Programs & Labs
Using Detailed Signal and Detector Data to Investigate Intersection Crash Causation
Principal Investigator:
- Gary A. Davis, Professor, Civil Engineering
Co-Investigator:
- Henry Liu, Assistant Professor, Civil Engineering
Project Summary
Mn/DOT knowledge-building priority KB020 states: “New tools need to be developed to aid in understanding crash dynamics and to assist in crash prevention.” This is consistent with a national trend, where transportation professionals are being required to explicitly consider safety outcomes in the design and operation of transportation facilities, yet the tools that allow prediction of safety outcomes are in a primitive state of development. Ultimately, the traffic modeling tools that have been successful in relating design and operational decisions to changes in travel time, delay and congestion must be expanded to include safety effects. This in turn requires that we identify the mechanisms by which crashes occur, characterize the actions of drivers in crashes, and determine to what extent crash-involved actions might differ from actions taken in more normal conditions.
In Minnesota, we have been given a unique opportunity to study crash phenomena at intersections controlled by traffic-actuated signals. The SMART-SIGNAL data retrieval and archiving system, developed by this project’s Co-PI, is a hardware/software system that can be installed in a signal controller cabinet and record and store a complete history of the status of the signal’s detectors and control indications. SMART-SIGNAL has been deployed and tested on two corridors in the Twin Cities, and been used to produce dynamic estimates of arterial travel time and intersection queue length. In this project we propose using SMART-SIGNAL’s microscopic data to (1) reconstruct intersection-related crashes, (2) to identify causal factors in intersection-related crashes, and (3) to investigate gap selection behavior by drivers.
Sponsors:
- ITS Institute (RITA)