Accurate estimates of bicycle and pedestrian volume inform safety studies, trend monitoring, and infrastructure improvements. The Federal Highway Administration’s Traffic Monitoring Guide advises current practice for estimation of nonmotorized traffic. While methodologies have been developed to minimize error in estimation of annual average daily nonmotorized traffic (AADNT), challenges persist. This study provides new guidance for monitoring and volume estimation of nonmotorized traffic. Using continuous count data from 102 sites across six cities, the findings confirm that mean absolute percent error (MAPE) in estimated AADNT is minimized when seven-day short duration counts are collected in June through September and for 24-h counts, when data are collected Tuesdays through Thursdays (except for pedestrian-only counts). MAPE across all days (except holidays) and seasons was 34% for 24-h and 20–22% for seven-day short duration counts. The magnitude of bicycle and pedestrian volumes did not significantly affect estimation errors. For factor groups larger than one counter, the length of short duration samples may influence accuracy of AADNT estimates more than the number of counters per group, all else equal. To maximize precision of estimates of AADNT, four or more counters per factor group for bicycle and five or more for pedestrian travel monitoring are recommended. These findings provide guidance for practitioners seeking to establish or improve nonmotorized traffic monitoring programs.
Modeling procedures in transportation planning depend on the quality of data collected from personal travel surveys, which in turn depend on the data-collection technique. All conventional data-collection techniques rely on respondents to report the time, distance, and location attributes of a trip, among other things. Respondents rarely know addresses that they visit with sufficient detail to permit accurate geocoding. Also, it has been observed that short trips are underreported. Earlier studies proved the feasibility of using the Global Positioning System (GPS) as an alternative to acquire error-free, high-quality information on trip-making behavior. However, all GPS survey methodologies tested relied on the respondent to enter information into a personal data assistant (PDA) as the trip is being made and to intervene in other ways to record all data for each trip. This adds the expense of a PDA and its power supply and puts a burden on the respondent. A method that uses GPS technology with less complexity, involving less cost and minimal user intervention while making the trip, is tested and explained. Additional trip attributes that cannot be recorded by the GPS receiver were obtained after the survey period by prompted recall, in which the respondents were aided with maps displaying their travel paths. Analysis of the data showed that this method performed very well. However, a still-larger survey is needed to estimate the benefits.
Walking is the most basic and sustainable mode of transportation, and many jurisdictions would like to see increased walking rates as a way of reducing congestion and emission levels and improving public health. In the United States, walking trips account for 10.5% of all trips undertaken. To increase this rate, additional research on what makes people feel more comfortable while walking is needed. Research on pedestrian quality of service (QOS) has sought to quantify the performance of the pedestrian facilities from a pedestrian’s perspective. However, the impact of pedestrian safety countermeasures on pedestrian QOS for roadway crossings is largely unknown. The objective of this study is to discern pedestrian QOS based on physiological measurements of pedestrians performing normal walking activities in different traffic contexts. The naturalistic walking study described in this paper recruited 15 pedestrians and asked each to wear an instrumented wristband and GPS recorder on all walking trips for one week. Surprisingly, the findings from the study showed no correlation between participants’ stress levels and individual crossing locations. Instead, stress was associated with roadway conditions. Higher levels of stress were generally associated with walking in proximity to collector and arterial streets and in areas with industrial and mixed (e.g., offices, retail, residential) land uses. Stress levels were tempered in lower-density residential land uses, as well as in forest, park, and university campus environments. The outcomes from this study can inform how planners design urban environments that reduce pedestrian stress levels to promote walkability.
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