This paper describes the collection and use of 1.4 million travel time records that were collected over a 12-week period in 2009 to evaluate and communicate quantifiable travel mobility metrics for a rural interstate highway work zone along I-65 in northwestern Indiana. The effort involved the automated collection and processing of Bluetooth probe data from multiple field collection sites, communicating travel delay times to the motoring public, assessing driver diversion rates, and developing proposed metrics for a state transportation agency to evaluate work zone mobility performance. Collected travel time profiles were compared with traditionally measured hourly flows in both incident and nonincident conditions. Through the 12-week period over which work zone performance was measured, the work zone had 422 h of congested conditions in which travel time delay was greater than 10 min. Despite the display of real-time delay measurements to the motoring public through portable dynamic message signs, a negligible percentage of the travel probes were observed to divert in advance of the congested work zone through self-guidance. Implementation of a targeted alternate route starting the weekend of July 24 resulted in an increase of observed probes diverting along the trail-blazed route from none to more than 30%. The paper concludes by suggesting that acquisition of work zone travel time data provides a mechanism for assessing the relationship between crashes and work zone queuing. Real-time monitoring of these travel time data may also enable future contracts to include innovative travel time reliability clauses.

Signal offsets are a signal-timing parameter that has a substantial impact on arterial travel times. The traditional technique is to optimize offsets with an offline software package, implement the settings, and then possibly observe field operations. It is not uncommon for a traffic engineer to fine-tune the settings by observing the arrivals of platoons at an intersection and making adjustments to the offset from this qualitative visual analysis. This paper discusses two tools to assist the engineer in managing arterial offsets. First, it introduces the Purdue coordination diagram (PCD) as a means of visualizing a large amount of controller and detector event data to allow investigation of the time-varying arrival patterns of coordinated movements. The second technique is arterial travel time measurement by vehicle reidentification via address matching by Bluetooth media access control. This technique is used to evaluate existing offsets and assess the impact of implemented offset changes. These tools are demonstrated with a case study involving a before-and-after comparison of an offsettuning project. PCDs were used to identify causes of poor progression in the before case, as well as to visualize both the predicted and the actual arrival patterns associated with the optimized offsets. More than 300 travel time measurements from Bluetooth probes were used for statistical assessment of before-and-after travel time. The statistical comparison showed a significant (at the 99% level) 1.7-min reduction (28%) in mean northbound travel time, corresponding to a 1.9-min reduction in median northbound travel time. Southbound travel times were not negatively affected by the offset changes.

An anonymous Bluetooth tracking system was deployed at the new Indianapolis International Airport in Indiana from May 8 to June 2, 2009, to measure the time for passengers (a) to move from the nonsterile side of the airport (presecurity), (b) to clear the security screening checkpoint, and (c) to enter the walkway to Concourse B on the sterile side. The maximum passenger transit time between these checkpoints was observed on Monday mornings at approximately 0600, when it could take passengers up to 20 min to transit the security queue and screening and to walk to Concourse B. Depending on the day of the week, this approach was demonstrated to sample between 5% and 6.8% of passengers. This modest sample size provides a more robust measurement of screening times than the current system of manually distributing time-stamped cards as passengers enter the queue and collecting them where passengers pass through the magnetometer. Furthermore, because the final passenger reference point used in this study is on the sterile concourse, it captures the time associated with passengers repackaging their belongings and redonning their shoes. The data from this pilot study suggest the feasibility of using an automated system to provide quantitative information to managers for more effective allocation of scarce resources, as well as providing the traveling public with necessary information about the amount of time they should allocate for transiting the security screening process. The paper concludes by suggesting that additional pilot studies should be performed at several airports with alternative checkpoint configurations to develop a consensus on best practices for locating sensors to measure passage times at airport security screening.

Instrument a four intersection corridor with both high resolution traffic signal controller data loggers and probe vehicle travel time measurement to actively manage the signalized corridor.