Kaiyu Liu

Prototype Information System for Estimating Average Vehicle Occupancies from Traffic Accident Records

Vehicle occupancy data are increasingly being used to assess and monitor congestion management strategies. They are traditionally collected in the field with the roadside windshield method and the carousel method. Although these traditional methods have the benefit of collecting up-to-date data and can be tailored to specific application needs, they are also much more costly to conduct, especially when repeated data collection is needed for monitoring purposes. An alternative to these traditional methods is to estimate average vehicle occupancies (AVOs) from vehicle occupancy information recorded in existing traffic accident records. This method is cost-effective because it involves no new data collection, and it can provide better spatial and temporal coverage. However, this method is also known to be affected by potential biases resulting from under-and overinvolvement of certain population sectors in traffic accidents. Also, for corridor studies, the number of accident records available may not meet the minimum required sample size for the desired accuracy. An effort was made to develop a prototype information system that can make use of vehicle occupancy information in accident data to estimate AVOs. The system was designed to account for drivers age and drivers gender biases. The system also includes a number of variables that can be used for spatial and temporal AVO monitoring, including district, county, hour, week, month, year, vehicle type, facility type, area type, and crash severity. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations.

Statewide implementation of Safety Analyst: The Florida experience

ABSTRACT Safety Analyst (SA) is a state-of-the-art software system designed to perform all the steps in the roadway safety management process. To implement the system, agencies must first prepare all the required input data and convert them into a standard format required by the system. However, this data preparation effort is extensive and has become a major obstacle to agency adoption of the system. This article describes Floridas efforts in preparing the input data needed to implement SA. It describes the SA data requirements and discusses several data preparation issues that agencies planning to implement SA are likely to encounter. Specifically, the article describes the methods employed to map Floridas variable codes and site subtypes to the required SA counterparts. The article also describes the approaches taken to collect missing data and to manipulate network data including network segmentation to achieve better results and inclusion of segment direction and geographic coordinates to enable data visualization in SA. The article further describes the development of a data converter tool to automatically convert the input data to standard import files used by SA, and the development of local safety performance functions to achieve better results. These experiences could provide useful lessons learned for agencies that have just started with SA or are contemplating its implementation.

Automated System to Prioritize Highway Improvement Locations and to Analyze Project Alternatives

The Florida Department of Transportation (DOT) District One first deployed a web-based system in 2009, called the Congestion Management Process (CMP), to screen and prioritize highway locations on its Strategic Intermodal System (SIS) for low-cost, near-term improvements. The system prioritizes highway locations on the SIS within the district on the basis of a simple scoring method with seven performance measures (i.e., crash ratio, fatal crash, volume-to-capacity ratio, average annual daily traffic, truck volume, truck percent, and delay). Once the Florida DOT adopted the Highway Safety Manual (HSM), there was a desire to apply safety performance measures to the CMP that were consistent with the manual’s methodology. There also was a desire to explore and implement a more advanced project prioritization method for better location screening and prioritization and to add mapping capabilities to improve data visualization. This paper describes the district’s efforts to incorporate these improvements into the CMP system. The CMP system can calculate performance measures automatically, including two safety-related measures on the basis of the HSM methodology, and prioritize highway locations with the Analytic Network Process, an advanced multicriteria decision-making technique. The system can create thematic maps of performance measures and other input variables on Google Maps for data visualization. It also can evaluate potential projects and record project-level information. Although developed for the Florida DOT District One, the system can serve as a prototype and be customized to prioritize highway locations in other states.

Integrated Analysis System for Rural National Transit Database

Performance data are needed in transit performance analysis to help to identify and to prioritize problem areas for management actions. In the United States, the most comprehensive source of transit performance data has been the National Transit Database (NTD). First collected in 1978 for urban transit systems, the NTD has included data on transit organization characteristics, vehicle fleet characteristics, revenues and subsidies, operating and maintenance costs, vehicle fleet reliability and inventory, services consumed and supplied, and safety and security. In 2006, FTA expanded the NTD program to require reporting by rural transit agencies. The NTD data for rural systems for 2007 through 2013 have since been released. Because NTD data are collected and distributed annually, they are stored in separate files of varying formats, making them difficult to access for performance analysis, especially when multiple years of data are needed. This paper describes a web-based system designed to overcome this limitation. The system integrates the rural NTD data from 2007 to 2013 and provides user-friendly tools to facilitate data access and performance analysis.

A Robust Dynamic Segmentation Tool for Highway Safety Analysis

This paper describes a dynamic segmentation application that allows roadways to be quickly segmented for highway safety analysis. After roadways are segmented (either variable-length or fixed-length), the system can automatically calculate the crash statistics associated with each segment, which can then be used to identify high-crash locations, to model the relationships between crash experience and geometric features, etc. The system can output segmented records in different formats, including tables, 2-D and 3-D charts, GIS shape files.