Potential advantages of global positioning systems (GPS) in collecting travel behavior data have been discussed in several publications and evidenced in many recent studies. Most applications depend on GPS information only. However, transportation mode detection that relies only on GPS information may be erroneous due to variance in device performance and settings, and the environment in which measurements are made. Accelerometers, being used mainly for identifying peoples’ physical activities, may offer new opportunities as these devices record data independent of exterior contexts. The purpose of this paper is therefore to examine the merits of employing accelerometer data in combination with GPS data in transportation mode identification. Three approaches (GPS data only, accelerometer data only and a combination of both accelerometer and GPS data) are examined. A Bayesian Belief Network model is used to infer transportation modes and activity episodes simultaneously. Results show that the use of accelerometer data can make a substantial contribution to successful imputation of transportation mode. The accelerometer only approach outperforms the GPS only approach in terms of the predictive accuracy. The approach which combines GPS and accelerometer data yields the best performance.
This Friday, November 1 2013, the SafeTREC-UCTC Brown Bag Seminar features the City of Oakland's Senior Transportation Planner Jaime Parks. Parks will present, "Transportation Policy in Oakland as It Is and as It Should Be".
Oakland has more BART stations than any other Bay Area jurisdiction, numerous mixed-use neighborhoods, and one of the highest bike-to-work mode shares in the country. Yet, the City has failed to fully take advantage of these natural advantages, partially due to the lack of a cohesive vision for the role transportation should play in the lives of Oaklanders. Oakland passed a Complete Streets Policy in 2013 that will allow the City to consider transportation decisions from a broader perspective. The presentation will share updates on several on-going complete streets initiatives, including analysis of crash trends Citywide, data management, CEQA reform, and experiments with green paint and temporary spaces. The presentation will also identify key knowledge gaps as suggested topics for future urban transportation research.
The seminar takes place from noon-1:00 PM SafeTREC 2nd Floor Conference Room, 2614 Dwight Way, Berkeley, CA
or via webcast.
In the spirit of Open Access Week, here's an interesting article from an open access journal - The Journal of Transport and Land Use. Go check it out and peruse the articles. No need to depend on your institution's sibscription because it's free to the public! (Thanks open access!)
This paper presents a methodology to investigate the link between bicycle activity and built environment, road and transit network characteristics, and bicycle facilities while also accounting for spatial autocorrelation between intersections. The methodology includes the normalization of manual cyclist counts to average seasonal daily volumes (ASDV), taking into account temporal variations and using hourly, daily, and monthly expansion factors obtained from automatic bicycle count data. To correct for weather conditions, two approaches were used. In the first approach, a relative weather ridership model was generated using the automatic bicycle count and weather data. In the second approach, weather variables were introduced directly into the model. For each approach, the effects of built environment, road and transit characteristics, and bicycle facilities on cyclist volumes were determined. It was found that employment, schools, metro stations, bus stops, parks, land mix, mean income, bicycle facility type (bicycle lanes and cycle tracks), length of bicycle facilities, average street length, and presence of parking entrances were associated with bicycle activity. From these, it was found that the main factors associated with bicycle activity were land-use mix, cycle track presence, and employment density. For instance, intersections with cycle tracks have on average 61 percent more cyclists than intersections without. An increase of 10 percent in land-use mix or employment density would cause an increase of 8 percent or 5.3 percent, respectively, in bicycle flows. The methods and results proposed in this research are helpful for planning bicycle facilities and analyzing cyclist safety. Limitations and future work are discussed at the end of this paper.
It's a new school year and a new semester, which means the TRANSOC Friday Seminars are back! Kicking things off this week is Brett Hondorp, AICP from Alta Planning + Design / Alta Bicycle Share. He will be talking about bikeshare implementation and lessons learned in "Bike Share Planning and Implementation – Lessons learned from DC, Boston, New York, and the Bay Area".
This presentation will focus on three elements of bicycle sharing: 1.) Planning for bikeshare, using the recent Bay Area launch as an example, 2.) Ongoing system operations, drawing from our recent experience operating eight bikeshare systems globally, and 3.) User characteristics, relying on data from our long running Capital Bikeshare and Hubway systems.
The seminar will take place a 4:00-5:00 PM September 6, 2013 in 534 Davis Hall. This week is also the return of Cookie Hour in the library at 3:30. See you then!
Is this the summer of Bikeshare? Divvy Bikes in Chicago launched last month. CitiBikes in New York City launched around Memorial Day. Any time now Bay Area Bike Share will be launching in San Francisco and on then Peninsula.
The issue of having bikes where people want them is a perennial issue for bikeshare systems. "Rebalancing" is the act of moving inventory around to match demand and travel patterns. This map provides realtime visualizations of the demand of bikeshare systems around the world. Researchers are working on solving the rebalancingproblem.
Bike-sharing systems allow people to rent a bicycle at one of many automatic rental stations scattered around the city, use them for a short journey and return them at any station in the city. A crucial factor for the success of a bike-sharing system is its ability to meet the fluctuating demand for bicycles and for vacant lockers at each station. This is achieved by means of a repositioning operation, which consists of removing bicycles from some stations and transferring them to other stations, using a dedicated fleet of trucks. Operating such a fleet in a large bike-sharing system is an intricate problem consisting of decisions regarding the routes that the vehicles should follow and the number of bicycles that should be removed or placed at each station on each visit of the vehicles. In this paper, we present our modeling approach to the problem that generalizes existing routing models in the literature. This is done by introducing a unique convex objective function as well as time-related considerations. We present two mixed integer linear program formulations, discuss the assumptions associated with each, strengthen them by several valid inequalities and dominance rules, and compare their performances through an extensive numerical study. The results indicate that one of the formulations is very effective in obtaining high quality solutions to real life instances of the problem consisting of up to 104 stations and two vehicles. Finally, we draw insights on the characteristics of good solutions.
The 4,280 pedestrian fatalities in 2010 were an increase of 4 percent from 2009, but
a decrease of 13 percent from 2001. In 2010, pedestrian deaths accounted for 13
percent of all traffic fatalities, and made up 3 percent of all the people injured in
"When Distracted Road Users Cross Paths" examines the relationship between distracted drives and distracted pedestrians. The authors conclude, " Ultimately, a safe roadway environment depends on all road users paying attention to where they are going and being aware of other users who might be sharing the road."
A nice summary of bicycle ridership in the United States, as well as information pretaining to bicycle related fatalitities in 2008 and investment in bike-ped infrastructure. The Bay Are has done well - San Francisco is ranked Gold for bicycle friendly and Oakland is bronze. (via CFIRE)