Evaluation of ACS Lite Adaptive Control using Sensys Arterial Travel ...

Wang, Robinson, Shelby, Cox, and Townsend

Evaluation of ACS Lite Adaptive Control using Sensys Arterial Travel Time Data Jun Wang, Ph.D., P.E. Siemens Industry, Inc. Mobility Division Traffic Solutions 5405 Metric Place Norcross, GA 30092 Phone: 770-280-2908 Email: [email protected] Ben Robinson ARCADIS 2849 Paces Ferry Road, Suite 400 Atlanta, GA 30339 Phone: (770) 431- 8666 ext. 639 Email: [email protected] Steven G. Shelby, Ph.D. Siemens Industry, Inc. Mobility Division Traffic Solutions 6375 E. Tanque Verde, Suite 170 Tucson, AZ 85715 Phone: (520) 290-8006 ext. 115 Email: [email protected] Kenneth B. Cox Sensys Networks, Inc. 2560 Ninth Street, Suite 219 Berkeley, CA 94710 Phone: (314)757-9011 Email: [email protected] Walt Towsend Siemens Industry, Inc. Mobility Division Traffic Solutions 5405 Metric Place Norcross, GA 30092 Phone: 770-280-2914 Email: [email protected]

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ABSTRACT This paper describes the deployment of an ACS Lite adaptive control system on an arterial in Atlanta, Georgia, and presents a performance evaluation including arterial travel time measures obtained using a new vehicle re-identification Sensys Arterial Travel Time System produced by Sensys Networks Inc.. The results of this study show that the deployed ACS Lite system substantially reduced arterial travel time and side-street queue lengths during peak traffic flow periods. This in turn improves system efficiency, thereby reducing vehicle emissions and fuel consumption.

INTRODUCTION This paper presents the performance benefits of an ACS Lite adaptive traffic signal control system, recently deployed on an Atlanta arterial, specifically highlight a new vehicle reidentification capability of Sensys Networks to collect arterial travel time performance measures. The document is organized into the following sections: • • • • •

An overview of ACS Lite system An overview of the Sensys arterial travel time capability ACS Lite deployment details Data collection and analysis Conclusions

OVERVIEW OF ACS LITE The Federal Highway Administration (FHWA) initiated the Adaptive Control Software Lite (ACS Lite) project to advance adaptive traffic signal control from state-of-the-art technology to state-of-the-practice technology that can be widely deployed (1, 2). The ACS Lite system was developed by Siemens, and designed specifically to address the following issues, which were identified during the requirements analysis effort as major impediments to the deployment of adaptive control (1,3,4). • • • • •

High cost Excessive complexity Uncertain benefits Hypersensitive to detection Hypersensitive to communications

The system was designated Lite by FHWA to prominently reflect the reduced burden imposed the system from a user’s perspective, which manifests in the form of significant relaxed requirements.

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ACS Lite

Communications Intersection Controllers

Detectors

Figure 1 Example of a typical ACS Lite adaptive traffic signal control system. ACS Lite System Architecture An ACS Lite system, portrayed in Figure 1 is composed of the following hardware: •

ACS Lite is deployed either as a small-scale central system on a Windows-based server at the traffic management center (TMC) or in the form of an on-street field-hardened processor replacing a legacy field master. This single processor, “centralized” architecture saves significant capital costs when compared to adaptive systems with a distributed architecture, which utilize dedicated processors at every intersection. The “on-street” configuration allows the flexibility for deployment in areas with limited communications infrastructure where adaptive traffic signal management has not historically been an option.

•

Controllers at each intersection are NEMA or 2070 model controllers, where the firmware has been upgraded to a more recent version that supports NTCIP and ACS Lite status messages.

•

Communications between ACS Lite and the controller may be IP-based, or serial, in order to retain existing twisted-pair infrastructure and forego the cost and complexity of peer-to-peer networking and fiber infrastructure. ACS Lite exchanges messages with each intersection on a per-minute basis; however, it obtains time-stamped status reports with the per-second resolution required for quality adaptive control. This infrequent messaging requirement largely eliminates the historical hypersensitivity found in adaptive systems that rely on flawless per-second real-time communications.

•

Detectors are essential to effective adaptive signal control decisions. ACS Lite is designed to leverage typical detectors layouts, as commonly located in fully actuated 3

Wang, Robinson, Shelby, Cox, and Townsend operations, using a combination of stop line detectors and advance detectors (on arterial approaches). ACS Lite processes second-by-second detector presence data, in comparison with corresponding second-by-second phase indications, and accounts for detector lengths and movement speeds in its demand estimation algorithms. This design substantially reduces the costs and the historical hypersensitivity found in adaptive systems that require detectors in uncommon locations with precise zone dimensions and precise vehicle count requirements.

Adaptive Logic ACS Lite operates by monitoring traffic signals that are running normal coordinated timing plans, computing revised coordination parameters every 5 to 10 minutes, and downloading these incremental adjustments to the intersection controllers. Second-by-second communications with each intersection are not necessary to exploit real-time flow information and exert real-time control, because each controller continues to allow phases to skip, extend, or gap-out based on real-time detectors states and according to its normal coordinated-actuated logic. Optimization of coordination parameters occurs as follows: •

Split time is reallocated to—in oversimplified terms—balance the volume-to-capacity ratio (i.e., v/c ratio or degree of saturation) across all competing phases (see Figure 2a and 2b), subject to configured minimum green times, pedestrian interval requirements, and maximum green times (when they are not inhibited during coordination). Thus, time would be reallocated from a phase with an excessively long (i.e., un-utilized) split time, to provide more split time for an oversaturated phase. Biasing logic skews the balance towards designated arterial phases, when there is sufficient “extra” capacity, to provide a wider green band and significantly improve progression. ACS Lite responds to the onset of saturation on one or more intersection approaches in a “defensive” manner that seeks to keep traffic flowing on designated arterial phases to the extent possible, and ultimately reverts to the engineer’s time-of-day allocation during complete oversaturation to provide consistency for daily commuters.

•

Offsets may be adjusted earlier or later by a few seconds at each intersection to maximize the proportion of the cyclic flow profile arriving to a green phase, amongst all designated inbound and outbound approaches to the intersection, as shown in Figure 2c. Offset adjustments are limited to small increments to eliminate any significant disruption of progression due to pattern transition.

•

Cycle length is currently not adjusted by ACS Lite, though the capability is under development. The cycle length is dictated by the “underlying” or “baseline” timing plan, which is selected according to a traditional time-of-day schedule. Despite this limitation, ACS Lite has demonstrated substantial benefits since its first deployment in 2005 (1).

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http

(a) ACS-Lite Processor

Laptop/Central

ACS Lite User Interface

(b)

(c)

Figure 2 View of the web-based user-interface featuring (a) color-coded saturation measures for each phase, (b) a ring-diagram oriented display of congestion, and (c) cyclic flow profile display.

OVERVIEW OF SENSYS ARTERIAL TRAVEL TIME The Sensys Arterial Travel Time System is an infrastructure based wireless solution that determines a distribution of vehicle travel time along an arterial roadway segment. The system

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Wang, Robinson, Shelby, Cox, and Townsend consists of an array of wireless sensors installed at strategic locations along an arterial roadway segment. Each sensor contains a 3-axis magnetometer, microprocessor, memory, low power radio, and batteries (10). After a vehicle crosses over the sensor array, each sensor transmits its unique magnetic signature and the time information to a wireless access point. The access point collects the data from each sensor or repeater and sends the information to a data archiving server through Ethernet or high speed cellular modem. Once the data archive server receives the information, the Re-ID engine server will conduct re-identification processes, where vehicles are identified at an upstream sensor array and later re-identified at a downstream array, and give the corresponding vehicle travel times. Depending on the spacing and geometry of an arterial, match rates or positive re-identification, from one array to another can range from 50-70% (10). Figure 1 below shows the typical system architecture.

Figure 3 Sensys Arterial Travel Time System Architecture

ACS LITE DEPLOYMENT In this study, an ACS Lite system was deployed on a section of Cascade Road in City of Atlanta, Georgia, as shown in Figure 4.

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Figure 4. ACS Lite deployment site on a section of Cascade Road, in Atlanta, GA.

Previous Signal System The Cascade Road corridor runs in an east-west direction and extends from the intersection at Danforth Road on the west end to the intersection at Shanter Trail on the east end. This arterial was previously managed by an Eagle MARC on-street field master with eight signalized intersections governed by Eagle 2070 controllers using SEPAC 3.32g firmware. The existing communication Infrastructure for the system was fiber optic transceivers located each controller. The system was retimed in June of 2009, by ARCADIS, as away to improve traffic flow. This area consists of single family homes, commercial business and a connection to Interstate 285, which serves as a bypass around the City of Atlanta. The posted speed limit for the system is 45 miles per hour (mph). All eight intersections use video detectors. However, due to problems with video processors on some intersections, this study only includes five adjacent intersections, including Fairburn, Publix, Utoy, I-285 SB, and I-285 NB, as shown in Figure 5.

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Figure 5 Study Arterial The Sensys Arterial Travel Time System was installed as a pilot project at the intersections of Danforth, Fairburn, Utoy Springs, I-285 SB, I-285 NB, and Cascade Parkway to provide travel time data for the arterial road segments between these intersections. ACS Lite utilizes the National Transportation Communications for ITS Protocol (NTCIP), and thus the controller firmware must support NTICP. ACS Lite communicates with each controller by polling both standard NTICP and ACS Lite objects that provides phase and detector data. In this study, the deployment of ACS Lite included the following tasks: • Upgrade controller firmware • Convert controller database • Set up detectors • System Integration

Firmware Upgrade The firmware (controller software) for each controller on the arterial was upgraded from Eagle SEPAC 3.32g to Eagle SEPAC NTCIP 4.01f. New firmware can be transferred from a laptop computer to the controller over a serial or Ethernet connection. The upgrade process can typically be completed in approximately five minutes when an Ethernet connection is available, or roughly half an hour when only the serial connection is available at 36400 baud.

Database Conversion The database conversion from ECOM (non-NTCIP) database to the NTCIP format is currently a manual process. The ECOM database uses Dial/Split/Offset to represents various plans and the NTCIP database uses pattern numbers. The SEPAC supports 6 dials, 6 splits, and 3 offsets. The following table shows the mapping between Eagle ECOM Dial/Split/Offset and NTCIP pattern numbers. 8


Eagle ECOM D/S/O 1/1/1 1/1/2 1/1/3 1/2/1 1/2/2 1/2/3 … 6/6/1 6/6/2 6/6/3

NTCIP Pattern 1 2 3 4 5 6 … 106 107 108

Table 1 Mapping between ECOM Dial/Split/Offset and NTCIP pattern An effective workflow for upgrading the arterial is to obtain a spare controller an upgrade it with the firmware and manually reconfigured database for the first intersection. Then, switch controllers in the cabinet to minimize signal downtime. The old controller retrieved from one intersection can be upgraded and configured to switch out the next intersection, and thus sequentially upgrade all intersections along an arterial.

Detector Setup ACS Lite uses stop-bar detectors for split tuning and advance detectors for offset tuning. At least one stop-bar detector is required for each phase where split tuning is desired. However, better performance can be achieved with one detector per lane (with separate lead-in cables and amplifier cards for each individual lane detector) (5). At least one advance detector is required on approaches where offset tuning is desired to improve progression (only the arterial approaches in this case). Again, better performance can be achieved with one detector per lane (with separate lead-in cables and an amplifier cards for each individual lane detector) on the designated progression approaches. In this study, all intersections have already had video detection for stop-bar detectors. The authors adjusted the existing video detection cameras to also detect vehicles exiting the intersection allowing the cameras to be used as advanced detectors for the next intersection. This method made it possible to add advance detection without adding any new detection hardware. The following figure shows the typical detector layout for one of the intersections.

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Figure 6 Intersection Detector Layout

System Integration ACS Lite can be deployed on either a central workstation or in the field on an embedded, fieldhardened computer. In this study, ACS Lite was deployed on a central workstation running inside the Fulton County traffic management office. The master controller of the previous closed-loop system utilized fiber connections to other controllers. In this study, a Comcast cable modem was installed in the controller cabinet where the master was previously located, to establish a permanent communications link between the central office and the arterial network. All intersections are connected to the first cabinet through serial connections operating at 19200 baud, as shown in the following figure. ACS Lite communicates with the controller in the first cabinet through Ethernet, but utilizes the serial connections for the other controllers. Using the fiber to provide Ethernet connections to all controllers would have provided better performance, but the project budget was not sufficient to provide the necessary Ethernet switches.

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Figure 7 System Architecture

DATA COLLECTION AND ANALYSIS This study collected arterial travel times for both directions and the queue length at side streets to do the before-and-after study. The arterial travel time is the travel time between the intersection of Fairburn and I-285 NB, which is collected by the Sensys Arterial Travel Time System. The travel time used in this study is the median travel time (50th percentile). Appendix A shows an example of the travel time data. Queue length data was collected manually by a team of five peoples stationed at each intersection to record the maximum number of vehicles in the queue at the onset of each green cycle (Appendix B). The before data was collected during the morning peak time (7:30 to 8:30 AM) and evening peak time (4:30 to 5:30 PM) on November 5th, 2009 and November 12th, 2009, two consecutive Thursdays. The traffic volumes on the arterial were also provided by ACS Lite archive data. The results indicates that the traffic volumes are very close during these time periods (Appendix C).

Before-and-After Travel Time Analysis The Sensys Arterial Travel Time System provides aggregated minute-by-minute arterial travel time data. Figure 8 compares the before-and-after travel time on the arterial from intersection of Fairburn to Utoy. The results indicate there is a clear pattern of reduced travel time along this road segment. The zero travel time represents an invalid data points. Individual per-minute data points where an invalid data point was observed for either the before or after scenario were discarded for both scenarios to preserve an unbiased comparison.

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Arterial Travel Time Comparison (Eastbound)

120 100 80

Before

60

After

40 20 8:28:00 AM

8:25:00 AM

8:22:00 AM

8:19:00 AM

8:16:00 AM

8:13:00 AM

8:10:00 AM

8:07:00 AM

8:04:00 AM

8:01:00 AM

7:58:00 AM

7:55:00 AM

7:52:00 AM

7:49:00 AM

7:46:00 AM

7:43:00 AM

7:40:00 AM

7:37:00 AM

7:34:00 AM

0 7:31:00 AM

Travel Time (seconds)

140

Figure 8 Arterial Minute-by-Minute Travel Time Comparison Table 2 compares the total travel time (seconds) of this corridor when drivers travel from intersection of Fairburn to I-285 NB (Eastbound) and from I-285 NB (Westbound) to Fairburn. Morning Peak EB: Fairburn to I-285 NB WB: I-285 NB to Fairburn Evening Peak EB: Fairburn to I-285 NB WB: I-285NB to Fairburn

Before 67 122

After 46 103

Reduction 32% 16%

Before 159 146

After 136 136

Reduction 14% 6%

Table 2 Arterial Total Travel Time Comparison The results indicate that eastbound (EB) travel time reduced 32% during morning peak and 14% during evening peak, and westbound (WB) travel time reduced 16% during morning peak and 6% during evening peak. The results are also displayed in graphic view in Figure 9.

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Figure 9 Before-and-After Arterial Travel Time One thing to note is the limited data from Sensys Arterial Travel Time System for the road segments between Utoy to I-285 SB, and I-285 SB to I-285 NB during the morning peak time. Therefore, the study only compares the travel time from Fairburn to Utoy, instead of Fairburn to I-285 NB. This is why the travel time is much shorter compared to evening peak time.

Before-and-After Queue Length Analysis Queue length is collected by personal observation at each intersection during the morning and evening peak time. Figure 10 and Figure 11 present the before-and-after queue length for side streets at five intersections.

Side Street Queue Comparison (Morning) Number of cars in the queue

25.0 19.3 20.1

20.0 15.0

14.9

14.4

13.3

10.0

Before

11.3

10.4

After 7.6

5.0

2.4 2.5

0.0 I-285 NB

I-285 SB

Utoy

Publix

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Fairburn

Wang, Robinson, Shelby, Cox, and Townsend Figure 10 Side Street Queue Lengths by Intersections during Moring Peak

Side Street Queue Comparison (Evening) Number of cars in the queue

35.0 30.3 30.0

26.8

25.0

25.4 21.4

20.0 15.0

17.2 17.3

Before

13.2

After 10.7

9.2 8.6

10.0 5.0 0.0 I-285 NB

I-285 SB

Utoy

Publix

Fairburn

Figure 11 Side Street Queue Lengths by Intersections during Evening Peak

The results indicate there is a significant reduction of queue length on side streets, especially on the I-285 NB and I-285 SB freeway ramps. However, some intersections show no reduction of queue length on side streets during the morning or evening peak time. ACS Lite only allocates more split time to side streets when there is high demand on side streets and the main street is not oversaturated (i.e., there is still minimally adequate “slack” green time on main streets). ACS Lite provides a “biasing” feature, whereby users can designate which (if any) phases to favor when there is ample slack time in the cycle after serving demands on all phases. Typically, biasing is enabled only for the coordinated (arterial through) phases on arterial intersections, which has the effect of increasing the green band on the arterial and significantly improving progression. However, biasing may also be appropriate (for example) for all four through phases in the context of an intersection of crossing arterials. For the freeway ramps, there is very high demand on the ramp during peak time and thus biasing was enabled for both the side-street (ramp) phase in addition to the main street through phases (phase 2 and phase 6). For other intersections, biasing was only enabled for the coordination phases on the main-street approaches (phase 2 and 6). This may explain why the two freeway ramps experienced more significant queue length reductions than the side-street approaches at other intersections, where biasing was not enabled for the side-street phases. For other intersections, main street phases were given more weight than side streets. In this case, if the traffic demand on both the side streets and main streets are both high, ACS Lite will try to allocate green time to the main streets instead of side streets. This is why there was no decrease in queue length on some of the side streets.

CONCLUSIONS This study conducted a before-and-after study to measure the arterial travel time and the queue length at the side streets on two consecutive Thursdays, with ACS Lite adaptive control enabled only on the second Thursday. The results indicate that the ACS Lite system effectively reduced the travel time on the arterial while simultaneously reducing queue length at side streets, during

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Wang, Robinson, Shelby, Cox, and Townsend peak periods, resulting in improved system efficiency, reduced emission and reduced fuel consumption. The following are the major finds of this study: •

•

•

Eastbound travel time was reduced 32% during morning peak and 14% during evening peak. Westbound travel time was reduced 16% during morning peak and 6% during evening peak. Significant reduction of queue length on the side streets, especially on the freeway ramps. I-285 NB ramp has a 21% and 19% reduction in queue length during morning and evening peak. I-285 SB ramp has a 48% and 20% reduction in queue length during morning and evening peak. The traffic volumes on the arterial during the before-and-after time period are very similar, therefore excluding the traffic volume as a factor in the travel time reduction.

ACKNOWLEDGEMENTS This study was conducted by Siemens Traffic Solutions, Arcadis, Inc., Sensys Networks Inc., and Fulton County, Georgia.

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REFERENCES 1. Shelby, S., Bullock, D., Gettman, D., Ghaman, R., Sabra, Z., and Soyke, N. An Overview and Performance Evaluation of ACS Lite – A Low Cost Adaptive Signal Control. In TRB 87th Annual Meeting Compendium of Papers DVD, Transportation Research Board, 2008. 2. Curtis, E., and Shelby, S. How ACS Lite improves traffic signal timing on closed loop traffic signal systems. Journal of Public Works and Infrastructure, Vol. 1, No. 4, March, 2009. 3. Hicks, B. and Carter, M. What Have We Learned About ITS? Arterial Management Systems. Chapter 3 in What Have We Learned About Intelligent Transportation Systems. FHWA, 2000. 4. Crenshaw, P. FHWA Adaptive Control Survey. Presented at the 2000 Mid-Year Signal Systems Committee Meeting, Seattle, WA, 2000. 5. Adrienne Graham, Study Shows Tyler Commutes Running Smoother, http://www.tylerpaper.com/article/20071209/NEWS08/712080377 6. ACS Lite User Manual 7. Sabra, Wang & Associates. Adaptive Control Software – LITE Before and After Traffic Analysis, Hamilton Road – City of Gahanna, Ohio. December, 2005. 8. Sabra, Wang & Associates. Adaptive Control Software – LITE Before and After Traffic Analysis, State Highway 6 – City of Houston, Texas. March, 2005. 9. Sabra, Wang & Associates. Adaptive Control Software – LITE Before and After Traffic Analysis, State Highway 70 – City of Bradenton, Florida. September, 2006. 10. Volling, Michael T. Arterial Travel Time Using Magnetic Signature Re-identification Theory of Application and ITS Deployment in San Diego. ITS America, 2009.

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APPENDIX A. Sensys Arterial Travel Time Example ID 004003 004003 004003 004003 004003 004003 004003 004003 004003 004003

Time 2009/11/05 07:31:00 2009/11/05 07:32:00 2009/11/05 07:33:00 2009/11/05 07:34:00 2009/11/05 07:35:00 2009/11/05 07:36:00 2009/11/05 07:37:00 2009/11/05 07:38:00 2009/11/05 07:39:00 2009/11/05 07:40:00

Travel Time 48 47 78 66 30 71 33 81 26 67

Time 2009/11/12 07:31:00 2009/11/12 07:32:00 2009/11/12 07:33:00 2009/11/12 07:34:00 2009/11/12 07:35:00 2009/11/12 07:36:00 2009/11/12 07:37:00 2009/11/12 07:38:00 2009/11/12 07:39:00 2009/11/12 07:40:00

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Travel Time 81 24 64 27 24 53 27 61 27 53


APPENDIX B. Queue Length at Side Streets Morning Peak I-285NB I-285SB Utoy Publix Fairburn Average Evening Peak I-285NB I-285SB Utoy Publix Fairburn Average

Before 13.3 14.4 14.9 2.4 19.3 12.9

After 10.4 7.6 11.3 2.5 20.1 10.3

Reduction 21% 48% 24% -1% -4% 20%

Before 13.2 26.8 17.2 9.2 30.3 19.3

After 10.7 21.4 17.3 8.6 25.4 16.7

Reduction 19% 20% -1% 7% 16% 14%

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APPENDIX C. Traffic Volume on Main Street Eastbound

Fairburn -> Publix Publix -> Utoy Utoy -> I-285SB I-285SB -> I-285NB Total Westbound

I-285NB -> I-285SB I-285SB -> Utoy Utoy -> Publix Publix -> Fairburn Total

Before Morning Peak Evening Peak 973 698 933 767 774 776 666 558 3346 2799

After Morning Peak Evening Peak 915 984 568 892 1196 747 710 512 3389 3135

Before Morning Peak Evening Peak 509 719 815 1231 321 257 723 795 2368 3002

After Morning Peak Evening Peak 499 719 805 1216 211 258 564 900 2079 3093

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