Tuesday, November 26, 2013

Connecting Poor and Rich: Transit, Equity, and Crime

Historically, rich neighborhoods in cities (like Lake Oswego in Portland, OR) have opposed building transit lines that connect them with poor neighborhoods in fear of their own safety. With the recent availability of large amount of urban data and "hotness" of big data analytics, an interesting idea of research is performing a comparative analysis of different transit routes with respect to equity and safety/crime. Thanks to the Transit Quality and Equity visualization project by the vudlab at UC Berkeley, one could qualitatively/visually realize that there exist some transit routes in San Francisco that connects poor neighborhoods to rich neighborhoods (or poor-to-poor and rich-to-rich). One could compute an equity score for each route (based on income for example) and compare different transit routes in the entire transit network with respect to that equity score. In addition to an average equity score, one could also look at the variations throughout each route and identify those routes that goes through highly different neighborhoods (from poor to rich for example). Using detailed crime data (if available publicly), a safety analysis (for example, # of crimes inside the transit vehicle or in the vicinity of the transit station) could also be performed for each route and comparatively. Can we verify whether the routes that connect rich and poor neighborhoods are associated with high crime rates? Does transit reduce safety in rich neighborhoods?

Reproducibility Initiative on Transportation and Traffic Phenomena

Inspired by the Reproducibility Initiative in psychology launched by Science Exchange, PLOS ONE, figshare, and Mendeley, I think there is a need to start a similar work to verify the reproducibility of some of the transportation and traffic phenomena. For example, transportation journals could announce a call for papers for a special issue on "reproducibility". The ideal initiative would be a world-wide collaborative project that first identifies some of the main phenomena/effects that need to be verified and then different research groups work together to collect/obtain new data and examine the reproducibility of the selected phenomena.
"It’s time to start rewarding the people who take the extra time to do the most careful and reproducible work. Current academic incentives place an emphasis on novelty, which comes at the expense of rigor...we believe that the scientific consensus on the most robust, as opposed to simply the most cited, work is a valuable signal to help identify high quality reproducible findings that can be reliably built upon to advance scientific understanding." - Reproducibility Initiative

Transferability and Reproducibility of Travel Behavior Phenomena

A recent article in Nature reports on a large collaborative study done by 36 labs across the globe to examine the reproduciblity of the results of several classic and contemporary studies in psychology. It's reported that they could successfully reproduce the results of 10 out of 13 past experiments. Further details are published in an article on "Investigating variation in replicability: The “Many Labs” Replication Project".

The question remains open for reproduciblity of some of the observed travel behavior phenomena. It would be interesting to test, for example, the shape of the response function to waiting time, or existence of thresholds in price sensitivity, etc. (Idea: courtesy of Hani Mahmassani).

With regard to temporal or spatial transferability of travel behavior models, there are numerous studies in the literature. Perhaps the following dissertation by Sujan Sikder (University of South Florida) provides a comprehensive background on the transferability issue: Spatial Transferability of Activity-Based Travel
Forecasting Models.

Growing Smart Cities Industry/Market

Here are a few readings on the growing "smart cities industry/market" which will be worth more than $400 billion globally by 2020:

15 Strategic Research Priorities of Australia

15 Strategic Research Priorities (released on 21 June 2013 by the Australian government) include:

Living in a changing environment
  1. Identify vulnerabilities and boundaries to the adaptability of changing natural and human systems
  2. Manage risk and capture opportunities for sustainable natural and human systems
  3. Enable societal transformation to enhance sustainability and wellbeing
Promoting population health and wellbeing
  1. Optimise effective delivery of health care and related systems and services
  2. Maximise social and economic participation in society
  3. Improve the health and wellbeing of Aboriginal and Torres Strait Islander people
Managing our food and water assets
  1. Optimise food and fibre production using our land and marine resources
  2. Develop knowledge of the changing distribution, connectivity, transformation and sustainable use of water in the Australian landscape
  3. Maximize the effectiveness of the production value chain from primary to processed food
Securing Australia's place in a changing world
  1. Improve cybersecurity for all Australians
  2. Manage the flow of goods, information, money and people across our national and international boundaries
  3. Understand political, cultural, economic and technological change, particularly in our region
Lifting productivity and economic growth
  1. Identify the means by which Australia can lift productivity and economic growth
  2. Maximise Australia’s competitive advantage in critical sectors
  3. Deliver skills for the new economy

Transportation & Health: Effects of Light Rail Transit Extension on Physical Activity and Travel Behavior in Houston

See the following articles:

UTHealth researchers to measure impact of METRO on physical activity of Houston residents

TTI and UTHealth Join Forces on 5-Year Transportation and Health Study Granted by NIH
"For the first time, the Texas A&M Transportation Institute (TTI) will team up with the University of Texas Health Science Center in Houston (UTHealth), for a new project funded by the National Institutes of Health (NIH). The five-year project will look at how the Metropolitan Transit Authority of Harris County’s (METRO’s) light rail transit (LRT) line extensions affect the physical activity and travel behavior of adults in Houston. Researchers are particularly interested in understanding this effect in the low-income, ethnically diverse adult population residing along the new LRT lines."

Example in Chile: Increasing Metro transit station capacity? (in Spanish)

Friday, November 22, 2013

Call for Papers: Big Data in Transportation and Traffic Engineering

Call for papers for a special issue in Transportation Research Part C:
"Big Data has been expanding into the transportation arena. However, the methods, models and algorithms that are used today in our domain to mine and explore data - think of estimation, prediction, validation of traffic and transportation theories and models - may not scale and/or perform well under these new conditions. This special issue solicits papers that advance the fundamental understanding, concepts and technologies related to Big Data applications to transportation and traffic engineering. Original contributions that provide novel theories, frameworks, and solutions to challenging problems of Big Data analytics are welcome."
Inquiries should be directed to Drs. Park (bpark@virginia.edu), van Lint (j.w.c.vanlint@tudelft.nl), Vlahogianni (elenivl@central.ntua.gr), and to the Editor-in-Chief, Dr. Karlaftis (mgk@mail.ntua.gr).

Australian Urban Research Infrastructure Network (AURIN)

"The Australian Urban Research Infrastructure Network (AURIN) is a $20 million initiative funded by the Australian Government’s Super Science scheme. AURIN will provide built environment and urban researchers, designers and planners with infrastructure to facilitate access to a distributed network of aggregated datasets and information services."https://aurin.org.au/
The final product will be a huge database including hundreds of valuable datasets from different urban-related organizations in Australia. It provides a basis for further development and understanding of cities.

Ports of Australia

The top five busiest ports in Australia by total cargo volume are:
  1. Port Hedland: 246,672 thousand of tons
  2. Dampier: 171,844 thousand of tons
  3. Newcastle: 129,283 thousand of tons
  4. Gladstone: 83,790 thousand of tons
  5. Hay Point: 82,854 thousand of tons
Reference: Ports Australia Trade Statistics

Thursday, November 21, 2013

United Parcel Service (UPS) and the Traveling Salesman Problem

Recently published in INFORMS Analytics Magazine
"UPS recently launched its route optimization software known as ORION (On-Road Integrated Optimization and Navigation), just in time for the busy holiday season. The rollout of ORION will optimize 10,000 delivery routes by the end of the year, thus reducing miles driven and reinforcing UPS’ sustainability efforts by saving more than 1.5 million gallons of fuel and reducing carbon dioxide emissions by more than 14,000 metric tones in that time frame. A reduction of just one mile each day per driver over the course of a year saves the company up to $50 million."

Sunday, November 17, 2013

Kerner's new article: "Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory"

Recently published by Boris Kerner in Physica A: "Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory: A brief review"
Abstract. "It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliably used for control and optimization in traffic networks. It is shown that the generally accepted fundamentals and methodologies of the traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of the traffic and transportation theory belong (i) Lighthill–Whitham–Richards (LWR) theory, (ii) the General Motors (GM) model class (for example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular (fixed or stochastic) value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of the traffic and transportation theory, we discuss the three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks."

Wednesday, November 13, 2013

Visualizing Urban Data IdeaLab @ UC Berkeley

If you are interested in urban data visualization, you may regret missing visiting the "Visualizing Urban Data IdeaLab" at UC Berkeley.
"The Visualizing Urban Data Idealab (VUDlab) is a student-led organization formed at University of California-Berkeley in May 2013. It is a project of the Blum Center for Developing Economies IdeaLabs program.

The past decade has witnessed explosive growth in the world’s urban population alongside equally quick growth in digital record-keeping. The Visualizing Urban Data IdeaLab builds on both trends, to create a space where participants can learn and invent visual ways to clarify urban data. The IdeaLab hosts speakers, teaches software and computer languages, and encourages collaboration across departments on projects that exploit they Berkeley community's strengths in the social and information sciences. We are open to off-campus participation. Follow @vudlab

Tuesday, November 12, 2013

MIT Big Data Challenge: Predict Taxi Demand

The goal is to predict taxi demand in downtown Boston based on historical taxi data (2.3 million rides) and other related data sets (weather, transit, events, and social media data).
"We have collected several months worth of twitter, MBTA, taxi pickup and drop off, and other datasets (see datasets page). In this challenge we will give you all of the data except for a number of 2 hour time spans at several locations in downtown Boston that we will remove from the taxi pickup dataset. Your job is to predict the total number of taxi trips within 250 meters of the locations and the 2 hour time spans. We will give you a list of location (latitude, longitude points) and timespan pairs. Your score will be computed as the root-mean-squared error of your predictions against the ground truth."

Monday, November 11, 2013

Hyper data vs. Big data

Big Data’s Little Brother: Start-Ups Are Mining Hyperlocal Information for Global Insights
Published in the NY Times.
"A picture of a pile of tomatoes in Asia may not lead anyone to a great conclusion other than how tasty those tomatoes may or may not look. But connect pictures of food piles around the world to weather forecasts and rainfall totals and you have meaningful information that people like stockbrokers or buyers for grocery chains could use."

Urban Network Gridlock

Recently published.

This study explores the limiting properties of network-wide traffic flow relations under heavily congested conditions in a large-scale complex urban street network; these limiting conditions are emulated in the context of dynamic traffic assignment (DTA) experiments on an actual large network. The primary objectives are to characterize gridlock and understand its dynamics. This study addresses a gap in the literature with regard to the existence of exit flow and recovery period. The one-dimensional theoretical Network Fundamental Diagram (NFD) only represents steady-state behavior and holds only when the inputs change slowly in time and traffic is distributed homogenously in space. Also, it does not describe the hysteretic behavior of the network traffic when a gridlock forms or when network recovers. Thus, a model is proposed to reproduce hysteresis and gridlock when homogeneity and steady-state conditions do not hold. It is conjectured that the network average flow can be approximated as a non-linear function of network average density and variation in link densities. The proposed model is calibrated for the Chicago Central Business District (CBD) network. We also show that complex urban networks with multiple route choices, similar to the idealized network tested previously in the literature, tend to jam at a range of densities that are smaller than the theoretical average network jam density. Also it is demonstrated that networks tend to gridlock in many different ways with different configurations. This study examines how mobility of urban street networks could be improved by managing vehicle accumulation and redistributing network traffic via strategies such as demand management and disseminating real-time traveler information (adaptive driving). This study thus defines and explores some key characteristics and dynamics of urban street network gridlocks including gridlock formation, propagation, recovery, size, etc.

Sunday, November 10, 2013

Wednesday, November 6, 2013

Journal of "Scientific Data" by Nature

Nature is launching "Scientific Data", an open-access, online-only, peer-reviewed journal for detailed descriptions of data sets: http://www.nature.com/scientificdata/

Initiatives on Smart Cities in the UK and EC

New initiative to support $40 billion smart cities in the UK
"It comes as a new report published today values the smart cities industry at more than $400 billion globally by 2020, with the UK expected to gain a 10% share ($40 billion)."
European Initiative on Smart Cities
"This Initiative will support cities and regions in taking ambitious and pioneering measures to progress by 2020 towards a 40% reduction of greenhouse gas emissions through sustainable use and production of energy. This will require systemic approaches and organisational innovation, encompassing energy efficiency, low carbon technologies and the smart management of supply and demand. In particular, measures on buildings, local energy networks and transport would be the main components of the Initiative."

Monday, November 4, 2013

Bike-Share as Mass Transit

The Atlantic Cities - In a recent issue of the Journal of Public Transportation, UCLA planning scholars Rui Wang and Chen Liu make a strong case that U.S. cities should do a better job integrating bikes into metro transit systems.
"This paper analyzes the recent trend in bicycle-transit integration in the U.S. It reviews data from the National Household Travel Surveys (NHTS) to show the characteristics of bicycle-transit integrated trips, where the integrators were from, and to which population groups the integrators belonged. Bicycle-transit integration was increasingly observed in commuters and younger travelers, and became more imbalanced by gender. Results indicate the rise in socio-economic diversity of bicycle-transit integrators, despite a racial gap. There was a clear concentration of bicycle-transit integrators in large and high-density urban areas, where most transit users lived. Evidence does not support that rail attracts more bike access/egress trips than bus. More transit users used bicycles to access/egress in the Pacific, East North Central, and Mountain regions. Given the non-trivial role of bicycles compared to transit in the U.S., the focus on bicycle use and the marriage between bicycle and transit should be further emphasized."
View the full article.