Development of a Methodology to Predict Through-Trip Rates for Small Communities Michael D. Anderson 1 ; Yasir M. Abdullah 2 ; Sampson E. Gholston 3 ; and Steven L. Jones 4 Abstract: This paper examines a new methodology to predict external trip exchanges in small urban communities. The paper documents a study performed on several small communities in Alabama and includes a video surveillance data collection methodology, data analysis, model development, and test versus existing models. The new model presented in this paper is shown to provide more accurate results when compared to existing models and demonstrated transferability to a similar city. DOI: 10.1061/ASCE0733-94882006132:2112 CE Database subject headings: Methodology; Urban areas; Alabama; Traffic surveillance; Transportation management. Introduction and Background Transportation planning activities in small urban areas are becom- ing increasingly important, as the popularity of smaller commu- nities has increased over the past several decades. Unfortunately, the growth in popularity of smaller communities has resulted in increased transportation problems related to safety and congestion Khisty and Rahi 1990. In addition, the tools and methods used to solve transportation problems in larger urban areas are often not applicable in smaller communities due to knowledge and bud- get limitation, especially when examining congestion and the use of infrastructure improvements to alleviation of congestion. Pass through trips represent a main area of concern for smaller urban communities as these trips contribute to congestion, but often to not enhance the economic condition or general welfare of the community. In 1982, Modlin concluded that studies to identify and predict transportation infrastructure needs in smaller commu- nities were limited and many of the completed studies to synthe- size through-trip tables in these communities were outdated Modlin 1982. Currently, the principle methodology for determining through- trip rates cited in the literature involves the application of a series of regression models, that were developed from data collected in the early 1980s. The models use functional classification, the average daily traffic ADT at the external station, the percentage of trucks excluding vans and pickups, the percentage of vans and pickups, and the population of the study area in a two-step equation to predict the external trip exchange Martin and McGuckin 1998. As an alternative, Anderson presented a spatial economic model to synthesize a through trip table that incorpo- rates surrounding communities and their impact, and although this model has not seen widespread use, it was shown to be more accurate than the common regression-based model for limited ap- plications Anderson 1999; Anderson and Souleyrette 2000. This paper presents a new model to predict the percent through trips in small urban areas, using limited and readily available data. The methodology proposed is developed specifically for ap- plication in communities with populations below 50,000. This paper presents a data collection effort conducted to construct and validate a new methodology to develop a through-trip table for smaller communities. The new model will then be tested against existing published models to compare results and concludes the updated model better reflects current travel conditions and incorporates a new component to account for the impact of neigh- boring communities or infrastructure facilities. Methodology and Case Study The methodology adopted to develop the through-trip prediction model for smaller urban communities required a significant data collection effort and statistical analysis of the collected data. The data collection effort undertaken involved a nonintrusive video data license plate collection scheme for several communities within Alabama. The communities were selected depending on a variety of considerations, specifically proximity to other major cities, population, economic considerations, and geographical lo- cation. The communities studied were Alexander City population 15,008, Arab population 7,174, Hartselle population 12,019, Roanoke population 6,563, Russellville population 8,971, Sylacauga population 12,616, and Troy population 13,935, all in Alabama. Nonintrusive video surveillance was used to collect vehicle travel information. Data were collected for all major roadways entering and leaving the study communities by placing two cam- eras at each location. Standard video recorders with 90 min 1 Associate Professor, Dept. of Civil Engineering, The Univ. of Alabama in Huntsville, Huntsville, AL 35899. 2 Research Associate, Dept. of Civil Engineering, The Univ. of Alabama in Huntsville, Huntsville, AL 35899; formerly, Data Acquisition Assistant. 3 Associate Professor, Dept. of Industrial Systems Engineering and Engineering Management, The Univ. of Alabama in Huntsville, Huntsville, AL 35899. 4 Assistant Professor, Dept. of Civil Engineering, The Univ. of Alabama, Tuscaloosa, AL 35487. Note. Discussion open until November 1, 2006. Separate discussions must be submitted for individual papers. To extend the closing date by one month, a written request must be filed with the ASCE Managing Editor. The manuscript for this paper was submitted for review and pos- sible publication on September 7, 2004; approved on August 25, 2005. This paper is part of the Journal of Urban Planning and Development, Vol. 132, No. 2, June 1, 2006. ©ASCE, ISSN 0733-9488/2006/2-112– 114/$25.00. 112 / JOURNAL OF URBAN PLANNING AND DEVELOPMENT © ASCE / JUNE 2006 J. Urban Plann. Dev., 2006, 132(2): 112-114 Downloaded from ascelibrary.org by U OF ALA LIB/SERIALS on 10/10/20. Copyright ASCE. For personal use only; all rights reserved.