The Impact of Bicycle Corridors on Travel Demand in Utah

Grant G. Schultz, Ph.D., P.E., PTOE; Christopher K. Haskell, EIT; David R. Bassett, EIT; Shaunna K. Burbidge, Ph.D.
Utah Department of Transportation (UDOT) Report No. UT-16.01

Figure 1 Grant Avenue 2125 South, Ogden

Bicycling as an alternate mode of transportation has been on the rise. It is environmentally friendly in nature and the associated health benefits have made it a popular choice for many types of trips. With the implementation of the UDOT Inclusion of Active Transportation policy, information on type and level of impact of bicycle facilities has become more important to UDOT. The purpose of this research is to increase understanding of the travel demand impacts of implementing bicycle corridors, like the one illustrated in Figure 1, as part of the UDOT Inclusion of Active Transportation policy.

Several analyses were conducted to determine if there were any relationships that existed between bicycle rates and average annual daily traffic (AADT), posted speed limit, number of lanes, or roadway classification; and if so, if the relationship was statistically significant. The results of the AADT analysis revealed no statistical significance between bicycle rates and AADT, but the analysis did indicate a distinct trend toward a decrease in bicycle rates as AADT increased. The posted speed limit analysis revealed statistical significance and a distinct trend in bicycle rates decreasing as the posted speed limit increased as illustrated in Figure 2.

Figure 2 Bicycle Rate vs. Posted Speed

Posted speed limits from 20 to 30 mph revealed the highest bicycle rates in the analysis. The results of the number of lanes analysis revealed no statistical significance as no specific lane configuration revealed a higher bicycle rate than another. For the roadway classification analysis, three different evaluations were conducted. The first two evaluations revealed no statistical significance in a relationship between bicycle rates and roadway classification; however, the third analysis did reveal a potential difference (not statistically significant) between the Major Collector and Minor Arterial classifications and the other classifications.

After the individual analyses were conducted, a mixed model analysis was also conducted to determine if roadways with bicycle infrastructure had higher bicycle rates than adjacent roadways without bicycle infrastructure. The results revealed a 40 to 66 percent increase in bicycle volumes on roadways with bicycle infrastructure when compared to adjacent roadways that do not have bicycle infrastructure as part of the cross section. Roadways with bicycle infrastructure saw average bicycle rates twice that of roadways without bicycle infrastructure.

Finally, to gain a more historical perspective on bicycle data, three trails in Utah County were reviewed to determine if bicycle usage has increased over the past year. The three trails reviewed from 2013 to 2014 were the College Connector Trail, Provo River Trail, and the Murdock Canal Trail. All three of the trails saw an increase in bicycle usage ranging from 1.7 to 7.5 percent (600 to 7,000 cyclists).

This research acts as a basline to build upon when evaluating the impact of bicycle corridors in Utah. As more bicycle infrastructure is implemented and corresponding data are collected, the baseline can be added upon to meet the needs of all users on the transportation corridors in Utah.