We are pleased to present the final report of Caltrans Task Orders 5211 and 6211, “Estimating Pedestrian Accident Exposure.” The project focused on defining pedestrian exposure and evaluating methods for measuring it within the State of California. The project was funded by the California Department of Transportation as part of the California Partners for Advanced Transit and Highways (PATH) Program of the University of California.

Deliverables associated with the project include (I) a protocol report on assessing pedestrian exposure, which is accompanied by a training curriculum and an evaluation of manual pedestrian counting methods; (II) an evaluation and test of automated pedestrian counting methods; and (III) a report on strategies to create a statewide pedestrian exposure database and (IV) a protocol for Pedestrian Exposure Study in Alameda County. The deliverables are discussed in more detail below.

This report discusses approaches to addressing the need for better and more widely available pedestrian volume data in the state of California. While a variety of approaches could be used, this report focuses on the strategy of a statewide pedestrian volume database.

This database would meet a variety of data needs for different stakeholder groups. One of its principal purposes would be to allow safety professionals at the state and local levels to estimate pedestrian exposure to risk at specific sites.

Since exposure data is essentially equivalent to facility usage data, a pedestrian exposure data would be used for many purposes beyond risk analysis. Facility usage data might be used by municipalities to pinpoint new infrastructure needs, or to determine whether new infrastructure encourages more pedestrian activity. Facility usage data might also be used by advocacy groups as a means to promote new facility investments.

If the database includes information beyond pedestrian volumes, such as facility characteristics (e.g. the availability of sidewalks and intersection crossings) or planning variables (e.g. land uses and population densities), it may be used as a means to improve pedestrian demand modeling techniques or to investigate the relationship between pedestrian environmental quality and pedestrian demand. Furthermore, if facility funding data are included, the database may also be used as a means to track spending on pedestrian projects.

In short, there is a wide range of usage for a pedestrian volume database. In designing the database, it is important to maximize its utility to pedestrian stakeholder groups while recognizing the costs associated with increased complexity.

Creation of a pedestrian volume database for the state of California involves several major decision points. This report examines these decision points and provides a range of database approaches given different funding and institutional constraints, and describes the challenges that will need to be addressed in the database development process.

Chapter 2 discusses the technical and institutional challenges inherent in creation of a pedestrian exposure database. Chapter 3 discusses the need for an inventory of the pedestrian network as a starting point for the database, and present two existing sources for the network. Chapter 4 presents a range of approaches to data collection process, and suggests data points that might be appropriate for inclusion in the data collection process. Chapter 5 discusses how pedestrian demand modeling might be used to estimate pedestrian volumes with limited data inputs. Chapter 6 summarizes the report and provides recommendations for future development of the database.

Walking is a healthful, environmentally benign form of travel, and is the most basic form of human mobility. Walking trips account for more than 8 percent of all trips taken in California, making walking the second most commonly used mode of travel after the personal automobile (Caltrans, 2002). In addition, many trips made by vehicle or public transit begin and end with walking. In spite of the importance and benefits of walking, pedestrians suffer a disproportionate share of the harm of traffic incidents in California. As noted above, walking trips make up just 8 percent of all trips in the state, but 17 percent of all traffic fatalities are suffered by pedestrians. In 2004, 694 pedestrians were killed in the state of California and 13,892 were injured (California Highway Patrol, 2004). To address this problem, significant resources are focused on countermeasures that aim to reduce the risk of pedestrian injury. Because resources are limited, risk analysis is necessary to develop cost-effective countermeasures (Hoj and Kroger, 2002). In the field of pedestrian safety, risk analysis involves assessing factors that contribute to the danger that a pedestrian is struck by a vehicle. These factors may include physical characteristics of the street, such as lack of sidewalks; behavioral issues, such as pedestrian or driver alcohol use; as well as other environmental variables. In order to fully understand how these factors contribute to risk, it is necessary to collect information on pedestrian exposure. Collection of pedestrian exposure information is an essential component of risk analysis. Pedestrian exposure is a concept that refers to the amount that people are exposed to the risk of being involved in a traffic collision. In principle, pedestrians are exposed to this risk whenever they are walking in the vicinity of automobiles. There are many metrics that can be used to measure pedestrian exposure, but pedestrian volumes are the most frequently used. Although many state, regional, and local agencies have developed methodologies to collect pedestrian volume data, there is no consensus on which method is best (Schneider et al., 2005; Schweizer, 2005). This is because there is no “one size fits all” method of counting pedestrians. Rather, the choice of strategy depends on a complex range of factors, including the characteristics of the area being studied; the resources available for data collection; and the specific purpose of data collection. This protocol aims to improve pedestrian data collection in the state of California by providing information and guidance for each decision point in the data collection process. Each chapter represents one of these decision points, and each will guide the user through important considerations relevant to the data collection stage. In addition, each chapter provides a combination of real-world and hypothetical example scenarios to illustrate the issues discussed in the text.

Resources for implementing countermeasures to reduce pedestrian collisions in urban centers are usually allocated on the basis of need, which is determined by risk studies. They commonly rely on pedestrian volumes at intersections. The methods used to estimate pedestrian volumes include direct counts and surveys, but few studies have addressed the accuracy of these methods. This paper investigates the accuracy of three common counting methods: manual counts using sheets, manual counts using clickers, and manual counts using video cameras. The counts took place in San Francisco. For the analysis, the video image counts, with recordings made at the same time as the clicker and sheet counts, were assumed to represent actual pedestrian volume. The results indicate that manual counts with either sheets or clickers systematically underestimated pedestrian volumes. The error rates range from 8-25%. Additionally, the error rate was greater at the beginning and end of the observation period, possibly resulting from the observer’s lack of familiarity with the tasks or fatigue.

Each year from 1998 to 2007, an average of approximately 4,800 pedestrians were killed and 71,000 pedestrians were injured in United States traffic crashes. Because many pedestrian crashes occur at roadway intersections, it is important to understand the intersection characteristics that are associated with pedestrian crash risk. This study uses detailed pedestrian crash data and pedestrian volume estimates to analyze pedestrian crash risk at 81 intersections along arterial and collector roadways in Alameda County, California. The analysis compares pedestrian crash rates (crashes per 10,000,000 pedestrian crossings) with intersection characteristics. In addition, more than 30 variables were considered for developing a statistical model of the number of pedestrian crashes reported at each study intersection from 1998 to 2007. After accounting for pedestrian and motor vehicle volume at each intersection, negative binomial regression shows that there were significantly more pedestrian crashes at intersections with more right-turn-only lanes, more non-residential driveways within 50 feet (15 m), more commercial properties within 0.1 miles (161 m), and a greater percentage of residents within 0.25 miles (402 m) who are younger than age 18. Raised medians on both intersecting streets were associated with lower numbers of pedestrian crashes. These results, viewed in combination with other research findings, can be used by practitioners to design safer intersections for pedestrians. This exploratory study also provides a methodological framework for future pedestrian safety studies.

High-quality continuous counts of pedestrian volume are necessary to evaluate the effects of pedestrian infrastructure investments and to improve pedestrian volume modeling. Automated pedestrian counting devices can meet the need for continuous counts of pedestrian volume and reduce the labor cost associated with manual pedestrian counting and data entry. However, most existing automated pedestrian devices are not well suited to the task of counting pedestrians in outdoor environments, and little is known about their effectiveness and accuracy. This study addresses the lack of performance information on automated counting devices by providing a review of commercially available devices and by testing the accuracy of a promising device in an outdoor urban context. It finds that a dual sensor passive infrared device is capable of producing reasonably accurate pedestrian volume counts in the outdoor urban context. It also finds a high degree of inter-reliability between counts collected by field observers and through video recordings.

Automated methods are commonly used to count motorized vehicles, but are not frequently used to count pedestrians. This is because the automated technologies available to count pedestrians are not very developed, and their effectiveness has not been widely researched. Moreover, most automated methods are used primarily for the purpose of detecting, rather than counting, pedestrians (Dharmaraju et al., 2001; Noyce and Dharmaraju, 2002; Noyce et al., 2006). Automated pedestrian counting technologies are attractive because they have the potential to reduce the labor costs associated with manual methods, and to record pedestrian activity for long periods of time that are currently difficult to capture through traditional methods. Data input and storage may also be less time consuming than with manual methods. On the other hand, the capital costs of automated equipment may be high; specialized training may be required to operate it; and automated devices are generally not capable of collecting information on pedestrian characteristics and behavior. For these reasons, automated devices are not appropriate for all pedestrian data collection efforts. The choice between which method is more appropriate to collect pedestrian data must be based on the accuracy level desired, budget constraints, and data needs specifications. Automated Counting Technologies Much of the research on automated pedestrian tracking devices has focused on pedestrian detection, not pedestrian counting. Extensive reviews of pedestrian detection technologies were conducted by Noyce and Dharmaraju (2002) and by Chan et al. (2006). Technologies include piezoelectric sensors, acoustic, active and passive infrared, ultrasonic sensors, microwave radar, laser scanners, video imaging (computer vision). Of the technologies listed above, those most adaptable to the purpose of pedestrian counting are: infra-red beam counters; passive infrared counters; piezoelectric pads; laser scanners; and computer vision technology. None of these devices are widely used for the purpose of counting pedestrians outdoors, but all have some potential to be adapted for that purpose. This report describes each of these technologies in detail, and discusses some of the technical strengths and weaknesses of each method. It is important to be aware that technical limitations are only one consideration among many when choosing an appropriate counting device. The device “packaging,” such as the method and location of installation may be equally important. For example, the location and accessibility of the device may create liability issues or promote vandalism.