#22 Building an accessible, low-stress, safe, and sustainable, bicycle infrastructure network for the City of Pittsburgh
- Principal Investigator
- Sean Qian
- Status
- Completed
- Start Date
- Jan. 1, 2017
- End Date
- Aug. 31, 2018
- Project Type
- Research Applied
- Grant Program
- MAP-21 TSET National (2013 - 2018)
- Grant Cycle
- 2017 TSET UTC
- Visibility
- Public
Abstract
The long-term sustainability of bicycle infrastructure networks call for systematic design and planning of bicycle infrastructure that takes into consideration the presence of pedestrians, bicycles, and other vehicles. In this research, we propose to utilize massive data in the existing multi-modal transportation systems to facilitate decision making on expanding infrastructure networks, as well as to provide bike-friendly route information to cyclists that considers riding easiness, bus coverage, safety risks and car frictions. Sustainable mobility is one of the key challenges for smart cities. Being a critical component of the multi-modal transportation system, bicycle infrastructure supports short- and medium-distance trips for residents, commuters and visitors. Cycling allows people to travel with minimum impact from/to roadway congestion. It offers a healthy lifestyle and reduces fuel use. The goal of this research is to build an accessible, low-stress, safe, and sustainable bicycle infrastructure network for the City of Pittsburgh. Pittsburgh is quickly emerging as one of the nation's most progressive bike-friendly cities. Pittsburgh already has 67 miles of designated bike lanes, and has built protected bike lanes on three streets, Penn Ave., Saline St. and Schenley Park. However, cyclists still have a hard time finding low-stress bike routes to commute and navigate from neighborhood to neighborhood that are safe to bicycle, pedestrian and motorized vehicular traffic. The long-term sustainability of bicycle infrastructure networks call for systematic design and planning of bicycle infrastructure that takes into consideration the presence of pedestrians, bicycles, and other vehicles. In this research, we propose to utilize massive data in the existing multi-modal transportation systems to facilitate decision making on expanding infrastructure networks, as well as to provide bike-friendly route information to cyclists. We plan to conduct this work in concert with organizations such as BikePGH as well as with the City of Pittsburgh.
Description
Research approach 1. Bike data collection. We will collect GIS data of the existing bike infrastructure, which include sidewalk, trails, bike lanes, on-street bike routes, cautionary on-street bike routes, and bike sharing stations. We also plan to work with BikePGH to collect cyclists demand information, namely how many cyclists travel from what origins to what destinations. This is partially done by the semi-annual city-wide cyclists count. We will conduct a survey for cyclists if necessary. 2. Analytics of existing bicycle infrastructure. For all road segments in the City of Pittsburgh, we will conduct data analytics by analyzing the following four factors. a. Roadway safety. We will geocode all reported traffic incidents from the County 911 call-for-service data, and estimate the crash risk for each road segment. b. Traffic flow. We have hourly traffic volume data from PennDOT and SPC at selected arterials and 5-min traffic speed data from TomTom. The traffic flow data is used to estimate emissions and potential crash risk for bike riding. c. Ride easiness. We use high-resolution elevation data to compute the slope of each road segment for each direction. d. Interaction with transit services. We can associate bus service with any road segment, since Pittsburgh buses are equipped with a front-mounted bike rack that holds two bicycles. 3. Navigation for cyclists. We will build a web-GIS application to provide best routes for cyclists that have the minimum crash risk, minimum potential conflicts with traffic flow, best air quality and easiest to ride. In addition, routes overlaying with bike sharing service and bus services can be recommended. 4. Infrastructure design. We will recommend the most cost-effective locations for building/extending bike lanes, sidewalks and bike sharing stations that can meet the needs of most cyclists demand. 5. Complete streets. We will identify several streets in the city that hold potential to implement traffic calming and design for non-motorized users. The traffic impact on cyclists and cars can be quantified. Guidelines on streets design can be provided.
Timeline
2 years
Strategic Description / RD&T
Deployment Plan
Work with PennDOT and the City of Pittsburgh
Expected Outcomes/Impacts
1. A methodology estimates the network impact of road closures in an efficient and accurate manner. 2. An open-source tools implementing the methodology and helping PA to manage and coordinate road closures. The tools, programs and data will be made available in the public domain.
Expected Outputs
TRID
Individuals Involved
| Name | Affiliation | Role | Position | |
|---|---|---|---|---|
| jbielak@cmu.edu | Bielak, Jacobo | CEE | Co-PI | Faculty - Research/Systems |
| xpi@andrew.cmu.edu | Pi, Xidong | CEE | Other | Student - Masters |
| seanqian@cmu.edu | Qian, Sean | CEE/Heinz | PI | Faculty - Research/Systems |
| shuguany@cmu.edu | Yang, Shuguan | CEE | Other | Student - Masters |
Budget
Amount of UTC Funds Awarded
$127500.00Total Project Budget (from all funding sources)
$127500.00Documents
Match Sources
No match sources!
Partners
No partners!