Incremental Accessibility Benefits and HOT Lane Subscription Choice

This paper presents the results of an investigation into the factors contributing to toll lane subscription choice using data from the MnPASS HOT lane system operated by the Minnesota Department of Transportation. A binomial logit model is estimated which predicts the likelihood that a household will have a subscription to the MnPASS system based on aggregate characteristics of the surrounding area. Variables in this model include demographic factors as well as an estimate of the incremental accessibility benefit provided by the MnPASS system. This benefit is estimated using detailed accessibility calculations. The model achieves a ρ value of 0.634, and analysis of the results suggest that incremental accessibility benefits play a statistically and practically significant role in determining how likely households are to hold a toll lane subscription. Owen, Janson, and Levinson 2 INTRODUCTION 1 The majority of research related to high-occupancy/toll (HOT) lanes and other types of toll lanes 2 takes place at the route choice level, investigating the factors that cause travelers to select a toll 3 lane during a single trip or as a part of a typical commute route. However, the electronic toll 4 collection (ETC) systems commonly used in urban toll lane systems add another layer to travelers’ 5 decision-making process that is typically not considered explicitly. ETC systems typically require 6 travelers to carry transponders, cards, or similar devices if they plan to use electronically-tolled 7 facilities. This equipment is typically available at low or no cost, but there are no known instances 8 of toll lane systems where transponders are provided preemptively; enrollment in toll lane systems 9 requires some action or expense by potential users. Before a traveler is ever presented with the 10 option of entering a toll lane, he or she must decide to become an eligible HOT lane user. 11 This analysis investigates the factors contributing to toll lane subscription choice using data 12 from the MnPASS HOT lane system operated by the Minnesota Department of Transportation 13 (MnDOT). A binomial choice model is estimated which predicts the likelihood that a household will 14 have a subscription to the MnPASS system based on aggregate characteristics of the surrounding 15 area. Variables in this model include demographic factors as well as an estimate of the incremental 16 accessibility benefit provided by the MnPASS system. This benefit is estimated at the transportation 17 analysis zone (TAZ) level using detailed accessibility calculations. It is hypothesized that in areas 18 where access to the MnPASS system would provide a greater increase in accessibility to jobs, 19 households are more likely to have MnPASS subscriptions. 20 The next section provides a background discussion of the MnPASS system and toll lanes in 21 general, as well as the application of accessibility evaluation and transportation choice modeling in 22 this context. Subsequent sections describe the data and methods employed in this analysis, followed 23 by a presentation and discussion of the model results and performance. 24 BACKGROUND 25 The MnPASS System 26 MnDOT began operating eastbound and westbound HOT lanes on I-394 west of downtown Min27 neapolis in May of 2005. In 2009, the system was expanded to include northbound and southbound 28 HOT lanes on I-35W south of downtown Minneapolis. Figure 1 illustrates the location of MnPASS 29 lanes within in the Twin Cities area. During peak periods, access to these lanes is restricted to ve30 hicles with two or more occupants and those paying a toll for access. Outside of the peak periods, 31 the lanes are open to general traffic. The toll varies from a minimum of $0.25 to a maximum of 32 $8.00, and is dynamically adjusted based on the current utilization of the MnPASS lanes. Tolls 33 are collected electronically; vehicles must carry a transponder which is provided by MnDOT after 34 participants enroll using a web site, by mail, or in person. Transponders are leased at a rate of 35 $1.50/month. (1, 2, 3) 36 Toll Lanes and Electronic Toll Collection 37 Toll lanes using transponder-based electronic toll collection (ETC) are a relatively young trans38 portation technology, and data collection methods have become established only over the past 39 decade. Li et al. (4) and Li et al. (5) provide a template for analyzing HOT lane usage and be40 havior using two important sources of data: toll collection records, which capture every interaction 41 that subscribers have with the HOT lane system, and GPS-based surveys which capture detailed 42 trip logs, regardless of whether a HOT lane is used. To fully understand traveler behavior in a HOT 43 Owen, Janson, and Levinson 3 lane system both must be used, since toll collection records alone cannot reveal traveler behavior 44 when a HOT lane is not used. (However, some ETC systems, such as Georgia’s PeachPass, employ 45 transponder readers in non-tolled lanes to provide this information.) 46 Burris and Stockton (6) highlight the importance of understanding the economics and be47 havior associated with HOT lanes. They chronicle the results of several variations of HOV and 48 HOT policies in Houston, where HOT lane pricing was implemented as a tool to more effectively 49 guide an appropriate level of demand into the lane, while preserving travel time reliability. This 50 importance is compounded by the fact that traveler behavior in HOT lane systems is often coun51 terintuitive, as illustrated by Liu et al. (7), where higher HOT lane prices were found to increase 52 demand. Janson and Levinson (8) found similar results through an investigation of user behavior 53 on the MnPASS HOT lanes which included experimental price modifications in the field. Goodall 54 and Smith (2) apply transportation choice theory in the context of HOT lanes. Their findings sug55 gest that travel time reliability, rather than expected travel time savings, drives both the choice to 56 enroll in HOT lane programs and the choice to use a HOT lane on a per-trip basis. Small et al. (9) 57 and Brownstone and Small (10) also investigate travelers’ valuation of travel time and reliability. 58 These and many other studies focus on the choices made by travelers when they decide 59 whether to use a toll lane during an individual trip. But electronic toll collection systems add another 60 layer of choice to the decisions facing potential toll lane users: the decision of whether to enroll 61 in the system. Enrolling in a HOT lane system is in most cases low-cost or free from a financial 62 standpoint, but it always requires some expense from users in the form of time spent processing 63 enrollment forms and managing accounts. Additionally, enrollment involves some risk: electronic 64 toll systems typically charge users for lost or damaged transponders. (11) The importance of the 65 subscription choice was recognized by MnDOT in their consideration of how to (and whether to) 66 market the I-394 MnPASS lanes when they began operation in 2005. They recognized that because 67 a subscription is required to use the system, the number of subscribers effectively caps the maximum 68 demand that the system could experience. (2, 12) 69 Parkany (13) directly investigates subscription choice in the context of tolled express lanes 70 in Orange County, CA, applying a logit-based choice model. The findings establish that having a 71 toll lane subscription is more determinative of toll lane use than demographic or trip characteristic 72 factors. A later study by Parkany (11) examines more closely the role that enrollment costs play in 73 determining how much, when, and by whom toll lanes are used. Similarly, Levinson and Chang (14) 74 incorporate the cost (both monetary and temporal) of enrollment in a model designed to maximize 75 the social welfare of an ETC system, and find these costs to be a key factor in toll lane usage and 76 outcomes. 77 Because of the costs (however small) associated with subscribing to a toll lane program, 78 it is reasonable to expect that people who would receive no benefit from the ability to use HOT 79 lanes will not enroll in a HOT lane toll collection program. Conversely, it is intuitive that a person 80 who would receive a very large benefit from enrollment — perhaps a much shorter or much more 81 reliable commute duration — would be very likely to enroll. 82 Accessibility 83 Accessibility combines the simpler concept of mobility with an understanding that travel is driven 84 by a desire to reach destinations. It is important to distinguish between individual accessibility and 85 locational accessibility: the former seeks to characterize the ease with which travelers might reach 86 their destinations, subject to constraints of ability, budget, and other barriers; the latter examines 87 Owen, Janson, and Levinson 4 accessibility as a spatial phenomenon by considering the costs and benefits of the potential trips 88 offered by transportation systems between origins and destinations of interest. 89 Horner (15) explored this distinction in the literature and notes that individual accessibil90 ity measures are generally poor at “producing . generalized assessments of intraurban structure,” 91 while locational accessibility measures are more useful for “understanding relationships between 92 transportation and land use. ” Locational accessibility can be a particularly useful tool for transporta93 tion planners because it provides a way to evaluate the properties of transportation systems at a level 94 that is aggregate enough to avoid the vagaries of individual users’ preferences and constraints, but 95 still detailed enough to provide guidance for planning at the city and regional level. 96 Many different implementations of locational accessibility measurement are possible. El97 Geneidy and Levinson (16) and provide a practical overview of historical and contemporary ap98 proaches. Perhaps the