A Smartphone-Based System for Automated Detection of Walking
| dc.contributor.author | Hurwitz, Philip M. | |
| dc.date.accessioned | 2019-04-09T19:58:22Z | |
| dc.date.available | 2019-04-09T19:58:22Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | Walking is the most effective mode of travel to access transit: transit hubs with higher residential and employment densities have higher ridership levels because they serve areas where a large population is within a short walk of transit service. Walking has additional benefits: it is well-known as a low impact mode of travel for short trips to and from, as well as within, commercial areas; and it is the most popular form of physical activity. However, current data on walking are notoriously poor. Travel surveys and diaries underestimate walking activity and lack information on walking paths taken, thereby undermining transportation policies that can encourage sustainable travel. Objective data on how often, how long and where people walk are essential to support environmentally friendly and safe transportation systems. | en_US |
| dc.description.sponsorship | Pacific Northwest Transportation Consortium UW Urban Form Lab | en_US |
| dc.identifier.uri | http://hdl.handle.net/1773/43577 | |
| dc.language.iso | en_US | en_US |
| dc.subject | Transportation Safety | en_US |
| dc.subject | Data and Information Technology | en_US |
| dc.subject | Pedestrian | en_US |
| dc.subject | Bicyclist | en_US |
| dc.subject | Planning and Forecasting | en_US |
| dc.subject | Public Transportation | en_US |
| dc.title | A Smartphone-Based System for Automated Detection of Walking | en_US |
| dc.type | Technical Report | en_US |
