Abstract
Manual traffic control is a common intersection control strategy in which trained personnel, typically police law enforcement officers, allocate intersection right-of-way to approaching vehicles. Manual intersection control is a key part of managing traffic during emergencies and planned special events. It is widely assumed that the flow of traffic through intersections can be greatly improved by the direction given from police officers who can observe and respond to change conditions by allocating green time to the approaches that require it the most. Despite the long history of manual traffic control throughout the world and its assumed effectiveness, there have been no quantitative, systematic studies of when, where, and how it should be used or compared to more traditional traffic control devices. The goal of this research was to quantify the effect of manual traffic control on intersection operations and to develop a quantitative model to describe the decision-making of police officers directing traffic for special events and emergencies. This was accomplished by collecting video data of police officers directing traffic at several special events in Baton Rouge, LA and Miami Gardens, FL. These data were used to develop a discrete choice model (logit model) capable of estimating police officer’s choice probabilities on a second-by-second basis. This model was able to be programmed into a microscopic traffic simulation software system to serve as the signal controller for the study intersections, effectively simulating the primary control decision activities of the police officer directing traffic. The research findings suggested police officers irrespective of their location, tended to direct traffic in a similar fashion; extending green time for high demand directions while attempting to avoid long gaps or waste in the traffic stream. This indicates that when officers are placed in similar situation they are likely to make the same primary control decisions.
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