Title
Generating contextual description from driving behavioral data
Abstract
This paper presents an automatic translation method from time-series driving behavior into natural language with contextual information. Nowadays, various advanced driver-assistance systems (ADASs) have been developed to reduce the number of traffic accidents and multiple ADASs are required to reduce further accidents. For such multiple ADASs, considering the context of driving and selecting appropriate assistance is key because the systems have to handle extremely complicated driving situations consisting of drivers (and their intents and maneuvers), environments (including other traffic participants such as vehicles and pedestrians), and vehicles dynamics. In this paper, time-series driving behavior is segmented into typical driving situation symbols, and the natural language expression of each situation is generated via the behavioral feature distribution observed in each situation. Owing to the symbolization of the driving behavior, the generated behavioral descriptions can be associated with their causes and results not on an actual time axis but on a situation-symbol axis as contextual descriptions, e.g., “letting up on gas pedal to pass tollgate.” The effectiveness of the proposed method was evaluated by using an actual data set of more than eight hours over a distance of 300 km in total. Although contextual expressions are very diverse even among human drivers, the proposed method obtained an agreement of more than 70%.
Year
DOI
Venue
2014
10.1109/IVS.2014.6856476
Intelligent Vehicles Symposium
Keywords
Field
DocType
driver information systems,natural language processing,road accidents,road traffic,time series,vehicle dynamics,ADASs,advanced driver-assistance systems,automatic translation method,behavioral feature distribution,contextual description,contextual information,driving behavior symbolization,driving situation symbols,natural language expression,situation-symbol axis,time-series driving behavior,traffic accident reduction,vehicles dynamics
Computer vision,Contextual information,Expression (mathematics),Natural language,Behavioral data,Human–computer interaction,Artificial intelligence,Engineering,Automatic translation
Conference
ISSN
Citations 
PageRank 
1931-0587
4
0.38
References 
Authors
16
4
Name
Order
Citations
PageRank
Takashi Bando112314.55
Kazuhito Takenaka2737.41
Shogo Nagasaka3766.02
Tadahiro Taniguchi420133.56