evolve how cities manage transportation in the modern era – launched today with the mission to promote safety, equity and quality of life. The announcement comes as a response to the growing number of vehicles and emerging mobility options on city streets. A new city-governed non-profit, the OMF brings together academic, commercial, advocacy and municipal stakeholders to help cities develop and deploy new digital mobility tools, and provide the governance needed to efficiently manage them.

“Cities are always working to harness the power of technology for the public good. The Open Mobility Foundation will help us manage emerging transportation infrastructures, and make mobility more accessible and affordable for people in all of our communities,” said Los Angeles Mayor Eric Garcetti, who also serves as Advisory Council Chair of Accelerator for America, which showcased the MDS platform early on.

The OMF convenes a new kind of public-private forum to seed innovative ideas and govern an evolving software platform. Serving as a forum for discussions about pedestrian safety, privacy, equity, open-source governance and other related topics, the OMF has engaged a broad range of city and municipal organizations, private companies and non-profit groups, and experts and advocates to ensure comprehensive engagement and expertise on vital issues….

The OMF governs a platform called “Mobility Data Specification” (MDS) that the Los Angeles Department of Transportation developed to help manage dockless micro-mobility programs (including shared dockless e-scooters). MDS is comprised of a set of Application Programming Interfaces (APIs) that create standard communications between cities and private companies to improve their operations. The APIs allow cities to collect data that can inform real-time traffic management and public policy decisions to enhance safety, equity and quality of life. More than 50 cities across the United States – and dozens across the globe – already use MDS to manage micro-mobility services.

Making this software open and free offers a safe and efficient environment for stakeholders, including municipalities, companies, experts and the public, to solve problems together. And because private companies scale best when cities can offer a consistent playbook for innovation, the OMF aims to nurture those services that provide the highest benefit to the largest number of people, from sustainability to safety outcomes….(More)”

Access to Data in Connected Cars and the Recent Reform of the Motor Vehicle Type Approval Regulation

Curated on Posted on by Stefaan Verhulst

Paper by Wolfgang Kerber and Daniel Moeller: “The need for regulatory solutions for access to in-vehicle data and resources of connected cars is one of the big controversial and unsolved policy issues. Last year the EU revised the Motor Vehicle Type Approval Regulation which already entailed a FRAND-like solution for the access to repair and maintenance information (RMI) to protect competition on the automotive aftermarkets. However, the transition to connected cars changes the technological conditions for this regulatory solution significantly. This paper analyzes the reform of the type approval regulation and shows that the regulatory solutions for access to RMI are so far only very insufficiently capable of dealing with the challenges coming along with increased connectivity, e.g. with regard to the new remote diagnostic, repair and maintenance services. Therefore, an important result of the paper is that the transition to connected cars will require a further reform of the rules for the regulated access to RMI (esp. with regard to data access, interoperability, and safety/security issues). However, our analysis also suggests that the basic approach of the current regulated access regime for RMI in the type approval regulation can also be a model for developing general solutions for the currently unsolved problems of access to in-vehicle data and resources in the ecosystem of connected driving….(More)”.

EU countries and car manufacturers to share information to improve road safety

Curated on Posted on by Stefaan Verhulst

Press Release: “EU member states, car manufacturers and navigation systems suppliers will share information on road conditions with the aim of improving road safety. Cora van Nieuwenhuizen, Minister of Infrastructure and Water Management, agreed this today with four other EU countries during the ITS European Congress in Eindhoven. These agreements mean that millions of motorists in the Netherlands will have access to more information on unsafe road conditions along their route.

The data on road conditions that is registered by modern cars is steadily improving. For instance, information on iciness, wrong-way drivers and breakdowns in emergency lanes. This kind of data can be instantly shared with road authorities and other vehicles following the same route. Drivers can then adapt their driving behaviour appropriately so that accidents and delays are prevented….

The partnership was announced today at the ITS European Congress, the largest European event in the fields of smart mobility and the digitalisation of transport. Among other things, various demonstrations were given on how sharing this type of data contributes to road safety. In the year ahead, the car manufacturers BMW, Volvo, Ford and Daimler, the EU member states Germany, the Netherlands, Finland, Spain and Luxembourg, and navigation system suppliers TomTom and HERE will be sharing data. This means that millions of motorists across the whole of Europe will receive road safety information in their car. Talks on participating in the partnership are also being conducted with other European countries and companies.

ADAS

At the ITS congress, Minister Van Nieuwenhuizen and several dozen parties today also signed an agreement on raising awareness of advanced driver assistance systems (ADAS) and their safe use. Examples of ADAS include automatic braking systems, and blind spot detection and lane keeping systems. Using these driver assistance systems correctly makes driving a car safer and more sustainable. The agreement therefore also includes the launch of the online platform “slimonderweg.nl” where road users can share information on the benefits and risks of ADAS.
Minister Van Nieuwenhuizen: “Motorists are often unaware of all the capabilities modern cars offer. Yet correctly using driver assistance systems really can increase road safety. From today, dozens of parties are going to start working on raising awareness of ADAS and improving and encouraging the safe use of such systems so that more motorists can benefit from them.”

Connected Transport Corridors

Today at the congress, progress was also made regarding the transport of goods. For example, at the end of this year lorries on three transport corridors in our country will be sharing logistics data. This involves more than just information on environmental zones, availability of parking, recommended speeds and predicted arrival times at terminals. Other new technologies will be used in practice on a large scale, including prioritisation at smart traffic lights and driving in convoy. Preparatory work on the corridors around Amsterdam and Rotterdam and in the southern Netherlands has started…..(More)”.

107 Years Later, The Titanic Sinking Helps Train Problem-Solving AI

Curated on Posted on by Stefaan Verhulst

Kiona N. Smith at Forbes: “What could the 107-year-old tragedy of the Titanic possibly have to do with modern problems like sustainable agriculture, human trafficking, or health insurance premiums? Data turns out to be the common thread. The modern world, for better or or worse, increasingly turns to algorithms to look for patterns in the data and and make predictions based on those patterns. And the basic methods are the same whether the question they’re trying to answer is “Would this person survive the Titanic sinking?” or “What are the most likely routes for human trafficking?”

An Enduring Problem

Predicting survival at sea based on the Titanic dataset is a standard practice problem for aspiring data scientists and programmers. Here’s the basic challenge: feed your algorithm a portion of the Titanic passenger list, which includes some basic variables describing each passenger and their fate. From that data, the algorithm (if you’ve programmed it well) should be able to draw some conclusions about which variables made a person more likely to live or die on that cold April night in 1912. To test its success, you then give the algorithm the rest of the passenger list (minus the outcomes) and see how well it predicts their fates.

Online communities like Kaggle.com have held competitions to see who can develop the algorithm that predicts survival most accurately, and it’s also a common problem presented to university classes. The passenger list is big enough to be useful, but small enough to be manageable for beginners. There’s a simple set out of outcomes — life or death — and around a dozen variables to work with, so the problem is simple enough for beginners to tackle but just complex enough to be interesting. And because the Titanic’s story is so famous, even more than a century later, the problem still resonates.

“It’s interesting to see that even in such a simple problem as the Titanic, there are nuggets,” said Sagie Davidovich, Co-Founder & CEO of SparkBeyond, who used the Titanic problem as an early test for SparkBeyond’s AI platform and still uses it as a way to demonstrate the technology to prospective customers….(More)”.

Using street imagery and crowdsourcing internet marketplaces to measure motorcycle helmet use in Bangkok, Thailand

Curated on Posted on by Stefaan Verhulst

Hasan S. Merali, Li-Yi Lin, Qingfeng Li, and Kavi Bhalla in Injury Prevention: “The majority of Thailand’s road traffic deaths occur on motorised two-wheeled or three-wheeled vehicles. Accurately measuring helmet use is important for the evaluation of new legislation and enforcement. Current methods for estimating helmet use involve roadside observation or surveillance of police and hospital records, both of which are time-consuming and costly. Our objective was to develop a novel method of estimating motorcycle helmet use.

Using Google Maps, 3000 intersections in Bangkok were selected at random. At each intersection, hyperlinks of four images 90° apart were extracted. These 12 000 images were processed in Amazon Mechanical Turk using crowdsourcing to identify images containing motorcycles. The remaining images were sorted manually to determine helmet use.

After processing, 462 unique motorcycle drivers were analysed. The overall helmet wearing rate was 66.7 % (95% CI 62.6 % to 71.0 %). …

This novel method of estimating helmet use has produced results similar to traditional methods. Applying this technology can reduce time and monetary costs and could be used anywhere street imagery is used. Future directions include automating this process through machine learning….(More)”.

Identifying commonly used and potentially unsafe transit transfers with crowdsourcing

Curated on Posted on by Stefaan Verhulst

Paper by Elizabeth J.Traut and Aaron Steinfeld: “Public transit is an important contributor to sustainable transportation as well as a public service that makes necessary travel possible for many. Poor transit transfers can lead to both a real and perceived reduction in convenience and safety, especially for people with disabilities. Poor transfers can expose riders to inclement weather and crime, and they can reduce transit ridership by motivating riders who have the option of driving or using paratransit to elect a more expensive and inefficient travel mode. Unfortunately, knowledge about inconvenient, missed, and unsafe transit transfers is sparse and incomplete.

We show that crowdsourced public transit ridership data, which is more scalable than conducting traditional surveys, can be used to analyze transit transfers. The Tiramisu Transit app merges open transit data with information contributed by users about which trips they take. We use Tiramisu data to do origin-destination analysis and identify connecting trips to create a better understanding of where and when poor transfers are occurring in the Pittsburgh region. We merge the results with data from other open public data sources, including crime data, to create a data resource that can be used for planning and identification of locations where bus shelters and other infrastructure improvements may facilitate safer and more comfortable waits and more accessible transfers. We use generalizable methods to ensure broader value to both science and practitioners.

We present a case study of the Pittsburgh region, in which we identified and characterized 338 transfers from 142 users. We found that 66.6% of transfers were within 0.4 km (0.25 mi.) and 44.1% of transfers were less than 10 min. We identified the geographical distribution of transfers and found several highly-utilized transfer locations that were not identified by the Port Authority of Allegheny County as recommended transfer points, and so might need more planning attention. We cross-referenced transfer location and wait time data with crime levels to provide additional planning insight….(More)”.

What Makes a City Street Smart?

Curated on Posted on by Stefaan Verhulst

Taxi and Limousine Commission’s (TLC): “Cities aren’t born smart. They become smart by understanding what is happening on their streets. Measurement is key to management, and amid the incomparable expansion of for-hire transportation service in New York City, measuring street activity is more important than ever. Between 2015 (when app companies first began reporting data) and June 2018, trips by app services increased more than 300%, now totaling over 20 million trips each month. That’s more cars, more drivers, and more mobility.

Taxi and Limousine Commission’s (TLC): “Cities aren’t born smart. They become smart by understanding what is happening on their streets. Measurement is key to management, and amid the incomparable expansion of for-hire transportation service in New York City, measuring street activity is more important than ever. Between 2015 (when app companies first began reporting data) and June 2018, trips by app services increased more than 300%, now totaling over 20 million trips each month. That’s more cars, more drivers, and more mobility.

We know the true scope of this transformation today only because of the New York City Taxi and Limousine Commission’s (TLC) pioneering regulatory actions. Unlike most cities in the country, app services cannot operate in NYC unless they give the City detailed information about every trip. This is mandated by TLC rules and is not contingent on companies voluntarily “sharing” only a self-selected portion of the large amount of data they collect. Major trends in the taxi and for-hire vehicle industry are highlighted in TLC’s 2018 Factbook.

What Transportation Data Does TLC Collect?

Notably, Uber, Lyft, and their competitors today must give the TLC granular data about each and every trip and request for service. TLC does not receive passenger information; we require only the data necessary to understand traffic patterns, working conditions, vehicle efficiency, service availability, and other important information.

One of the most important aspects of the data TLC collects is that they are stripped of identifying information and made available to the public. Through the City’s Open Data portal, TLC’s trip data help businesses distinguish new business opportunities from saturated markets, encourage competition, and help investors follow trends in both new app transportation and the traditional car service and hail taxi markets. As app companies contemplate going public, their investors have surely already bookmarked TLC’s Open Data site.

Using Data to Improve Mobility

With this information NYC now knows people are getting around the boroughs using app services and shared rides with greater frequency. These are the same NYC neighborhoods that traditionally were not served by yellow cabs and often have less robust public transportation options. We also know these services provide an increasing number of trips in congested areas like Manhattan and the inner rings of Brooklyn and Queens, where public transportation options are relatively plentiful….(More)”.

In High-Tech Cities, No More Potholes, but What About Privacy?

Curated on Posted on by Stefaan Verhulst

Timothy Williams in The New York Times: “Hundreds of cities, large and small, have adopted or begun planning smart cities projects. But the risks are daunting. Experts say cities frequently lack the expertise to understand privacy, security and financial implications of such arrangements. Some mayors acknowledge that they have yet to master the responsibilities that go along with collecting billions of bits of data from residents….

Supporters of “smart cities” say that the potential is enormous and that some projects could go beyond creating efficiencies and actually save lives. Among the plans under development are augmented reality programs that could help firefighters find people trapped in burning buildings and the collection of sewer samples by robots to determine opioid use so that city services could be aimed at neighborhoods most in need.

The hazards are also clear.

“Cities don’t know enough about data, privacy or security,” said Lee Tien, a lawyer at the Electronic Frontier Foundation, a nonprofit organization focused on digital rights. “Local governments bear the brunt of so many duties — and in a lot of these cases, they are often too stupid or too lazy to talk to people who know.”

Cities habitually feel compelled to outdo each other, but the competition has now been intensified by lobbying from tech companies and federal inducements to modernize.

“There is incredible pressure on an unenlightened city to be a ‘smart city,’” said Ben Levine, executive director at MetroLab Network, a nonprofit organization that helps cities adapt to technology change.

That has left Washington, D.C., and dozens of other cities testing self-driving cars and Orlando trying to harness its sunshine to power electric vehicles. San Francisco has a system that tracks bicycle traffic, while Palm Beach, Fla., uses cycling data to decide where to send street sweepers. Boise, Idaho, monitors its trash dumps with drones. Arlington, Tex., is looking at creating a transit system based on data from ride-sharing apps….(More)”.