Measuring the accuracy of map matched trajectories
First Claim
1. A method comprising:
- receiving from a transport service vehicle raw location data, the location data associated with a timestamp and a trip;
receiving from a transport service system a map of an area associated with the transport service vehicle and the trip, the map containing information on viable trajectories for the transport service vehicle;
calculating with a Hidden Markov Model an emission probability, the emission probability based on the likelihood that the transport service vehicle is at a road segment given an observation of the location data at a candidate road;
calculating with a Hidden Markov Model a transition probability, the transition probability based on the likelihood that for a current state, the transport service vehicle will transition to a next state; and
based on the joint probability of the emission and transition probabilities, determining a total number of zero forward probability occurrences and an average forward probability associated with the trip.
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Abstract
A transport service system determines the accuracy of a map matched trajectory using a forward probability algorithm. A transport vehicle on a trip relays location data to the system. The system uses a map of the corresponding area and the location data to calculate an emission probability, the likelihood of a candidate road being associated with a location data point, and a transition probability, the likelihood of a second state occurring after a first state. The joint probability of the emission and transition probabilities is used to determine a total number of zero forward probability occurrences and an average forward probability associated with the trip. These metrics are used to measure the accuracy of the map matching algorithm for the trip.
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Citations
18 Claims
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1. A method comprising:
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receiving from a transport service vehicle raw location data, the location data associated with a timestamp and a trip; receiving from a transport service system a map of an area associated with the transport service vehicle and the trip, the map containing information on viable trajectories for the transport service vehicle; calculating with a Hidden Markov Model an emission probability, the emission probability based on the likelihood that the transport service vehicle is at a road segment given an observation of the location data at a candidate road; calculating with a Hidden Markov Model a transition probability, the transition probability based on the likelihood that for a current state, the transport service vehicle will transition to a next state; and based on the joint probability of the emission and transition probabilities, determining a total number of zero forward probability occurrences and an average forward probability associated with the trip. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A non-transitory computer-readable storage medium storing computer program instructions executable by a processor to perform operations comprising:
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receiving from a transport service vehicle raw location data, the location data associated with a timestamp and a trip; receiving from a transport service system a map of an area associated with the transport service vehicle and the trip, the map containing information on viable trajectories for the transport service vehicle; calculating with a Hidden Markov Model an emission probability, the emission probability based on the likelihood that the transport service vehicle is at a road segment given an observation of the location data at a candidate road; calculating with a Hidden Markov Model a transition probability, the transition probability based on the likelihood that for a current state, the transport service vehicle will transition to a next state; and based on the joint probability of the emission and transition probabilities, determining a total number of zero forward probability occurrences and an average forward probability associated with the trip. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A system comprising:
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a computer processor for executing computer program instructions; and a non-transitory computer-readable storage medium storing computer program instructions executable by the processor to perform operations comprising; receiving from a transport service vehicle raw location data, the location data associated with a timestamp and a trip; receiving from a transport service system a map of an area associated with the transport service vehicle and the trip, the map containing information on viable trajectories for the transport service vehicle; calculating with a Hidden Markov Model an emission probability, the emission probability based on the likelihood that the transport service vehicle is at a road segment given an observation of the location data at a candidate road; calculating with a Hidden Markov Model a transition probability, the transition probability based on the likelihood that for a current state, the transport service vehicle will transition to a next state; and based on the joint probability of the emission and transition probabilities, determining a total number of zero forward probability occurrences and an average forward probability associated with the trip. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification