Abstract: Methods and systems for dynamically providing routes to users of vehicles. In some examples, a method includes determining a first traffic flow model for uninformed drivers of vehicles and determining a second traffic flow model for informed drivers of vehicles. Each of the informed drivers makes driving decisions based on receiving dynamic routes from a traffic routing system. The method includes iteratively updating the second traffic flow model using the first traffic flow model until a convergence criterion is met. The method includes sending, to at least one informed driver, a first dynamic route from a first origin to a first destination using the second traffic flow model.

Abstract: A system and method for determining a probability that a driver will detect a hazard while driving. An eye tracker tracks the driver's forward and non-forward glance durations. A probability calculator categorizes the glance durations into an observation type and selects a transition matrix specific to that observation type. The probability calculator groups the glance durations and observation type into a tuple and calculates a probability that the driver will detect a hazard in the current time segment based on the tuple, the previous time segment's detection state, and the transition matrix. Based on whether the determined probability is above or below a threshold, the current time segment detection state is stored in memory as a detect state (driver is likely to detect a hazard) or a non-detect state (driver is not likely to detect a hazard). The driver is alerted if determined to be in a non-detect state.

Abstract: An approach is disclosed that reduces traffic network delays by identifying optimal sensor locations for one or more time periods and by controlling traffic signals through optimized sensor deployment.