Data

New LibGuide: Transportation Data!


flickr photo shared by Eric Fischer under a Creative Commons ( BY ) license

Have you ever felt overwhelmed looking for transportation data? This new Transportation Data LibGuide should make things a little easier getting started. It provides links to data sources from a number of modes to help you with your research. 

Monitoring Traffic for Incidents and Extreme Congestion Events


flickr photo shared by canihazit under a Creative Commons ( BY-NC-ND ) license

Last week's Friday Seminar welcomed back ITS alumn, now Univeristy of Illinois Urbana-Champaign Assistant Professor, Dan Work. He presented some of his work in the area of monitoring traffic data to better responde to incidents and extreme congestion events. The talk began with focus on how his group uses the app TrafficTurk for low-cost traffic sensing, which has been used in managing big events like homecoming weekend at University of Illinois and the Farm Progress Shows in Decatur, IL (where over 100,000 people flock for the event). He then talked about how he's used this sensing data to more quickly respond to traffic incidents through multiple model particle filtering. He concluded the talk preseting some preliminary results from New York City taxi data (which is shared here as open data) on the congestion in the city following Hurricane Sandy. The data shows that there was not much congestion during evacuation, as there was a system and a plan in place, but that the extreme congestion after the storm shows a need for better post-event planning and coordination. 

You can find more of Work's publications (and source code) here

Making City-Scale Networks of Connected Vehicles Reality


creative commons licensed ( BY-NC-ND ) flickr photo shared by Roberto Maldeno

Last week's Friday Seminar featured João BarrosAssociate Professor at the University of Porto and CEO of Veniam talking about how he and his team turned public transit into smart city hot spots for Porto. After early attempts to use cellular technology for connected vehicles, which had major bottlenecks in the networks and was cost prohibitive, Barros explored the possibilities of using wi-fi technology to create a city wide mesh network. This builds upon some of Barros' earlier research that looked into the feasibility and impact of VANETs in urban environments

The key to Veniam's success on Porto has been the city's fibre-optic backbone to create wifi hotspots around the city, like bus stops. A combination of wifi and the IEEE 802.11p standard for wireless vehicle communication, and deployment in fleets such as many of the city's taxis and Metro de Porto's fleet, made the city wide mesh network possible. It also made it very cheap to offer free wifi on the entire bus fleet, which has pleased passengers

For the buses, the connectivity can be used for ticketing, navigation, infotainment, and vehicle diagnostics. This has also created a very rich, high definition data set of the fleet's operations which has informed service and route updates. 

The mesh network has also been very effective in tracking operations at Porto de Leixões. Early attempts to track vehicles with cellular technology were hindered by the lack of cell towers in the industrial area and interference from shipping containers. The wifi mesh network has made it possible to track port traffic to improve efficiency and safety. 

Barros hinted that the next wave of innovation could be in the field of wearables. His group had a project that tracked bus driver comfort and stress to better understand their behavior and how it depends on the built environment. 

Bike/Ped Data, Bike/Ped Planning

Catch up

Here are a couple of Berkeley bike/ped related things to start off your week.

First, this month NCHRP Report 797: Guidebook on Pedestrian and Bicycle Volume Data Collection has been published, which included some Berkeley researchers on the team that compiled the guidebook. You can read about their methodology here

Second, on Saturday 31 January, 2015 from 10:00am to noon the city of Berkeley hosts the Adeline Corridor Redesign Community Meeting at the South Berkeley Senior Center (2992 Ellis Street). Many of the proposed design ideas focus on improving access and safety for pedestrians and cyclists in the area. In 2010, a UC Berkeley Design Studio examined the area, and you can see their designs here. Are they going to be implemented? Time will tell. 

A Brief History of GTFS

Time within each minute that Muni buses are typically reported at each location

Hang out around transportation geeks enough and you'll hear people throwing around the term GTFS. People throw it around on Twitter like crazy. It's an important part of the transit data landscape, so let's take a look at it. 

GTFS is also known as the General Transit Feed Specification. It was originally known as the Google Transit Feed Specification and was used to integrate transit into Google Maps, but the name was changed as more people began to use GTFS beyond the Google platform. GTFS allows agencies to easily publish their route data so that it can be used for trip planning, data visualization, and improved accessibility. For a good history of GTFS, read this chapter from Beyond Transparency

Portland's TriMet was one of the first agencies to really implement GTFS to much scuccess. And soon others like BART and MBTA followed suit. For a comprehensive list of agencies with GTFS feeds check out the GTFS Data Exchange. One of the more recent GTFS developments has been the launce of GTFS-realtime which, as the name implies, allows agencies to provide realtime information about transit services to users. 

A company spun out of ITS Berkeley research has extended GTFS to include operational data. VIA Analytics recently launched VTFS, which is based upon GTFS but also has AVL data. They also have visualization and tracking products, and they're all open source.  

 

What's the difference between people who use taxis and people who use ridesourcing in SF?

Proposed CPUC regulations improve consumer protection for Uber, Lyft and Sidecar

It seems like every week the two largest ridesourcing/TNC/ridesharing companies, Uber and Lyft, are in the news. This week featured stories about the two companies opposing a California state legislature bill mandating insurance for drivers, Uber's efforts to sabbotage Lyft with burner phones, and that both operations are now basically commodoties and not really that different from one another. 

Which makes this new UCTC paper all the more timely. 

In App-Based, On-Demand Ride Services: Comparing Taxi and Ridesourcing Trips and User Characteristics in San Francisco, Lisa Rayle (a 2014 Eisenhower Graduate Fellowship recipient) et al examine who uses these ridesourcing apps, and how they relate to more traditional taxi or transit riders. 

The rapid growth of on-demand ride services, or ridesourcing, has prompted debate among policy makers and stakeholders. At present, ridesourcing’s usage and impacts are not well understood. Key questions include: how ridesourcing and taxis compare with respect to trip types, customers, and locations served; whether ridesourcing complements or competes with public transit; and potential impacts on vehicle miles traveled. We address these questions using an intercept survey. In spring 2014, 380 complete surveys were collected from three ridesourcing “hot spots” in San Francisco. Survey results are compared with matched-pair taxi trip data and results of a previous taxi user survey.

The findings indicate ridesourcing serves a previously unmet demand for convenient, point-to-point urban travel. Although taxis and ridesourcing share similarities, the findings show differences in users and the user experience. Ridesourcing wait times are markedly shorter and more consistent than those of taxis, while ridesourcing users tend to be younger, own fewer vehicles and more frequently travel with companions. Ridesourcing appears to substitute for longer public transit trips but otherwise complements transit. Impacts on overall vehicle travel are ambiguous. Future research should build on this exploratory study to further understand impacts of ridesourcing on labor, social equity, the environment, and public policy.

The full paper can be found here

On Ramp for d3.js - March 20th!

 

Do you want to use d3.js to make data visualizations to effectively communicate your research but don't know where to start? This Thursay, March 20th, in the Lower Level of the Blum Center join VUDLab from 6-9 PM for On Ramp for d3.js.

Our "On Ramp for d3.js" is designed to get people across disciplines the needed tools and know-how to create simple and easy-to-manipulate data visualizations. By the end of the night, we plan to have our participants complete two web-based visualizations and get the baseline tools needed to begin learning d3.js on a more serious level. Think of our event as your first crash course in creating interactive tools to show off your work! We will be providing food and soft drinks for everyone (don't worry... we got you).

Details of the event can be found here

Travel Demand Forecasting: Beyond the models and into reality?

Chicago road network

Recently the State Smart Transportation Inivitiative (SSTI) asked if travel demand forecasts from U.S. DOT were accurate

Their answer is no

In the post, "U.S. DOT highway travel demand estimates continue to overshoot reality", Eric Sundquist examines the projections in FHWA's 2013 Conditions & Performance report. He finds that the estimates for VMT growth were 5-6% higher than reality. Concluding:

Had the report based estimates on more current historic data—e.g., VMT trends for 2003-13, which grew at one-fifth the USDOT’s 1995-2010 estimate—the cost estimates would have dropped by tens of billions more, reducing pressure on budgets while freeing up funds to bring the existing system to a state of good repair.

The accuracy of travel demand models and forecast predictions is not a new issue and more people are questioning the methodoloy. This year's TRB Annual Meeting featured a workshop on the issue The Next 50 Years in Travel Analysis: What We Don’t Know but Need to Know. The moderator, David T. Hartgen, mentioned a recent paper he wrote, "Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling," in Transportation. Hartgen, examining 50 years of forecasting, describes problems with accuracy and ways to imrpove models. Definitely a paper worth reading. 

Friday Seminar: Transportation modeling: A practitioner’s perspective

View from the 33rd

Today's TRANSOC Friday Seminar is all about modeling. SFCTA's Deputy Director for Technological Services, Elizabeth Sall will present, "Transportation modeling: A practitioner’s perspective".  She will speak about the types of models commonly used in long-range transportation planning in the county of San Francisco and their role in the decision-making process, as well as give an overview of some research projects that have recently been conducted at the SFCTA.

The seminar will take place today! November 1, 2013 in 534 Davis from 4:00-5:00 PM. Don't forget about Cookie Hour at 3:30 in the library. See you then!

Visualizing Urban Data Lecture with Ian Johnson

tracing the bart tracks

The first Visualizing Urban Data (VUD) idealab lecture features Ian Johnson (@enjalot), creator of tributary.io, a live-coding environment for data visualization, and curator of the d3.bayArea() meetup group. Ian will tell the story of how he got involved in data visualization and tell us more about getting involved in the world capital of data visualization.

When: THIS Wednesday 9/11 from 530-630pm
Where: B100 (lower level) of the Blum Center
Bonus: Pizza and drinks will be provided!

Syndicate content