The colloidal instability index (CII) has been widely used for testing the stability of asphaltenes as a classical method. In this study, five oil samples were tested by the CII method; the results obtained greatly differ from the real field results. In our investigation, we combined the Turbiscan LAB stability analyzer and saturate, aromatic, resin, and asphaltene (SARA) analysis to further investigate the asphaltene stability by heptane titration. The results revealed that there exists a threshold volume ratio before the asphaltenes destabilize. The stability of crude oil is related to the saturation solubility of asphaltenes. By testing the CII value of the crude oil in its current state and the CII value of the dissolved asphaltenes in its saturated state, we were able to propose a new way to judge the oil stability.

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Drivers' Smart Advisory SystemFuzzy logic Socio-demographic specifications Lane-changing model a b s t r a c t Lane-changing behavior is an important component of traffic simulation. A lane-changing action is normally confined to a decision-making process of the task, and the action itself is sometimes assumed as an instantaneous event. Besides, the lane-changing behavior is based mostly on observable positions and speeds of other vehicles, rather than on vehicles' intentions. In practice, changing one lane requires about 5e6 s to complete. Existing lanechanging models do not comprehensively consider drivers' response to work zone lanechanging signs (or other related messages, if any). Furthermore, drivers' socio-demographics are normally not taken into account. With regard to this, fuzzy logic-based lane-changing models that consider drivers' socio-demographics were developed to improve the realism of lane-changing maneuvers in work zones. Drivers' Smart Advisory System (DSAS) messages were provided as one of the scenarios. Drivers' responses, including reactions to work zone signs and DSAS messages, and actions to change lane, were investigated. Drivers' socio-demographic factors were primary independent variables, while Lane-Changing Response Time (LCRT) and Distance (LCRD) were defined as output variables. The model validation process yielded acceptable error ranges. To illustrate how these models can be used in traffic simulation, the LCRT and LCRD in work zones were estimated for five geo-locations with different socio-demographic specifications. Resultsshow that the DSAS is able to instruct all drivers to prepare and change lanes earlier, thereby shortening the duration of changing lanes. Educational background and age are essential variables, whereas the impacts of gender on the output variables are indistinctive. .e lsev ie r. co m/ lo cate/ j tte j o u r n a l o f t r a f fi c a n d t r a n s p o r t a t i o n e n g i n e e r i n g ( e n g l i s h e d i t i o n ) 2 0 1 5 ; 2 ( 5 ) : 3 1 3 e3 2 6 http://dx.

Objective: The objective of this research is to investigate the impacts of drivers' demographic factors on speed patterns in response to a smartphone based warning message, while driving through the advance warning area of a work zone. Methodology:A smartphone application was developed using Massachusetts Institute of Technology (MIT) App Inventor 2, which was used to provide test drivers with a warming message on traffic control and incident awareness. Twenty-four subjects with different demographic features (different gender, age, education background, and driving experience) were recruited to drive through an advance warning area of a work zone twice in two scenarios (with and without the warning message). The advance warning area was divided into three segments for the convenience of analysing the significant difference in subjects' reactions to the warning messages and the static traffic control signs, in terms of speed patterns. Findings:Under a traditional traffic control, drivers' driving speed patterns were not significantly sensitive to the four studied socio-demographic features; but their mean driving speeds and speed variance were noticeable higher than in the situation with an audio warning message. When the smartphone-based messages were provided, drivers drove noticeably slower within the work zone, and the variance became narrower in the most studies of sociodemographic features. Experienced drivers and highly educated drivers drove significantly slower after receiving a warning message from the second and third segment (AWM 2 and 3). Conclusion:The smartphone-based warning messages were able to help drivers to control their driving speed better for cautious driving in a work zone area, especially for the experienced and highly educated drivers driving through a merging area and an activity area of workers.