Identification of High Pedestrian Crash Locations

CHAPTER 6. SUMMARY/CONCLUSIONS AND FUTURE RESEARCH NEEDS

OVERVIEW

This chapter provides summaries and conclusions along with a discussion of the implications of the findings of each study. The chapter concludes with a list of future research needs.

SUMMARY/CONCLUSIONS

Literature Review

Key findings and conclusions for this literature and state-of-the-practice review include the following:

• With the growth of improved statistical techniques, the profession is better able to handle RTM and low-sample challenges.
  
  
• The development of new techniques—such as SPFs, the HSM, or systemic analyses—and new computer programs (e.g., ArcGIS® or usRAP) allows relatively easy comparison between a city’s data and national trends.
  
  
• Several different approaches are used to identify and display HCLs, and often, these approaches are not well documented in the mapping application. In some cases, the mapping software application automatically determines how to group nearby crashes based on view level. In other cases, agencies predetermine how nearby crashes will be grouped and displayed in the mapping software.
  
  
• Certain map displays are more likely to successfully convey crash density. The use of larger symbols or color-coded symbols (e.g., green–yellow–red scale) seemed to be most appropriate for quickly identifying HCLs. In most cases, showing symbols for individual crashes does not display well because the crash symbols overlap on the map.
  
  
• Map displays with zoom capability can be used to quickly identify high crash areas at a citywide scale yet still provide the option to view individual crashes at a specific intersection or street. Maps that display additional information once clicked are ideal for exploring crash patterns or attributes at a detailed level.

Interviews With Governmental Agencies

Several cities and a State were contacted to determine the criteria that are being used to identify and rank high pedestrian crash locations. In all cases, crash data are used. In some cases, other variables are considered, especially when developing the list of sites considered for treatment. For example, Los Angeles uses a score that considers the age of the pedestrian and a health and equity index in addition to the number of injury crashes and the number of fatal crashes.

Agencies are now geocoding the location of their crashes, which is resulting in the ability to quickly illustrate visually where crashes are occurring. All the interviewed agencies are using a GIS to identify HCLs. The agencies generally start with identifying high crash intersections and then cluster the sites into corridors and/or areas. GIS tools are used to aid in the clustering; however, several agencies noted that visually confirming the clustering is how they set the limits for their corridors and areas.

Agencies have considered surrogates to identify locations of concern, such as activity centers, walk scores, or citizens’ comments. Pedestrian exposure data are not used to identify sites because of the lack of good data. The analysis period ranges from 1 to 3 yr.

The skill sets needed to work with crash data include familiarity with a GIS, the ability to work with attribute tables, and programming skills. Key lessons learned include the importance of having analysts with the needed skill sets, sharing data between partner agencies, having access to reliable geocodes for the crashes, and having strong support from others within the city.

Interviews About Pedestrian Collision Warning Systems

In this effort, the research team contacted three industry representatives to discuss the feasibility of logging warning events from pedestrian collision warning systems for use in pedestrian safety analyses. The most feasible near-term approach is available through fleet-vehicle-based systems such as Mobileye’s Shield+™ system. In fact, Mobileye has already developed and demonstrated an analytics platform for identifying safety hot spots from pedestrian collision warning event data. The technical feasibility for consumer-auto-based collision warning systems depends entirely on whether a carmaker or information services provider has communications capability. Toyota indicated that it does not currently have this capability. As part of their operating model, information service providers such as HERE have two-way communications capability with cars and do intend to gather various sensor data if it suits their business purposes. However, these efforts at gathering sensor data from connected cars are in early stages, and any pedestrian collision warning event data will likely not be available on a systematic basis within the next few years.

Guidebook and Webinar Workshop

The draft Guidebook was developed and distributed for review. After revisions were made, the research team held a webinar workshop with FHWA and the panel to present the process developed to identify high pedestrian crash locations. Comments made during the webinar workshop were used in the development of the final version of the Guidebook.

FUTURE RESEARCH NEEDS

Several future research needs were identified, with the following having the highest support by the panel:

• Explore alternative methods to identify locations of concern for pedestrians that can supplement or expand pedestrian crash data, such as hospital data, conflict data, or citizens’ concerns.
  
  
• Investigate the sensitivity of exposure data—both pedestrian and vehicle—in affecting the ranking of locations of concern for pedestrians.