Developing an Active Traffic Management System for I-70 in Colorado
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2012-09-01
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Edition:Final.
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Abstract:The Colorado DOT is at the forefront of developing an Active Traffic Management (ATM) system that not only
considers operation aspects, but also integrates safety measures. In this research, data collected from Automatic
Vehicle Identification (AVI), Remote Traffic Microwave Sensors (RTMS) and Real-Time weather data were utilized
to incorporate safety within the ATM system. Preliminary investigation of crashes along 20-miles of I- 70 revealed
that the mountainous terrain and adverse weather during the winter season may increase crash likelihood. A traditional
automatic incident detection system is a reactive approach to mitigating the effects of crashes without attempting to
avoid primary incidents. To reduce the risk of primary incidents, a more proactive approach that identifies locations
where a crash is more likely to happen in real-time can be implemented.
The results from the research study suggest that there is a clear demand to incorporate real-time weather conditions
and roadway geometric characteristics within the development of the ATM system. Remote Traffic Microwave
Sensors, AVI, weather data, and road geometry information were collected and utilized to develop a real-time risk
assessment system. Data Mining (DM) techniques were also used to reveal important data relationships and improve
prediction accuracy. Based on the data and DM techniques, models were tested and their performances were
compared. Results show that the Full Model which incorporates AVI, RTMS data, weather data, and geometric
information outperforms other models by identifying about 89% of crash cases in the validation dataset with only
6.5% false positive.
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