Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
Data from connected probe vehicles can be critical in estimating road traffic conditions.
Unfortunately, current available data is usually sparse due to the low reporting frequency …
Unfortunately, current available data is usually sparse due to the low reporting frequency …
[PDF][PDF] Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part C, 2016 - cecas.clemson.edu
abstract Data from connected probe vehicles can be critical in estimating road traffic
conditions. Unfortunately, current available data is usually sparse due to the low reporting …
conditions. Unfortunately, current available data is usually sparse due to the low reporting …
Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part C: Emerging …, 2016 - infona.pl
Data from connected probe vehicles can be critical in estimating road traffic conditions.
Unfortunately, current available data is usually sparse due to the low reporting frequency …
Unfortunately, current available data is usually sparse due to the low reporting frequency …
Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part C: Emerging …, 2016 - trid.trb.org
Data from connected probe vehicles can be critical in estimating road traffic conditions.
Unfortunately, current available data is usually sparse due to the low reporting frequency …
Unfortunately, current available data is usually sparse due to the low reporting frequency …
Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part …, 2016 - ui.adsabs.harvard.edu
We propose an approach to reconstruct trajectories using sparse probe vehicle data. An EM
algorithm is used to allocate travel time to small segments. Our approach can estimate stop …
algorithm is used to allocate travel time to small segments. Our approach can estimate stop …
[PDF][PDF] Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part C, 2016 - thuvien.huce.edu.vn
abstract Data from connected probe vehicles can be critical in estimating road traffic
conditions. Unfortunately, current available data is usually sparse due to the low reporting …
conditions. Unfortunately, current available data is usually sparse due to the low reporting …
Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part C: Emerging …, 2016 - infona.pl
Data from connected probe vehicles can be critical in estimating road traffic conditions.
Unfortunately, current available data is usually sparse due to the low reporting frequency …
Unfortunately, current available data is usually sparse due to the low reporting frequency …
[PDF][PDF] Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates
N Wan, A Vahidi, A Luckow - Transportation Research Part C, 2016 - thuvien.huce.edu.vn
abstract Data from connected probe vehicles can be critical in estimating road traffic
conditions. Unfortunately, current available data is usually sparse due to the low reporting …
conditions. Unfortunately, current available data is usually sparse due to the low reporting …