4. OPERATIONS AND MAINTENANCE APPLICATIONS

            In order to effectively identify which ITS-generated data are relevant to operations and maintenance applications, it is important to understand the functions to which transportation operations and maintenance refer. Although “safety, reliability, and security” seem to be the terms that effectively convey the key goals of transportation operations, a clear concise definition of operations that articulates the scope and intent of the activities it comprises is being developed.^4.1

            Nonetheless, “optimizing the performance of the existing system to meet or exceed varying customer expectations under varying conditions” seems to be a reasonable objective for beginning the process of building the future of transportation operations.^4.2 To reach that objective, Dr. Johnson urged solving the four “real” transportation problems facing the nation: congestion, public safety, work zones, and weather response. Public safety refers to transportation safety and efficiency that are enabled by effective police, fire, and emergency operations. “Security” was added to the list, in response to the tragedy of September 11^th.

            The state-of-the-practice review of archiving and using ITS-generated data on operations and maintenance applications focused on data elements that have the potential to solve those aforementioned problems. This includes data generated from almost all of the nine ITS components.

4.1 STATE-OF-THE-PRACTICE REVIEW

4.1.1 Archiving and Sharing ITS-Generated Roadway/Traffic Data

            The ITS infrastructure elements pertinent to generating traffic and roadway data include: traffic signal control systems in Arterial Management Systems, Freeway Management Systems, Incident Management Programs, Transit Management Systems, Electronic Toll Collection, Advanced Rail-Highway Crossings, Regional Multimodal Traveler Information, and Emergency Response. Many of these activities are concentrated within metropolitan areas. The objectives of these deployments range from reducing congestion and delays, to providing drivers/travelers with real-time choices, to saving lives through accessible emergency response, to improving on-time transit performance.

            One hundred and six agencies responded to the Freeway Management Survey in both 1999 and 2000. Almost one in three responding agencies in 1999 did not collect any freeway data while this percentage increased to almost 40% in 2000 (Table 4.1). Data collected from this Freeway Management survey range from traffic volume, to information related to intermodal connections. By far the most commonly collected freeway data are: traffic volume, and information on scheduled work zones (Figure 4.1). The most common technique used to collect traffic data is loop detectors, followed by video imaging detectors. Figure 4.2 depicts the prominence of different techniques used to collect traffic data. It is obvious from this figure that less intrusive technologies are becoming popular in collecting traffic data. Traffic volume and vehicle classification data are the two data elements that are most likely to be archived. Eighty-seven percent of the agencies in 1999 that collected traffic volume data also archive them. And, seventy-six percent of the agencies that collect vehicle classification data also archive them (Table 4.1). The most noteworthy observation is the fewer number of agencies that generate and archive lane occupancy data, declining from 39 agencies in the year 1999 to 6 in year 2000. We speculate that data reporting errors led to the downward trend from 1999 to 2000 in terms of fewer data elements being generated and/or archived. Ramp metering has the potential to significantly reduce the traffic flow impediment. Thirty-nine of the 106 responding agencies reportedly operate entrance ramp meters within their planning boundary. However, less than one third of those agencies collect data related to ramp metering (Table 4.1).

    Table 4.1 Number of Agencies that Generated and/or Archived Freeway Traffic Data

1999 and 2000 ITS Deployment Tracking Surveys

                  * These questions were not asked in 1999

                  ** These questions were not asked in 2000

            Tables 4.2 and 4.3 show the propensity for data archiving in 1999 and 2000, with a significant downward trend. No agencies collect all seventeen data elements identified on the survey questionnaire. In 1999 one agency collected 14 of out the 17 data elements and it archived every data element collected. Overall, 31 of the 78 agencies in 1999 archived all of the traffic data collected (cells on the diagonal line) while the corresponding numbers are 19 out of 66 agencies in year 2000. In 1000 ten agencies reportedly collected traffic data but did not archive any (the “0“ column).

Table 4.2 Distribution of Agencies by Number of Data Elements Generated and Number of Data Elements Archived

1999 ITS Deployment Tracking Survey

Table 4.3 Distribution of Agencies* by Number of Data Elements Generated and Number of Data Elements Archived

2000 ITS Deployment Tracking Survey

* Excludes agencies that archived more data elements than they actually collected.

4.1.2 Usage and Users of the Archived Freeway Data

            Based on the tracking survey results, the media is the largest archived data requester/user, followed by state Departments of Transportation (Figure 4.3). The archived traffic data are primarily used for traffic analysis and planning (Figure 4.4). However, the specific applications of the analysis are unclear from the surveys. It is also unclear which of the users use which of the archived data and for what purpose.

4.1.3 Barriers to Freeway Data Archiving

            To avoid reporting burden, ORNL only contacted a limited number of agencies for questions more specifically related to data archiving. For those agencies that did not archive any data generated, the reasons given were: (1) lack of need to archive, and (2) lack of necessary hardware, storage capacity, and resources (either human or monetary) to archive. Lack of articulated needs was the overarching reason for those agencies that archived part, but not all, of the data elements.

4.1.4 Archiving and Sharing ITS-Generated Emergency Response and Work Zone Data

            Other data elements specifically pertinent to operations and maintenance application are:

            ●          Information on current and scheduled work zones. Almost three quarters of the agencies that collected this information archive it.

            ●          Weather and roadway conditions. Weather conditions and road conditions are archived by at least half of the agencies that collect/report weather and road conditions as part of their Freeway Management Systems as well as their Arterial Management Systems.

            ●          Information on ramp metering strategies has the potential to shed light on the benefits of time-sensitive metering control strategies.

            ●          Data archived on emergency responses and emergency vehicle signal preemption provide a foundation to evaluate the effectiveness of emergency management controls in saving lives. Unlike the Freeway Management Survey and the Arterial Management Survey, the Emergency Management Survey did not include questions specific to data generation and archiving. Consequently, no information is available on ITS-generated emergency response data.

            ●          Information on traffic signal controls (turning movements, phasing and cycle lengths and queues) allows the development of more proactive, rather than reactive, traffic control strategies.

            Three hundred eighty-eight agencies responded to the 1999 Arterial Management Survey. More than half of these agencies did not collect any data. Of those that reported data collection activities, more than two-thirds collected data on traffic signal controls (Figure 4.5). The percentage of agencies that archived their traffic signal data is very high (Figure 4.5).

4.2 CASE STUDIES OF OPERATIONS AND MAINTENANCE APPLICATIONS

            There was at least one case study for each of the four applications. The purpose of the case studies was to:

            ●    gain better insight into why archived ITS-generated data are, and are not, used in terms of technological and institutional situations and barriers,

            ●    identify additional opportunities for archiving and using ITS-generated data, and

            ●    identify successful practices in archiving ITS data for transportation decision-making.

Specifically, the case studies addressed the following questions:

            1.   What data do ITS deployments generate?

            2.   How are data generated and archived?

            3.   Are the ITS-generated data shared?

            4.   If so, how, with whom and for what purposes?

            5.   Were there barriers to archiving and sharing the data? If so, what were they and how were they overcome?

            It should be re-emphasized that this assessment only focuses on ITS deployments that have generated data that have the potential of being used in applications other than what was originally intended. This assessment has not attempted to identify ITS deployments that have not, but that could have, generated and archived data such as the I-95 Corridor FleetForward project, and the in-vehicle signing system for school buses at railroad-highway grade crossings. Specifically, the prerequisite for being selected to be a case study in this project was that an ITS system has to have been generating and archiving data.

            ITS projects in two metropolitan areas were examined - Atlanta and Los Angeles. The rationale for selecting these two locations was because of their data archiving activities and the level of collaboration among local agencies and jurisdictions. However, this by no means suggests that no other areas are archiving and sharing ITS-generated data as extensively as these two areas. In fact, an increasing number of agencies and researchers have been using archived ITS-generated freeway data in the past two years to monitor their system performance.

4.2.1 Georgia Department of Transportation's NaviGAtor in Atlanta

            NaviGAtor is designed to gather information from a variety of sources: a video monitoring and detection system, Highway Emergency Response Operators (HEROs) and the public. NaviGAtor links the Transportation Management Center (TMC) to the Transportation Control Centers (TCCs) of five surrounding counties (Cobb, Gwinnett, Clayton, Fulton and Dekalb), the City of Atlanta, and the Metropolitan Atlanta Rapid Transit Authority (MARTA), creating an intelligent transportation network spanning more than 220 miles.

System Description

            The current level of coverage is about 220 miles of instrumented roadway including freeway and arterial streets monitored by the central TMC and satellite TCCs. The central TMC currently has 42 miles of instrumented freeway along Interstates 75 and 85 inside the Interstate 285 beltway. Additional 14 miles of instrumentation were deployed along the northern arc of the 285 beltway in July, 2001.

            Atlanta’s NaviGAtor system (which is operated by Georgia DOT) is highly integrated with other agencies. The central TMC is currently linked to the Traffic Control Centers (TCC) of 5 other counties: Clayton, Cobb, DeKalb, Fulton, and Gwinnette counties, plus the City of Atlanta and the Metropolitan Atlanta Rapid Transit Authority (MARTA). These county and city TCCs are used to manage arterial road systems, while the NaviGAtor TMC manages the freeways. All monitored data are shared between the centers so that the arterial TCCs can see the traffic conditions on the freeways, and conversely, the freeway TMC can see traffic conditions on the arterial streets. The NaviGAtor TMC acts as the main warehouse for stored data. However, it is not clear whether the city and county TCCs archived any of their data.

Some of the agencies that are currently integrated into the system are:

            ●    Georgia Emergency Management Agency (GEMA),

            ●    Atlanta City Police Department,

            ●    911,

            ●    Metropolitan Atlanta Rapid Transit Authority (MARTA), and

            ●    Georgia State Patrol, which is located in the same compound as the TMC. (Although not currently connected to the system, it will be connected in the near future.)

            NaviGAtor uses the video monitoring and detection system (i.e., a camera-based system) to provide real-time images of road conditions. It serves as an incident verification tool. Installed on Interstates 75 and 85 are more than 317 fixed black-and-white Autoscope detector cameras that are spaced 1/3 of a mile apart, and 67 pan, zoom and tilt full color surveillance cameras spaced 2/3 of a mile apart. Information on average speed, traffic volume, lane occupancy and vehicle classification is collected from the Autoscope cameras. Video monitoring from the surveillance cameras allows the operators at the TMC to verify incidents, thus reducing response time, speeding up removal of incidents and minimizing congestion. The newly instrumented northern arc of I-285 added 114 additional fixed black and white cameras, and 36 color cameras. This brings the total to 103 pan, zoom, and tilt full-color cameras and 431 fixed black and white cameras.

            Of these two types of camera, only data generated from the fixed black and white Autoscope cameras are archived. The color surveillance cameras provide views of the traffic for the authorities as well as for the public at large via the Internet. No information from the color surveillance cameras is archived.

            A gyroscopic camera mounted on a helicopter is used for aerial monitoring. This aerial camera provides live video within a 50-mile radius of Atlanta, vastly increasing NaviGAtor's area of coverage.

            The County and City TCCs use primarily loop detectors for traffic signal optimization on arterial streets. There are some surveillance cameras installed in order to view incidents but no data is generated from these cameras that can be archived.

Data Archiving

            The Autoscope cameras gather data on a 20 second polling period. These data are then aggregated into 15-minute logs, which are stored onto an internal server for 30 days. Each month, the data are compressed, written and archived to a CD. When uncompressed, this system generates 4.6 megabytes of data on a daily basis.^4.3 Data have been archived for the past 4 years.

            The Autoscope camera images are interpreted by software at the TMC. Speed and vehicle counts are interpreted directly while the other data elements are derived using mathematical algorithms. The following is a list of data elements that are generated by the NaviGAtor freeway system for each lane of the freeway:

            ●    Speed,

            ●    Vehicle Counts,

            ●    Lane Occupancy,

            ●    Vehicle Classification

                  •    Auto: Less than 25 feet,

                  •    Light Truck: 25 to 49 feet, and

                  •    Tractor Trailer: ≥ 50 feet.

            ●    Headway: a measurement of the average gap between vehicles,

            ●    Flow Rate: expressed as number of vehicles per lane per hour, reflecting lane capacity,

            ●    Level of Service: Graded A through F, where A= light traffic, and F= gridlock,

            ●    Presence of stopped vehicles, and

            ●    Wrong way vehicles

Georgia DOT has the ownership of the data stored at the TMC. Of these data elements, only data on traffic volume, speed and lane occupancy are archived on a fifteen-second interval. Figure 4.6 illustrates an example of these archived data. These archived freeway data are stored in a format which facilities use for further analyses. 

Although the information disseminated by Variable Message Signs (Figure 4.7) is not archived at the present time, the availability of these data in real time on the Internet suggests that it can easily be archived. The usefulness of this information, by itself, is probably of little value. However, if integrated with sensor, roadway and weather information, it could provide valuable insights in the nature of locale-specific congestion and delay, and the effectiveness of different control strategies.

Sharing and Uses of Archived Data

            Since real time data are shared among all agencies integrated into the NaviGAtor system, there has not been a need to share archived data among those agencies. However, there have been many external requests to NaviGAtor’s central TMC for archived data. Some examples are:

            ●    Planning Commissions use the archived traffic data to analyze the traffic impacts of new construction.

            ●    Academia and the research community (e.g., Georgia Technology Institute) rely heavily on these data to develop a new generation of traffic prediction models that predict traffic delays by the month of the year and by weather conditions.

            ●    Environmental Protection Agency (EPA) establishes relationship(s) between traffic patterns and air quality based on the archived traffic data.

            ●    The Atlanta Regional Commission (ARC) used the archived data to create surface transportation models.

            ●    Environmental advocacy groups attempt to halt unwanted commercial developments.

            ●    Private citizens request the archived speed data to contest speeding tickets and other types of citations in court.

            Unfortunately, there is no convenient way for sharing archived data. When archived data are requested, Georgia DOT burns a CD that contains the data in compressed .txt format. The data are uncleaned and contain time stamps and camera ID numbers, along with their associated data elements.

            Accommodating data requests can be extremely time consuming, which has prompted Georgia DOT to consider several options:

            ●    Make the data available online for the public to query using some sort of relational database. This idea is under serious consideration and is likely to happen in the near future.

            ●    Another option being considered is a data broker who could take the entire data management responsibility off Georgia DOT. This option is still in its infancy and faces many institutional barriers such as how to use taxpayer money to contract out to a private company. One possible solution might be a mutually beneficial arrangement where control of the data management is given to a company or an organization, but no funds are passed from Georgia DOT to the data broker. The data broker can then provide value added to the data and sell it.

Barriers and Lessons Learned

            Although freeway data are archived and shared with the planning communities, Georgia DOT speculates that the archived data have not been fully utilized because of incompatible data format and data aggregation.

            Initially, there was much concern and debate over the development of an integrated system with shared control of equipment, especially the pan, tilt, zoom, color surveillance cameras. Many were concerned that sharing the control of cameras might conflict with the different objectives of different agencies. In reality, this concern has not been substantiated. Nonetheless, a camera control hierarchy has been developed.

            Although the surveillance cameras can be controlled by many different groups in the NaviGAtor system, Atlanta City Police have priority control of these cameras. This policy intends that if there are other users on the system trying to adjust the same camera simultaneously, the system defers priority control to the City Police. Otherwise, anyone in the NaviGAtor network with a set of controls can adjust the cameras. After the City Police, the NaviGAtor TMC has priority over their freeway cameras, and the various TCCs have priority over their arterial cameras. The diagram depicting the control hierarchy is illustrated in Figure 4.8.

            Data archiving and sharing of the archived data transpire despite the fact that ADUS has yet to be part of the NaviGAtor’s system architecture. At the time of the interview, a plan was underway to use NaviGAtor data to meet reporting needs required by the Highway Performance Monitoring System (HPMS).

4.2.2 Traffic ITS Deployments in the Los Angeles Metropolitan Area

            Traffic operations and transportation planning in the Los Angeles metropolitan area are the responsibility of many different jurisdictions. Experience and plans in archiving ITS-generated data and using the archived data in three agencies were analyzed: (1) the City of Los Angeles’ Department of Transportation (LADOT); (2) Los Angeles Metropolitan Transportation Agency (LAMTA), and (3) California Department of Transportation (CalTrans). The rationales to include these agencies in our case study are that: (1) they each have different perspectives on data archiving and sharing data, and (2) there is an ongoing plan to eventually integrate almost all ITS systems in the southern California areas into an integrated system. The extent of archiving data and use of archived data varies from one agency to the next. Nonetheless, there was consensus among all agencies visited that ADUS has significant benefits.

            The City of Los Angeles Department of Transportation (LADOT) has centralized authority over the planning and operation of the City's street system - which consists of 6,400 street miles, 1,400 major and secondary miles, 5,000 collector and local miles, 40,000 intersections and 160 freeway miles. Among its many other responsibilities, LADOT is responsible for the installation and maintenance of traffic signals, and other traffic control devices; and administers the City's transit programs. LADOT develops and uses the Automated Traffic Surveillance and Control (ATSAC) System to optimize the capacity of its existing highway system by reducing delay and minimizing traffic congestion. It is estimated that ATSAC reduces travel time of recurrent traffic by 12%, intersection delay by 32%, and intersection stops by 30%.^4.4

            The Los Angeles County Metropolitan Transportation Authority (MTA) is unique among the nation’s transportation planning agencies in that it serves as transportation planner and coordinator, designer, builder and operator of LA County’s transportation system. MTA was identified as a case study for its role in the Southern California Priority Corridor Showcase project, and its role as a potential ADUS user.

            CalTrans District 7 is the state transportation department that constructs and maintains the California state highway and freeway system in Los Angeles and Ventura Counties (Figure 4.9). Specifically, it manages 909 freeway and highway miles in LA County, and 273 freeway and highway miles in Ventura County. On a typical day, these miles carry an average of 90 million vehicle miles traveled (VMT) per day.

Automated Traffic Surveillance and Control (ATSAC) system

            The Automated Traffic Surveillance and Control (ATSAC) system, a computer-based traffic signal control system, is used by the City of LA to optimize the capacity of its existing arterial systems (Figure 4.10). ATSAC monitors traffic conditions and system performance. Loop detectors imbedded in the arterial roads detect the passage of vehicles, vehicle speed, and the level of congestion. If required, the signal timing is either automatically changed by the ATSAC computers or manually changed by the operator to achieve better traffic flow.

            To date, ATSAC operates 11,000 loop detectors and has been deployed in 2,449 of the 4,285 signalized intersections. Funding has been committed to instrument additional intersections, leaving only 25% of the city’s intersections without instrumentation. To supplement the information from loop detectors, closed-circuit television (CCTV) surveillance equipment has been installed at critical locations throughout the city. At the time of the site visit (February 2000), there are 150 CCTV cameras installed.

ATSAC-Generated Data

            Loop detectors generate data on vehicle counts, speed, and lane occupancy. Real-time traffic conditions are posted on the web.^4.5 Congestion level is determined by speed thresholds. For example, congestion is considered “heavy” when the average vehicle speed falls below 10 miles per hour (mph), “moderate” between 10 and 20 mph, and “none” above 20 mph. No data are generated from the CCTV cameras. Although no incident information is generated from ATSAC, the California Highway Patrol (CHP) posts incident information on its’ Traffic Incident Information Page.^4.6 This page contains all incidents to which CHP responded. Hot spots, the most serious incidents, are identified on real-time basis. Information generated for each incident includes: the area, type (e.g. “Traffic Collision-Ambulance Responding”), location, time, additional details, and CHP’s responses of the incident. Figure 4.11 illustrates a few examples of the incident report. These incidents are geo-coded on a GIS platform (Figure 4.12). Although incident data are not archived at the present time, it could easily be done especially with the “text” format of the data.

Archiving, Sharing and Uses of Archived ATSAC Data

            Traffic data generated from ATSAC are archived only for one week. The system automatically over-writes the old data after a week. Requests on archived data are addressed on an individual basis. For example, Southern California Association of Governments (SCAG) uses ATSAC’s traffic volume information to validate results from its travel forecast models. A contract was put in place for LADOT to archive and reformat the traffic data.

            In addition to outside users (e.g., SCAG), LADOT uses the archived ATSAC data to identify traffic “signatures.” Traffic surveillance data collected from surface streets impose a challenge different from those brought about by the freeway traffic data. Unlike freeway systems, no loop detectors are placed on curve lanes, thereby underestimating traffic volume. Although not a barrier to archiving traffic data, this is definitely a challenge for the proper use of the data.

Barriers, Lessons Learned, and Potential of Archived ATSAC-Generated Data

            ATSAC officials believe that any long-term data archiving needs first to overcome storage limitations. To date, ATSAC data amount to 76MB per day. Their second concern about data archiving is the challenge to make data accessible in a reasonable time frame. To make ATSAC more useful for planning purposes, ATSAC data should be integrated with data from other sources (e.g., weather).

            Although little is occurring right now at ATSAC on data archiving and data sharing, the potential of the archived data is considerable. For example, the LADOT, in collaboration with the Los Angeles County Metropolitan Transportation Authority (MTA), is implementing an advanced transit project - the Transit Priority System (TPS).^4.7 This project is designed to improve the on-time performance of metro buses by adjusting the signal timing at intersections for buses as they approach the intersection. A transponder mounted underneath a bus communicates with the ATSAC loop detectors imbedded in the roadway. Traffic signal priority is provided to a particular bus only if the bus is running behind schedule. If data generated from this project are archived, they can provide the information needed to develop plans for transit operations without impacting street traffic.

CalTrans

            CalTrans District 7 monitors more than 500 miles of freeway in LA area. Loop detectors are installed every ½ mile. Data on V(olume), O(ccupancy), and S(peed) are generated. The 30-second data are archived for thirteen months. In addition to the loop detectors, more than 20,000 CCTVs are installed. However, no video data are archived.

Archiving, Sharing and Uses of Archived ATSAC Data

            Lane-specific VOS data that are archived on a stand-alone server are accessible by University of California, Berkeley to perform the California Transportation System Performance Measures Project (PeMs).^4.8 This project assists Caltrans Traffic Operations and Traffic Operational Centers to manage traffic operations. Caltrans’ primary goal in using these archived data is to measure the performance of the freeway system and to identify recurrent congestion. Parameters such as Vehicle Miles Traveled (VMT) and Vehicle Hours Traveled (VHT) are measured at each loop location in real time and are archived for up to one year.

            Furthermore, CalTrans uses archived traffic volume data for special event planning, and archived speed profiles for incident detection. The latter is still somewhat ad hoc. CalTrans staff recommend the use of Common Object Request Broker Architecture (CORBA) to facilitate data sharing. No video images are archived due to the privacy concern. Archived ITS-generated data could be more widely used and many parts of the agency could benefit from ADUS.

4.2.3 Houston Roadway Weather Monitoring^4.9

            The Houston area is confronted with frequent weather conditions that affect traffic. In order to study the effects of weather conditions on traffic, 27 weather stations were deployed in the Fall of 2000. These stations provide real-time data on:

            ●    Roadway water depth. This measurement is achieved by using a pressure transducer imbedded in the base of a curb which provides readings based on the pressure of water at a given depth. They hope to use this technology to establish a baseline water depth for road closures.

            ●    Rainfall rate,

            ●    Humidity,

            ●    Wind speed. Houston has many tall bridges which are exposed to high wind velocities and wind gusts. These weather conditions pose a serious rollover threat to trucks and vehicles around the trucks. Variable Message Signs can be used to alert truck drivers of hazardous wind conditions.

            ●    Wind direction. These data will be used to assess the vulnerability of bridges to cross winds that could pose a threat to tall box-style trucks.

            ●    Air temperature,

            ●    Pavement temperature, which is measured by a thermocouple imbedded in the concrete of a bridge deck.

            ●    Pavement moisture. A thermocouple imbedded in the concrete of a bridge deck perform a conductivity test in order to detect moisture. Increased moisture on the pavement increases the conductivity readings.

            ●    Stream velocity. In Houston, a lot of ships and barges go under roadway bridges. If stream velocity rises to a dangerous level, water vessels may lose control and damage roadway structures with possible environmental consequences. This is particular true when the vessel is carrying petroleum or other hazardous materials. The attempt is to establish thresholds of stream velocity so that the Coast Guard can stop water traffic when the velocity reaches beyond the thresholds.

Figure 4.13 illustrates an example of the archived weather data. Although these data are archived in a flat text file format at http://www.hcoem.org/road/txdot_choose_date.asp, they are not widely disseminated. The system will be fully tested before the data can be more widely available. In December of year 2000, the plan was to store their data at the TranStar traffic management center where the data will be stored along with the traffic data in an ORACLE database. The combined data base of weather conditions and traffic data will allow the examination of impacts of weather conditions on traffic.

4.3 BARRIERS AND SOLUTIONS

            The institutional and other barriers associated with implementing ADUS are largely the same among the different ITS applications. These common barriers such as cost, proprietary rights, data issues, politics, and a lack of understanding or knowledge about ADUS are covered in further detail in Chapter 2.

            Beyond these common barriers, roadway/traffic and the Metropolitan planning process encounter a different kind of obstacle. People working in traffic management centers are forced to think in terms of hours and minutes, while metropolitan planners think in terms of months and years. This difference in perspective can cause a strain between these two groups when trying to implement ADUS. One possible solution to bridge this gap is to demonstrate the value of using archived data to improve operations. For example, an analysis of historical traffic patterns and signal timing can help develop proactive signal timing strategies that are sensitive to the temporal patterns of the traffic.

4.4 OPPORTUNITIES

            Opportunities for using ITS-generated data to improve operations are virtually limitless. Rather than try to identify all possible opportunities, this section identifies those that are practically feasible, can be quickly deployed, and are most likely to produce immediate benefits/results. The rationale for identifying these “low-hanging fruits” is that the sooner that quantifiable benefits of using ITS-generated data for operations improvement are demonstrated and disseminated, the sooner additional deployments will be stimulated. Any of these opportunities identified below can be developed into a Field Operational Test (FOT) with public and private partnership.

4.4.1 ADUS for Assessing Security Vulnerability of Highway Network

            The terrorist attacks on September 11, 2001 were the first time that terrorists used transportation vehicles as weapons of mass destruction against the United States. Uncorroborated information suggests the possibility of additional terrorist attacks against our nation’s transportation infrastructure such as the Golden Gate Bridge and the Bay Bridge in the San Francisco area, the Vincent Thomas Bridge at the Port of Los Angeles, and the Coronado Bridge in San Diego.

            To prepare for these and other threats, it is critical to assess the vulnerability of our transportation infrastructure, identify the weak links, and develop strategies to minimize the vulnerability.

            A digital multi-modal transportation network that is populated with archived data on traffic flow and speed, facility capability information, other traffic operation characteristics, and non-ITS traffic monitoring data can provide essential information to assess the vulnerability of the nation’s transportation system and to identify the weak links. With suitable algorithms and software (many of which already exist), the vulnerability, resilience, and redundancy of our transportation system can then be assessed. Furthermore, this integrated database can be used to develop beforehand alternative strategies, and to evaluate the consequences and feasibility of these alternatives. For example, if a bridge(s) and a link(s) were to be closed or destroyed, do alternative, parallel routes exist to accommodate the lost service? How long will it be before these alternative routes reach their capacities? What will then be the alternatives to these alternative routes?

            It should be emphasized that ADUS alone can not satisfy all of the information needs for an assessment of our transportation security vulnerability. However, when integrated with other data sources (e.g., highway monitoring data, remotely sensed data) and tools, ADUS can provide an indispensable base to do so.

4.4.2 ADUS for Performance Measures

            The interest in the development and use of performance measures and performance-based planning and program development has increased dramatically to meet customer needs under different conditions. Performance measures have been used at several levels, ranging from day-to-day operations to long-term capital planning that enhances system operations. Link travel times, duration of congestion, reliability, level of service, seasonal road closures, recurring and non-recurring delays are some of the typical performance measures used to improve highway operation performance. As pointed out in a NCHRP report^4.10, “...evaluating and improving system operations through performance measures can be challenging. Data collection and analysis demands can be overwhelming....” Archived ITS-generated data on traffic, speed, incidents, weather, and work zone schedules offer unique opportunities to fill this data collection concern. However, it should be emphasized that ADUS can best be used in developing facility-specific performance measures due to the current limited number of traffic surveillance deployments.

4.4.3 ADUS to Manage Traffic Delay

            According to recent research on traffic delay^4.11, it is estimated that about 2.3 billion vehicle-hours of delay per year on U.S. freeways and principal arterials are due to work zones, crashes, breakdowns, adverse weather, and sub-optimal signal timing. This estimate is reasonably close to an estimate of non-recurring traffic delay that was produced by the Texas Transportation Institute^4.12 which includes data from the 68 most congested cities. These results reveal the magnitude of the societal impact due to traffic delay. TTI further concluded that total non-recurring traffic delay is greater than recurring delay.

            A study of various archived ITS-generated data on traffic conditions, the duration and nature of the incidents, speed contours by time of day, and weather and road conditions will significantly increase knowledge about facility-specific inter-relationships between traffic patterns, speed profiles and the propensity of traffic delay. This information can help develop proactive and adaptive facility-specific strategies to reduce traffic delay. Further, this information can help inform the traveling public of the anticipated reliability status of the system at different times of the day.

4.4.4    ADUS for Planning and Managing Special Events

            Planned and unplanned events are an important and frequent part of transportation system operations. In Los Angeles area alone, it is estimated that there are 1,500 special events annually. To optimize the performance of the transportation system during special events, transportation agencies plan and coordinate the delivery of transportation services and operations in advance.

            As implemented by Caltran, archived freeway traffic data have been used, on an ad hoc basis, to manage and plan special events. One of the greatest benefits of archived data is the development of facility-specific traffic patterns (or “signatures”). If archived traffic data are used in conjunction with real-time traffic data and dynamic traffic routing tools, then plans and alternatives can be instantaneously developed to accommodate anticipated and non-anticipated losses of roadway capacity.

4.4.5    ADUS for Planning and Managing Unplanned Events

            Unplanned events include the tragic events on September 11, 2001, natural disasters, and other catastrophes. In the development of evacuation plans, archived ITS-generated traffic data provide perhaps the most accurate information on typical traffic flow and on the probability of recurring and non-recurring traffic delays by time of day, not only on the evacuation routes but also on alterative routes. With this kind of information, it is then possible to examine beforehand the impacts and feasibility of alternative evacuation scenarios by conducting “what-if” analyses.

4.4.6 ADUS for 511 Information Validation

            The success of any 511 deployments depends substantially on the validity and credibility of the information provided by 511. Information validation has largely relied on subjective engineering judgements, or on “borrowed” information. Moreover, even if data are collected, data quality is sometimes questionable. ADUS provides valuable historical data to develop trends, patterns, and acceptable data ranges which will in turn facilitate identification of questionable data before they are disseminated to the traveling public.

            Furthermore, ADUS allows credible estimation of potential traffic delays under varying conditions. An additional benefit of ADUS is that these estimates can be enhanced on a continuous basis because of the fact that ADUS data are continuously added to the database from which the estimates are derived. Credible information on potential traffic delays gives the traveling public adequate lead way to effectively pre-plan or alter their travel.

4.4.7 ADUS for Adaptive Signal Timing Strategies

            Centralized controlled signal timing on arterial roads can significantly improve the efficiency of traffic operations. Archived ITS-generated traffic data from arterials, in conjunction with existing signal timing, can be used to evaluate the impacts of various timing plans under varying conditions. Furthermore, archived ITS-generated traffic data permit the development of timing plans that are adaptive to the site-specific traffic patterns, and analysis of alternative timing scenarios.

            As previously mentioned, any of these opportunities can be developed into an FOT with the goals of:

            (a)       identifying technical and institutional barriers to archiving, using, and sharing ITS-generated data;

            (b)       developing solutions to overcome these barriers;

            (c)       identifying issues pertinent to standards development;

            (d)       examining the feasibility of integrating ITS-generated data with data collected from traditional and emerging technologies (e.g., highway monitoring data, remotely sensed data);

            (e)       identifying and quantifying costs and benefits;

            (f)        disseminating lessons learned, and

            (g)       sharing the developed procedures and software in an open-source environment. Some examples of these procedures and software are: those developed to convert raw ITS-generated data into formats acceptable to existing and/or off-the-shelf data management or analysis software, check the quality of the data, impute missing data, correct questionable data, abstract information suitable for data analysis from “text” files, estimate potential recurring and non-recurring traffic delays, and other applications. The benefit of sharing these procedures and software in an open-source environment is that it reduces the “re-inventing the wheel” thus enabling more efficient use of resources.

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