|M.Sc Student||Sharif Shayma|
|Subject||Modeling Toll Lanes Demand|
|Department||Department of Civil and Environmental Engineering||Supervisor||Professor Tomer Toledo|
|Full Thesis text|
High occupancy toll lanes (HOT) are increasingly popular facilities as they allow to maintain high travel speeds for public transportation and to promote ride-sharing, while efficiently utilizing the lane excess capacity. Understanding the demand for toll lanes and the factors that affect it is critical in developing tolling strategies and pricing schemes.
Drivers that choose whether or not to use a toll lane are commonly shown variable message signs (VMS) with toll rates and in sometime travel information in various forms. They then make their decisions based on partial and inaccurate knowledge of traffic conditions. Previous research has shown that drivers systematically mispercieve travel times.
This thesis develops two models for toll lane choice scenarios using data from stated preferences (SP) experiments. The first model predicts the travel times that drivers expect to experience depending on the type and content of information they are provided with. The second model predicts the choice whether or not to use the toll lane. The results show that drivers’ expectation of the travel times on the free lanes are strongly affected by the information provided to them on the VMS. In particular, in the absence of precise travel time information they use the toll rate itself as an indicator to the expected travel times. In the choice model, there are significant differences in preferences and the related (VOT) among drivers. In particular, there are large differences in VOT between drivers who pay the toll themselves and those whose employers pay the tolls.