The general relationships between hourly accident rates and hourly traffic volume/capacity ( v/c) ratios were examined. A 26 km (16 mi) segment of Interstate I-94 in the Detroit area was selected as the study segment. The v/c ratios were calculated from average hourly traffic volume counts collected in 1993 and 1994 from three permanent count stations. Accident rates were derived from hourly distributed number of accidents in the same 2 years. The correlation between v/c values and accident rates follows a general U-shaped pattern. The study of all observed accidents combined indicates that accident rates are highest in the very low hourly v/c range, decrease rapidly with increasing v/c ratio, and then gradually increase as the v/c ratio continues to increase. U-shaped models also explain the relationship between v/c and accident rates for weekdays and weekend days, multivehicle, rear-end, and property-damage-only accidents. On the other hand, single-vehicle, fixed-object, and turnover accidents, and accidents involving injury and fatality follow a generally decreasing trend with increasing v/c ratio. Traffic conflict is viewed as a major contributing factor to high accident rates observed in the high v/c range, whereas night conditions and driver inattention were identified as explanatory factors for the occurrence of high accident rates in the low v/c ranges.

Speed-flow relationships have been established for different free-flow speeds on urban freeways. However, there have been few research efforts relating real-time traffic flow parameters and weather conditions for different levels of heavy vehicle traffic. This study aims at establishing relationships between speed and volume in freeway sections using Remote Traffic Microwave Sensor (RTMS) data as a function of weather conditions. Historical weather and RTMS detector data (i.e., volume and speed) from two highway corridors in the Istanbul metropolitan area are used for this purpose. Empirical relationships between traffic speed and volume are analyzed by weather condition (clear, rain, fog/mist/haze, or snow), surface condition (dry, wet, or icy), and percentage of heavy vehicles in the traffic mix. The findings from the analysis show that rain reduced the average vehicular speeds by 8 to 12% and the capacity by 7-8%. Moreover, wet surface conditions resulted in a reduction of average speeds by 6 to 7% and light snow affected demand leading to a significant reduction in traffic volume

Objective: External distraction appears to affect at least 6–9% of distraction-affected motor vehicle collisions. Billboards may be good models for studying external distraction in general, and it is also desirable to understand billboard-related distraction per se. However, there has not yet been a clear consensus on the scope of billboard-related distraction or its dynamics with respect to characteristics of drivers, billboards, traffic, and the roadway. To narrow these knowledge gaps, a systematic literature review was conducted on billboard-related changes in driver visual behavior. Methods: A systematic literature search yielded 443 results, of which 8 studies met all inclusion criteria. Five studies meeting all inclusion criteria were later identified and added. Results were analyzed in terms of 4 categories of visual behavior: (1) gaze variability (GV), glance pattern activity (GPA), and percentage of time spent glancing at the forward roadway; (2) glances at unexpected drive-relevant stimuli; (3) glances at expected drive-relevant stimuli; and (4) glances at billboards. Results: There was considerable evidence that about 10–20% of all glances at billboards were ≥0.75 s, that active billboards drew more glances and more long glances (≥0.75 s, ≥2.0 s) than passive billboards but did not attract a longer average glance, and that there was large variability among individual billboards within categories (e.g., active vs. passive). The extent to which billboards attracted glances ≥ 2.0 s was uncertain. There was tentative evidence that billboards did not affect GPA, glances at expected drive-relevant stimuli, or the proportion of time drivers spent glancing at the forward roadway and that they did affect vertical GV and glances at unexpected drive-relevant stimuli. Conclusions: Generally, billboard-related distraction appeared to be minor and regulated by drivers as the demands of the driving task changed. However, this review's findings suggest that this may not be true in all cases. Future research should emphasize the tails of the distribution in addition to average cases, in terms of both the analysis of visual behavior and the complexity of driving tasks. Further research is also needed to understand the effects of billboard design, driver characteristics, and road and traffic context.