Accurate methods of counting pedestrians are needed to quantify exposure for safety analysis, rank infrastructure improvements and safety programs by priority, evaluate the benefits of pedestrian projects, develop models of pedestrian volumes, and track changes in pedestrian activity over time. However, pedestrian counts are still much less common than motor vehicle counts in most communities. In addition, existing count methodologies are not standardized and rarely provide enough information to extrapolate to weekly, monthly, or annual volumes. This exploratory study presents a methodology for estimating weekly pedestrian intersection crossing volumes based on 2-h manual counts. The methodology, implemented in Alameda County, California, involves a combination of manual and automated counts to determine weekly volumes. More than 690,000 pedestrians were counted during the 13-week study period. Manual counts were conducted at a set of 50 intersections. Automated counts from sidewalk locations in close proximity to a subset of 11 intersections were used to adjust these counts for time of day and week, surrounding land use characteristics, and weather conditions. The extrapolated pedestrian volume estimates were then used to calculate the number of reported crashes per 10 million pedestrian crossings at each of the study intersections. The results of this study demonstrate how pedestrian volumes can be routinely integrated into transportation safety and planning projects.

Methodology for Counting Pedestrians at Intersections: Use of Automated Counters to Extrapolate Weekly Volumes from Short Manual Counts

A framework for assessing the usage and level-of-service of rail access facilities is presented. It consists of two parts. A dynamic demand estimator allows to obtain time-dependent pedestrian origin–destination demand within walking facilities. Using that demand, a traffic assignment model describes the propagation of pedestrians through the station, providing an estimate of prevalent traffic conditions in terms of flow, walking times, speed and density. The corresponding level-of-service of the facilities can be directly obtained. The framework is discussed at the example of Lausanne railway station. For this train station, a rich set of data sources including travel surveys, pedestrian counts and trajectories has been collected in collaboration with the Swiss Federal Railways. Results show a good performance of the framework. To underline its practical applicability, a six-step planning guideline is presented that can be used to design and optimize rail access facilities for new or existing train stations. In the long term, the framework may also be used for crowd management, involving real-time monitoring and control of pedestrian flows.

/pdf/assessing-the-usage-and-level-of-service-of-pedestrian-18z4br6h54.pdf

Assessing the usage and level-of-service of pedestrian facilities in train stations: A Swiss case study

In this paper a new crosswalk detection strategy is presented. The application area is narrowed down to driver assistance systems to guarantee a reliable detection result and to benefit from the properties of a vehicle mounted camera.

On visual crosswalk detection for driver assistance systems

We present a framework for estimating pedestrian demand within a train station. It takes into account ridership data, and various direct and indirect indicators of demand. Such indicators may include link flow counts, density measurements, survey data, historical, or other information. The problem is considered in discrete time and at the aggregate level, i.e., for groups of pedestrians associated with the same origin-destination pair and departure time interval. The formulation is probabilistic, allowing to consider the stochasticity of demand. A key element is the use of the train timetable, and in particular of train arrival times, to capture demand peaks. A case study analysis of a Swiss train station underlines the practical applicability of the proposed framework. Compared to a classical estimator that ignores the notion of a train timetable, the gain in accuracy in terms of root-mean-square error is between 20% and 50%. More importantly, the incorporation of the train schedule allows for prediction...

/pdf/estimation-of-pedestrian-origin-destination-demand-in-train-48g1tst8s1.pdf

Estimation of pedestrian origin-destination demand in train stations

Applying Intelligent Transportation Systems (ITS) to arterial systems allows the Texas Department of Transportation (TxDOT) to significantly enhance transportation system operation efficiency and improve traffic mobility. However, no guidelines are available to assist TxDOT staff in selecting the most beneficial arterial ITS elements and desirable ITS technologies. To address these gaps, this study was initiated by TxDOT to investigate the arterial ITS elements, technologies, arterial performance measures, information dissemination technologies, and financial considerations for arterial ITS deployments and to enhance the arterial traffic operation efficiency. A variety of techniques are available to monitor and manage the traffic on arterial roadways, and ITS applications can support many of these strategies. Evaluation of these ITS strategies and available technologies to meet TxDOT needs is the essence of this research project. The research addresses two TxDOT goals: making the current transportation system more efficient through innovative arterial ITS deployments, and maximizing the benefits of existing ITS infrastructure and new arterial ITS deployments. The research team first synthesized the state-of-the-art in arterial ITS technologies and management strategies. Then critical performance measures were investigated and identified through a survey study. Next, the most beneficial ITS elements were examined and desirable ITS technologies and solutions were identified for arterial management enhancement. Various traveler information dissemination modes were studied and evaluated, and the guideline was developed to prioritize arterials suitable for ITS implementations. Finally, a case study was conducted to demonstrate representative arterial ITS applications. It was found deploying ITS technologies can significantly improve arterial system operation efficiency. The study findings provide new knowledge and practical guidance to help TxDOT better utilize existing ITS infrastructure elements and to make wise investments in future arterial ITS applications.

https://rosap.ntl.bts.gov/view/dot/17939/dot_17939_DS1.pdf

Arterial Intelligent Transportation Systems—Infrastructure Elements and Traveler Information Requirements

The foundation for several pedestrian safety measures is reliable and accurate detection of pedestrians. The main objective of this study was to evaluate sensors for use in a pedestrian safety test bed in College Station, TX. The following sensors were installed for use in the pedestrian test bed: 1) MS SEDCO SmartWalk 1400 (curbside detection) and SmartWalk 1800 (crosswalk detection); and 2) ASIM IR 201 (curbside detection) and IR 207 (crosswalk detection). Several other sensors designed for counting pedestrians and bicyclist on trails also were evaluated: 1) Jamar Scanner, 2) TrafX Infrared Trail Counter, and 3) Diamond Traffic TTC-4420. The ASIM and MS SEDCO intersection sensors provided fair to mediocre results, with error rates ranging from 9 to 39 percent. The typical error rates were in the 20 to 30 percent range, which may not be sufficient accuracy for most pedestrian detection applications. The accuracy of the sensors appeared to be very location-specific, in that pedestrian detection can be more effective in certain situations in which the pedestrian travel area is constrained. The three trail sensors were able to accurately detect a single pedestrian at typical walking speed or a bicyclist at slow speed (5 to 10 mph). The Jamar sensor had difficulty counting bicyclists at typical bicycling speed. All three trail sensors did consistently undercount the actual ground truth counts, with the undercounting being more severe in situations with more pedestrian groups. This undercounting presents a problem on busy shared-use trails.

Testing and Evaluation of Pedestrian Sensors

This paper will discuss how the need to accommodate pedestrian and bicycle traffic is increasing with the growing trend toward concepts such as walkable streets and livable communities. Similar to needs with vehicular traffic, it is necessary for transportation agencies and jurisdictions that employ these concepts to ascertain the current and potential demand on their infrastructure by other road users such as pedestrians and bicyclists. These concepts will enable agencies to determine where users travel and help predict where increasing travel demand will occur. One means of quantifying this new travel demand is using automated pedestrian/bicycle counters. Similar to automated motor vehicle counters, pedestrian/bicycle counters provide traffic engineers and planners with a tool to count volumes and record traffic patterns on shared use paths, sidewalks, and other linear spaces frequented by pedestrians and bicyclists. A recent research project evaluated three automated pedestrian/bicycle counters and compared their relative strengths and weaknesses in ease of installation, accuracy of count, and ability to distinguish pedestrian groups. A break-beam counter exhibited the best overall count accuracy (including groups), but lacked user-friendliness in setup and operation. The first of two infrared counters had both moderate ease of installation and counting accuracy, but missed detecting a large percentage of bicycles. The second infrared detector was the easiest to both install and upload the post-test data, but lacked the detection range to count wide trails and had slightly less overall accuracy than its counterparts. The paper shows how slight modification of the sensors’ detection algorithms could improve their accuracy and more user-friendly interfaces could enhance their ease of use.

Evaluating the Accuracy of Pedestrian/Bicycle Counters

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Testing and Evaluation of Pedestrian Sensors

Evaluating the Accuracy of Pedestrian/Bicycle Counters