Objective: Although a considerable amount of prior research has investigated the impacts of speed limits on traffic safety and operations, much of this research, and nearly all of the research related to differential speed limits, has been specific to limited access freeways. The unique safety and operational issues on highways without access control create difficulty relating the conclusions from prior freeway-related speed limit research to 2-lane highways, particularly research on differential limits due to passing limitations and subsequent queuing. Therefore, the objective of this study was to assess differences in driver speed selection with respect to the posted speed limit on rural 2-lane highways, with a particular emphasis on the differences between uniform and differential speed limits.
Methods: Data were collected from nearly 59,000 vehicles across 320 sites in Montana and 4 neighboring states. Differences in mean speeds, 85th percentile speeds, and the standard deviation in speeds for free-flowing vehicles were examined across these sites using ordinary least squares regression models.
Results: Ultimately, the results of the analysis show that the mean speed, 85th percentile speed, and variability in travel speeds for free-flowing vehicles on 2-lane highways are generally lower at locations with uniform 65 mph speed limits, compared to locations with differential limits of 70 mph for cars and 60 mph for trucks.
Conclusions: In addition to posted speed limits, several site characteristics were shown to influence speed selection including shoulder widths, frequency of horizontal curves, percentage of the segment that included no passing zones, and hourly volumes. Differences in vehicle speed characteristics were also observed between states, indicating that speed selection may also be influenced by local factors, such as driver population or enforcement. 相似文献
Highway stormwater runoff quality data were collected from throughout California during 2000-2003. Samples were analyzed for conventional pollutants (pH, conductivity, hardness, and temperature); aggregates (TSS, TDS, TOC, DOC); total and dissolved metals (As, Cd, Cr, Cu, Ni, Pb, and Zn); and nutrients (NO(3)-N, TKN, total P, and ortho-P). Storm event and site characteristics for each sampling site were recorded. A statistical summary for chemical characteristics of highway runoff is provided based on statewide urban and non-urban highways. Constituent event mean concentrations (EMCs) were generally higher in urban highways than in non-urban highways. The chemical characteristics of highway runoff in California were compared with national highway runoff chemical characterization data. The results obtained in California were generally similar to those found in other states. The median EMC for Pb measured in studies conducted in previous decades was much higher than the current median Pb EMC in California. The lower Pb EMC in California compared to previous highway runoff monitoring is believed to be due to the elimination of leaded gasoline. An attempt was also made to identify surrogate constituents within a general family of water quality categories using Spearman correlations and selected pairs with Spearman coefficients greater than 0.8. The strongest correlations were observed among parameters associated with dissolved minerals (EC, TDS, and chloride); organic carbon (TOC and DOC); petroleum hydrocarbons (TPH and O & G); and particulate matter (TSS and turbidity). Within the metals category, total iron concentration was highly correlated with most total metal concentrations. The correlations between total and dissolved concentrations were all less than 0.8, even between total and dissolved concentrations of the same metals. Multiple linear regression (MLR) analyses were performed to evaluate the impact of various site and storm event variables on highway runoff constituent EMCs. Parameters found to have significant impacts on highway runoff constituent EMCs include: total event rainfall (TER); cumulative seasonal rainfall (CSR); antecedent dry period (ADP); contributing drainage area (DA); and annual average daily traffic (AADT). Surrounding land use and geographic regions were also determined to have a significant impact on runoff quality. The MLR model was also used to predict constituent EMCs. Model performance determined by comparing predicted and measured values showed good agreement for most constituents. 相似文献