Research Article Influence of Multiple Freeway Design Features on Freight Traffic Safety Juneyoung Park, 1 Mohamed Abdel-Aty, 2 Ling Wang , 3 Gunwoo Lee , 4 and Jungyeol Hong 5 1 Department of Transportation and Logistics Engineering, Hanyang University, Ansan, Republic of Korea 2 Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL, USA 3 e Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, China 4 Department of International Logistics, Chung-Ang University, Seoul, Republic of Korea 5 Department of Transportation Engineering, e University of Seoul, Seoul, Republic of Korea Correspondence should be addressed to Jungyeol Hong; jyhong9868@uos.ac.kr Received 28 July 2019; Revised 20 October 2019; Accepted 1 November 2019; Published 25 December 2019 Academic Editor: Richard S. Tay Copyright © 2019 Juneyoung Park et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Since various freeway design features are simultaneously installed on roadways, it is important to assess their combined safety effects correctly. is study investigated associations between multiple roadway cross-section design features on freeways and traffic safety. In order to consider the interaction impact of multiple design features and nonlinearity of predictors concurrently, multivariate adaptive regression splines (MARS) models were developed for all types and freight vehicle crashes. In MARS models, a series of basis functions is applied to represent the space of predictors and the combined safety effectiveness of multiple design features can be interpreted by the interaction terms. e generalized linear regression models (GLMs) with negative binomial (NB) distribution were also evaluated for comparison purposes. e results determine that the MARS models show better model fitness than the NB models, due to its strength to reflect the nonlinearity of crash predictors and interaction impacts among variables under different ranges. Various interaction impacts among parameters under different ranges based on knot values were found from the MARS models, whereas two interaction terms were found in the NB models. e results also showed that the combined safety effects of multiple treatments from the NB models over-estimated the real combined safety effects when using the simple multiplication approach suggested by the HSM (Highway Safety Manual). erefore, it can be recommended that the MARS is applied to evaluate the safety impacts of multiple treatments to consider both the interaction impacts among treatments and nonlinearity issues simultaneously. 1. Introduction Traffic safety has become one of the serious global concerns and many countries have taken safety plans and initiatives towards safer roadways. While roadway crashes occur over- whelmingly due to driver failures (human errors), there is an adequate potential to increase the safety of road users through the roadways themselves. erefore, designing roadways with appropriate facilities contributes to traffic safety to prevent death and injury from crashes. Among various roadway classifications such as rural two- lane highways, rural multilane highways, urban arterials, and freeways, the freeway is a roadway where additional efforts are needed to enhance traffic safety. In freeway sections, the severe crash risk may increase because vehicles drive mostly at high speeds. Moreover, there is a high potential for large-truck involved crashes due to high truck volumes and the frequent presence of interchanges. It is generally known that large trucks (i.e., commercial or freight vehicles) are substantial contributors to the roadway fatalities and injuries [1]. According to the National Highway Traffic Safety Administration (NHTSA) [2], a 10-percent increase was found in 2017 in large-trucks involved in fatal crashes from 2016 in the United States. From 2016 to 2017, large truck fatalities per 100 million vehicle miles traveled increased by 6 percent. More specifically, the number of large- truck involved injury crashes also increased from 102,000 in 2016 to 107,000 in 2017. Also, the number of large trucks involved in property damage (only crashes) increased by 3 percent, from 351,000 in 2016 to 363,000 in 2017. ere have been a number of studies which tried to assess the safety of freeway [3–7] by simple comparison methods and Hindawi Journal of Advanced Transportation Volume 2019, Article ID 5739496, 8 pages https://doi.org/10.1155/2019/5739496