Darcy M Bullock

Input-Output and Hybrid Techniques for Real-Time Prediction of Delay and Maximum Queue Length at Signalized Intersections

Vehicle delay and queue length are quantitative measures of intersection performance. The technological advancement in the field of vehicle sensors and traffic controllers has reached a point where it has enabled efficient measurement of these performance measures. Two techniques are presented for real-time measurement of vehicle delay and queue length at a signalized intersection, and these automated delay and queue estimates are compared with manually ground-truthed measurement. These techniques were evaluated at an instrumented intersection in Noblesville, Indiana. The root-mean-square error by both techniques was below 0.7 veh-s for estimation of average delay and less than 0.15 vehicle for estimation of average maximum queue length, both on a cycle-by-cycle basis.

Event-Based Data Collection for Generating Actuated Controller Performance Measures

Cycle-by-cycle data have been shown to be effective in the analysis of a signalized intersection with measures of effectiveness such as volume-to-capacity ratios, arrival type, and average vehicular delay. Currently, actuated traffic controllers are unable to store vehicle counts and vehicle occupancy in cycle-by-cycle bins, requiring extra equipment and personnel to collect data in these bins. The objective of this research was to develop an integrated general purpose data collection module that time-stamps detector and phase state changes within a National Electrical Manufacturers Association actuated traffic signal controller and uses those data to provide quantitative graphs to assess arterial progression, phase capacity utilization, movement delay, and served volumes on a cycle-by-cycle basis. Given that the United States recently received a grade of 61 of 100 on the National Traffic Signal Report Card, it is particularly important that procedures such as these be used to provide performance measures over extended periods so agencies have cost-effective mechanisms for assessing and priority-ranking signal timing efforts.

ACS-LITE ALGORITHMIC ARCHITECTURE: APPLYING ADAPTIVE CONTROL SYSTEM TECHNOLOGY TO CLOSED-LOOP TRAFFIC SIGNAL CONTROL SYSTEMS

ACS-Lite is being developed by FHWA to be a cost-effective solution for applying adaptive control system (ACS) technology to current, state-of-the-practice closed-loop traffic signal control systems. This effort is intended to make ACS technology accessible to many jurisdictions without the upgrade and maintenance costs required to implement ACS systems that provide optimized signal timings on a second-by-second basis. The ACS-Lite system includes three major algorithmic components: a time-of-day (TOD) tuner, a run-time refiner, and a transition manager. The TOD tuner maintains plan parameters (cycle, splits, and offsets) as the long-term traffic conditions change. The run-time refiner modifies the cycle, splits, and offsets of the plan that is currently running based on observation of traffic conditions that are outside the normal bounds of conditions this plan is designed to handle. The run-time refiner also determines the best time to transition from the current plan to the next plan in the schedule, or, like a traffic-responsive system, it might transition to a plan that is not scheduled next in the sequence. The transition manager selects from the transition methods built in to the local controllers to balance the time spent out of coordination with the delay and congestion that is potentially caused by getting back into step as quickly as possible. These components of the ACS-Lite algorithm architecture are described and the similarities and differences of ACS-Lite with state-of-the-art and state-of-the-practice adaptive control algorithms are discussed. Closed-loop control system characteristics are summarized to give the context in which ACS-Lite is intended to operate.

Real-Time Offset Transitioning Algorithm for Coordinating Traffic Signals

A traffic signal offset transitioning algorithm is introduced that can be viewed as an integrated optimization approach designed to work with traditional coordinated-actuated systems. The proposed approach assumes a fixed cycle length (selected by either time of day or some traffic-responsive technique). The splits are determined by each local controller subject to maximum and minimum constraints traditionally imposed by coordinated-actuated signal systems. End-of-green offsets at each intersection are continually adjusted by the proposed algorithm with the objective of providing smooth progression of a platoon through an intersection using the volume and occupancy profile of advance detectors. The algorithm was implemented in a hardware-in-the-loop simulation and evaluated with a set of National Transportation Communications for Intelligent Transportation Systems Protocol (NTCIP) National Electrical Manufacturers Association controllers. The offsets were manipulated with NTCIP messages. The unique aspect of this algorithm is the cycle-based procedure used to tabulate volume and occupancy profiles, which can then be used to adjust the offsets in a traditional coordinated-actuated signal system. This automatic tuning process is analogous to an engineer or technician standing beside the cabinet and tuning the offset so that the coordinated phase turns green at the appropriate time to facilitate smooth progression of the upstream platoon. Because only the offsets are tuned, it is unlikely that this algorithm will be able to achieve the global optimum parameters or rapid adaptation possible with model-based approaches; nevertheless, this algorithm has the advantage of working within the framework of traditional coordinated-actuated signal systems that are familiar to system operators.

A Real-Time Simulation Environment for Evaluating Traffic Signal Systems

Features and operating modes of the current generation of actuated controllers have evolved to the point where there is a significant difference between the configuration parameters associated with an actuated controller and the information obtained from traffic signal system optimization packages such as TRANSYT 7F and PASSER II. As a result, TRANSYT 7F and PASSER II give no guidance on the impact or sensitivity of many actuated control parameters on a traffic signal system’s performance. Furthermore, none of the current generation of microscopic simulation models is detailed enough to evaluate the effect particular features, such as cycle transition algorithms or return from preemption algorithms, have on overall system performance. To address this need, an enhancement made to the CORSIM package that allows physical controllers to be connected to CORSIM is described in this paper. In this arrangement, CORSIM provides the microscopic simulation and tabulation of measures of effectiveness (MOEs). However, instead of CORSIM emulating controller features, CORSIM sends detector information to the physical controllers and reads back phase indications. This type of simulation is often referred to as hardware-in-the-loop. Since CORSIM tabulates performance MOEs, qualitative before-and-after measurements can be obtained for any hardware conforming to the NEMA TS-1 electrical standard for phase outputs and detector inputs. To validate the performance of this hardware-in-the-loop approach, an evaluation is presented that shows there is no evidence of a significant statistical difference in MOEs between the internal control algorithm and the hardware-in-the-loop control algorithm for both a fixed time and actuated controller.

Evaluation of Arterial Signal Coordination: Methodologies for Visualizing High-Resolution Event Data and Measuring Travel Time

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.

Influence of Vertical Sensor Placement on Data Collection Efficiency from Bluetooth MAC Address Collection Devices

The consumer electronics industry has made extensive use of the Bluetooth wireless protocol in many portable devices. A substantial number of these Bluetooth devices broadcast a unique identifier in the form of the media access control (MAC) addresses. These MAC addresses can be captured electronically and the same matching algorithms used in traditional license plate studies can be used to estimate segment travel time and origin-destination matrices. This paper briefly illustrates how these data can be used to estimate arterial link travel times and empirically illustrates the sensitivity of sample size to sensor placement. A controlled experiment with fixed lateral mounting and varying vertical mounting heights is then conducted to develop design recommendations for mounting Bluetooth monitoring devices. The paper concludes by recommending a Class I Bluetooth detector mounting height of at least 8 ft above the pavement grade. Based on a 24-h empirical data set on I-65 in Indianapolis, we found that 7.4%...

Impact of Emergency Vehicle Preemption on Signalized Corridor Operation: An Evaluation

A case study that examines the impact of emergency vehicle preemption on closely spaced arterial traffic signals is reported. The study was conducted on State Route (SR) 26, a principal arterial and main thoroughfare that connects Interstate 65 with US-52 on the east side of Lafayette, Indiana. Four coordinated intersections along SR-26 were examined by using seven preemption paths and three different transition algorithms (smooth, add, and dwell). The number of preemption calls in the simulation period varied from one to three for equal simulation periods. The findings generally show that a single preemption call had a minimal effect on the overall travel time and delay through the network. The results also indicate that the smooth transitioning algorithm performed the best with most scenarios and paths for both the arterial and the side streets. When multiple emergency vehicles preempt at closely spaced time intervals, the impact of preemption was more severe. For the network studied, the most severe impact on arterial travel time observed was an increase in the average arterial travel time on the order of 20 to 30 s. The study focused on emergency vehicle preemption, but the general procedures described could also be applied to railroad preemption or transit priority.

Real-Time Measurement of Travel Time Delay in Work Zones and Evaluation Metrics Using Bluetooth Probe Tracking

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.

Analysis of Freeway Travel Time Variability Using Bluetooth Detection

Travel time has long been an important performance measure for assessing traffic conditions and the extent of highway congestion. However, recently, more and more attention has been given to understanding the uncertainty regarding the variability in travel time from hour to hour and day to day—variability that is known to be a source of great frustration among road users. In this paper, travel-time variability is studied by collecting travel-time data using probe data on freeway segments in Indianapolis obtained using anonymous Bluetooth sampling techniques. The data show considerable travel-time variability is induced by adverse weather, but also show that variability results from unexpected changes in traffic flow rates and driver behavior. Various statistical models are estimated to understand the effect that traffic-related variables have on variability in individual vehicle travel times as well as average travel times. For individual vehicle travel times, a model is estimated to study how the probabi...