摘要
The use of managed lanes to control and maximize freeway throughput is increasing. One way of encouraging more managed lane use is through the implementation of incentives. In the Dallas-Fort Worth area, a managed lane is being added to the I-30 (Tom Landry freeway) and incentives to maximize the use of this lane were planned. Since the managed lanes were not yet open and the incentives were hypothetical, a stated preference survey was used to gauge the potential impact of the incentives on traveler behavior. The stated preference questions were designed using Db-efficient and random adaptive designs. The incentives were chosen by looking at other programs around the country and through discussion with transportation experts. Once ready, the survey was administered online to travelers in the area and a total of 898 usable responses were gathered. From the responses, a mixed-logit model was developed to describe and predict traveler behavior. From the model, elasticities were calculated to predict the impact of the incentives on mode choice. The model found that incentives with discounts and free trips (a transit fare discount, express bus service to downtown, a free trip for every X number of paid trips, and a discount offered to select businesses) were more effective at encouraging managed lane use. The other incentives (gift card worth $5 for every X number of trips and $5 in credit for every X number of trips taken by transit) had less of an impact.
The use of managed lanes to control and maximize freeway throughput is increasing. One way of encouraging more managed lane use is through the implementation of incentives. In the Dallas-Fort Worth area, a managed lane is being added to the I-30 (Tom Landry freeway) and incentives to maximize the use of this lane were planned. Since the managed lanes were not yet open and the incentives were hypothetical, a stated preference survey was used to gauge the potential impact of the incentives on traveler behavior. The stated preference questions were designed using Db-efficient and random adaptive designs. The incentives were chosen by looking at other programs around the country and through discussion with transportation experts. Once ready, the survey was administered online to travelers in the area and a total of 898 usable responses were gathered. From the responses, a mixed-logit model was developed to describe and predict traveler behavior. From the model, elasticities were calculated to predict the impact of the incentives on mode choice. The model found that incentives with discounts and free trips (a transit fare discount, express bus service to downtown, a free trip for every X number of paid trips, and a discount offered to select businesses) were more effective at encouraging managed lane use. The other incentives (gift card worth $5 for every X number of trips and $5 in credit for every X number of trips taken by transit) had less of an impact.
