Dynamic travel time provision for road networks
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
T-drive: driving directions based on taxi trajectories
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Real-time routing with OpenStreetMap data
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Evaluating eco-driving advice using GPS/CANBus data
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Travel cost inference from sparse, spatio temporally correlated time series using Markov models
Proceedings of the VLDB Endowment
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The reduction of greenhouse gas (GHG) emissions from transportation is essential for achieving politically agreed upon emissions reduction targets that aim to combat global climate change. So-called eco-routing and eco-driving are able to substantially reduce GHG emissions caused by vehicular transportation. To enable these, it is necessary to be able to reliably quantify the emissions of vehicles as they travel in a spatial network. Thus, a number of models have been proposed that aim to quantify the emissions of a vehicle based on GPS data from the vehicle and a 3D model of the spatial network the vehicle travels in. We develop an evaluation framework, called EcoMark, for such environmental impact models. In addition, we survey all eleven state-of-the-art impact models known to us. To gain insight into the capabilities of the models and to understand the effectiveness of the EcoMark, we apply the framework to all models.