Connected vehicle (CV) technology can connect, communicate, and share information between vehicles, infrastructure, and other traffic management systems. Recent research has examined and promoted CV and connected automated vehicle (CAV) technology on managed lane systems to increase capacity and reduce congestion, as managed lane systems could be equipped with advanced infrastructure relatively quickly. However, the effect on travel considering, information-based managed lane choice decisions in a CV environment is not clear. Therefore, this research analyzed the potential effects on a managed lane system with connected vehicles considering several travel behavior elements, including drivers’ willingness to reroute and their choice of managed lanes based on individual travel time savings. This study analyzed the potential effects on a managed lane system by assigning different market penetration rates (0%, 10%, 50%, 100%) of CVs and informing CV drivers about travel time savings for a 10-mi stretch at 5-min intervals. How the traffic performance measurements (i.e., throughput, travel time saving, average speed and average travel time) vary under different market penetration rates of CVs is then investigated. Two major conclusions are reached: (i) although information exchange was assumed to be instantaneous between vehicles and the system, there existed a response time (or time delay) in the macroscopic traffic reflection; (ii) managed lane use may decrease, when travel time information becomes available, since drivers perceive they are saving more travel time than they actually do save.

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Tolled managed lanes (ML) are an innovative way to increase capacity and regulate demand on roadways. They are still relatively new and a lot remains unknown about how travelers choose to use MLs or not. This paper uses disaggregate real-world travel data of travelers who choose between paying a toll to use ML or travel toll free on the adjacent general purpose lanes (GPL). The travel behavior before and after a toll increase is evaluated. The change in toll rates did not affect the overall ML use as anticipated. Overall, ML use increased after the toll increase. In addition, frequent ML users (more than 10 ML trips in a month) and infrequent ML users (1–3 ML trips in a month) behaved differently following the increase in the toll.

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Priced managed lanes (MLs) offer travelers an option to choose to pay a toll to travel on the MLs for a generally faster, more reliable travel than on the adjacent, toll-free general-purpose lanes (GPLs). Recent research has shown that many travelers on freeways with MLs choose the same lane type every trip regardless of travel time savings and toll rate. In this paper, a classic experimental economics traffic game was replicated and re-examined to model traveler choice by classifying travelers as “choosers” (people who frequently choose between MLs and GPLs) and “non-choosers” (people who use only one type of lane). This traffic experiment was then augmented with a travel survey to find the individual differences (psychological traits), trip-related variables, and socio-demographic variables that help differentiate travelers into the above two categories. Based on the traffic experiment and travel survey, it was found that: (1) the experiment could identify real life choosers and (2) many more travelers indicate that they are choosers in a survey than in actual travel. Features that are related to the choosing behavior were the time taken by the subject to answer a survey section and time used to verify their answers before submitting. Participants who spent more time on those things tended to be choosers. Travelers who were direct responders in the experiment tended to be choosers. Other factors that differentiated choosers from non-choosers were trip duration, familiarity with the ML facilities, and education level.