Feasibility of implementing high occupancy toll (HOT) lanes in Indiana

Worsening congestion, developments in electronic road pricing technology, and increased awareness of energy and environmental effects of automobile travel have heightened interest in congestion pricing in recent years as a long-term solution to reducing congestion. The types of congestion pricing that have been implemented with success in the US are high-occupancy toll and express lane systems on congested urban highways. The purpose of the present study was to determine whether the benefits of HOT or express lanes realized in other states can also be achieved in Indiana. An important process when beginning to consider HOT systems is to evaluate what toll prices and potential revenues are feasible. A significant step in this evaluation is a stated preference willingness-to-pay survey. However, the results of these surveys have been found to vary widely in different parts of the country and with changing public perception within a given region. Based on a willingness-to-pay survey conducted in Indianapolis, Indiana, it was found travelers, on average, would be willing to pay $0.60 to save 10 minutes and $0.26 to save 3 minutes for work trips. For non-work trips, travelers would be willing to pay $0.36 to save 10 minutes and $0.14 to save 3 minutes. Willingness to pay was found to be significantly lower in this study as compared to other studies conducted around the country. The results of an ordered probit model showed willingness to pay to be significantly impacted by whether a traveler uses transit, traveler’s income, age, perception of congestion, and travel time with respect to rush hour. A preliminary revenue estimation was also performed for a hypothetical 6-mile HOT lane system on I-69 in northeastern Indianapolis. An annual revenue of $422,755 was estimated for the system. The number of average weekday toll users was estimated to be at least 4,000 and the average weekday toll to travel six miles on the system was estimated to be $0.52. Based on the results of estimated revenue sensitivity analysis, it is shown that small changes in travel time savings, willingness to pay, and vehicle occupancy can impact potential system revenue significantly