Land Use

Open Access Article: Spatial modeling of bicycle activity at signalized intersections

Biking at Grand/Halsted/Milwaukee (3 of 4)

This week is Open Access Week. What's Open Access? Here is a not very brief overview by Peter Suber. UC Berkeley also has an Open Access Initiative to help open up your research and data. 

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!)

In "Spatial modeling of bicycle activity at signalized intersections", Jillian Strauss and Luis F Miranda-Moreno look at the built-environment and cycling. 

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.

The full article can be found here

Access Across America: How accessible are the jobs?

This week University of Minnesota's CTS issued a report about accessibility to job that includes an interactive map. Access Across America

Access Across America, a study by David Levinson, the R.P. Braun/CTS Chair in Transportation Engineering at the University of Minnesota, goes beyond congestion rankings to focus on accessibility: a measure that examines both land use and the transportation system. The study is the first systematic comparison of trends in accessibility to jobs by car within the U.S. By comparing accessibility to jobs by automobile during the morning peak period for 51 metropolitan areas, the study tells us which cities are performing well in terms of accessibility and which have seen the greatest change.

The full report can be found here. And here's the data!California is well represented with Los Angeles (1), SF-Oakland (2), and San Jose (6) all in the Top Ten.

Influence of Neighborhood Design on Travel Behaviour

United Auto Bristol RE ECW, PHN 177L

The connection between land use and travel behavior isn't a new field of transportation research, though it is definitely of much concern these days. Several researchers are looking at the current relationship of land use and travel behavior in neighborhoods. One new paper in the March 2013 issue of Transport Policy from Newcastle University focuses on the attitudes of neighborhoods in Tyne and Wear, North East England. In "The influence of neighbourhood design on travel behaviour: Empirical evidence from North East England" by Paulus Teguh Aditjandraa Corinne Mulley, and John D. Nelson find: 

This paper investigates the factors that affect travel behaviour within neighbourhoods in Tyne and Wear, North East England while accounting for differences in attitudes and perceptions. Ten different neighbourhoods have been carefully selected to characterise the two different types of traditional and suburban neighbourhood street layouts. A self-administered questionnaire has been delivered to 2200 households to capture neighbourhood design, travel patterns, travel attitudes and socio-economic characteristics. Multivariate analysis of cross-sectional data shows that some socio-economic variables as well as travel attitudes and neighbourhood design preferences can explain the differences in travel patterns between the two distinct neighbourhood designs. The results show additionally that the traditional neighbourhood group is more sensitive to factors of perception and attitudes in relation to neighbourhood design that lead to walking, cycling and public transport use travel patterns, suggesting that land-use policy designed to accommodate lower carbon-based travel together with measures to encourage active travel will have greater impact on the traditional group than the suburban group. This finding suggests that generic measures imposed by many governments, and certainly implied by current UK land-use policy, to promote sustainable mobility should be selectively targeted.

The full paper can be found here

Friday Seminar - Mark Hickman on Inferring Transit Passenger Behavior

Bus Rider's Union on The Train

This week’s Friday TRANSOC Seminar has  Mark Hickman, Ph.D., Associate Professor, Civil Engineering and Engineering Mechanics, University of Arizona, presenting “Inferring Transit Passenger Behavior.”

There are many aspects of mass transit passengers and their travel that are often difficult to observe, but which are very useful for transit service planning. These aspects include the passengers' basic travel characteristics, such as origins and destinations, time of travel, associated activities during the day, and the level of temporal and spatial access to different land uses. Traditional on-board and regional household surveys, and even newer electronic methods of observation, often have limitations on the data available for transit passengers. In this context, we explore methods that use a combination of different data sources to infer passengers' behavior. Preliminary findings, based on transit data from the Minneapolis-St. Paul area, suggest some progress in understanding this behavior. However, there remain some very interesting challenges for further research.

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