To date, many efforts have been made to explore how to support driver's decision-making process with advisory information. Previous studies mainly focus on a single modality, e.g. the visual, auditory or haptic modality. In contrast, this study compares data from two simulator studies with 50 participants in total, where the visual vs. the auditory modality was used to present the same type of advisory traffic information under the same driving scenarios. Hereby we compare the effect of these two modalities on drivers' responses and driving performance. Our findings indicate that modality influences the drivers' behaviour patterns significantly. Visual information helps drivers to drive more accurately and efficiently, whereas auditory information supports quicker responses. This suggests that there are potential benefits in applying both modalities in tandem, as they complement each other. Correspondingly, we present several design recommendations on Advisory Traffic Information Systems.

Within vehicle Human Machine Interface design, visual displays are predominant, taking up more and more of the visual channel for each new system added to the car, e.g. navigation systems, blind spot information and forward collision warnings. Sounds however, are mainly used to alert or warn drivers together with visual information. In this study we investigated the design of auditory displays for advisory information, by designing a 3D auditory advisory traffic information system (3DAATIS) which was evaluated in a drive simulator study with 30 participants. Our findings indicate that overall, drivers' performance and situation awareness improved when using this system. But, more importantly, the results also point towards the advantages and limitations of the use of advisory 3D-sounds in cars, e.g. attention capture vs. limited auditory resolution. These findings are discussed and expressed as design implications.

Understanding complex behavior patterns in response to triggered forward collision warning system benefits localized user experience design, especially in safety critical scenarios from a cross-regional perspective. This paper studies driver response behavior patterns towards two alarm timings, in car-following scenarios with different traffic density. Data from 32 participants in China and 30 participants in Sweden were collected using a driving simulator. Differences were observed between China group and Sweden group regarding response behavior patterns, system acceptance and effectiveness. Seen from obtained results, Chinese drivers were found to steer more frequently than Swedish drivers in response to triggered alarm no matter what alarm timing or traffic density there were. Chinese drivers preferred later alarm timing than Swedish drivers. To better design regional-adaptive human machine interaction of forward collision warning system; some suggestions were produced based on obtained results.

Truck drivers is a key group to promote road safety. For them, proper priority ranking scheme of content adaptation design benefits the high system effectiveness of in-vehicle driver decision support. Taking Chinese truck drivers as an example, the present study revealed the context-adaptive support information from the perspective of truck drivers; their perceptions of in-vehicle information contents priority in 6 typical driving contexts. Data of 19 participants from 7 logistics companies were collected using a simulation interview method. Based on qualitative summary and statistical analysis, the results are summarized in two aspects; contextual information priority and impacts of driving experience on it. From the perspective of truck driver requirement, these results provide references for the design of context-adaptive driver decision support.

Many advanced driving assistance systems have been developed based on the western automobile markets. However, it is widely known that the differences between Western and Asian markets are large in terms of traffic safety culture, traffic situation, and driver behavior. This study aimed to explore the differences between Swedish and Chinese drivers' information requirements in regards to a 3D Auditory Advisory Traffic Information System design (3DAATIS). A total of 46 participants took part in the study. The results showed that both Swedish and Chinese drivers appreciated the concept of a 3DAATIS. Moreover the two groups expressed similar information needs when interacting with a single road user, e.g. giving higher priority to vulnerable road users. In contrast, they expressed different information requirements in complex traffic scenarios. The results further imply that identifying drivers' requirements under different traffic scenarios can be a feasible approach to successful cross-regional adaption design.

With an increased number of both cars and drivers in the world, it is of great importance to design well-functioning driver support systems for them, in order to reduce the number of accidents. Despite the fact that the growing markets can be found in Asia, most advisory traffic information systems (ATIS) are designed for, and adapted to, the western market, and its predominant traffic safety cultures (TSCs). However, traffic safety cultures differ between different parts of the world, and this in turn affects how drivers respond to advisory traffic information. In our study, we designed an ATIS to accommodate two different traffic safety cultures. Our findings show that although drivers belonging to both TSCs drove more safely with our ATIS than without, they still responded very differently to it, using it to support their different driving strategies. This implies that the traffic safety culture of the driver cannot be ignored; ATIS designers need to study and understand the TSC they are designing for.

Detection of driver cognitive distraction is critical for active safety systems of road vehicles. Compared with visual distraction, cognitive distraction is more challenging for detection due to the lack of apparent exterior features. This paper presents a novel real-time detection algorithm for driver cognitive distraction by using support vector machine (SVM). Data are collected from 26 subjects, driving in typical urban and highway scenarios in a simulator. The chosen urban scenario is the stop-controlled intersection and the highway scenario is the speed-limited highway. Driver cognitive distraction while driving is induced by clock tasks which compete with the main driving tasks for visuospatial short working memory. For each subject, distracted driving instances and the equal number of non-distracted driving instances were collected (24 for urban scenario and 20 for highway scenario in total). Features concerning both driving performance and eye movement are used for training and validation. The proposed algorithm have correct rate of 93.0% and 98.5% for highway and urban scenarios respectively. Results also show that driver distraction can be recognized 6.5 s to 9.0 s after its happening, indicating good performance of the detection algorithm.

Lane change maneuver recognition is critical in driver characteristics analysis and driver behavior modeling for active safety systems. This paper presents an enhanced classification method to recognize lane change maneuver by using optimized features exclusively extracted from vehicle state and driver operation signals. The sequential forward floating selection (SFFS) algorithm was adopted to select the optimized feature set to maximize the k-nearest-neighbor classifier performance. The hidden Markov models (HMMs), based on the optimized feature set, were developed to classify driver lane change and lane keeping maneuvers. Fifteen drivers participated in the road test for validation with an accumulation of 2,200 km naturalistic driving data, from which 372 lane changes were extracted. Results show that the recognition rate of lane change maneuver achieves 88.2%. The numbers are 87.6% and 88.8% for left and right lane change maneuvers, respectively, superior to the results from conventional classifiers.

With the rapid motorization in countries such as China, the large number of vehicles has caused a dramatic increase of accidents. Thus, the needs for active safety systems are urgent; the system designs must fulfill drivers' needs and local situations. Many studies have indicated that auditory design has great potentials for presenting traffic information to the drivers. In this study, the aim is to understand Chinese drivers' attitudes toward 3D Auditory Traffic Information System, and to explore Chinese drivers' requirements for traffic information support. In the experiment, 23 car drivers were invited to focus group discussions. The results illustrated that the majority (19 out of 23) of participants are interested in 3D auditory design concept and have strong preferences towards using meaningful sounds as the basis for auditory icons. Results also showed differences between experienced and novice drivers regarding how to prioritize traffic information under different traffic conditions. The findings have implications for future design of 3D auditory traffic information system development.