The authors in this study examined the travel speed characteristics of passenger vehicles, trucks, and buses through different states with different speed limits policies, to arise and make certain of the effects of Differential speed limits (DSL) against Uniform speed limits (USL). The spot-speed data in this study was collected from the states of Indiana, Michigan, and Ohio. The data collected helped to examine the speed characteristics along the same freeways along several speed limit settings.
The idea of DSL and USL arises because if the fact that vehicles that travels with excessively lower or higher speed limits usually causes collisions. This raised an argument whether to have a Uniform or differential speed limits policies for vehicles and trucks. The supporting argument for DSL is, the trucks require greater time and distance to stop and that would cause severe casualties due to the size of the truck. Against supporting argument for USL is that increase speed differences between vehicles may increase the potential for collisions. The main focus of this article was the operational aspect of speed limits specially how speed limits affected travel speeds and how speed characteristics differed on roadways in states with USL policies versus those with DSL policies. The three principle speed measures (mean speed, 85th percentile speed, and speed variance) were used in this study, while other aspects as roadway geometry, traffic volumes, and other factors were controlled. This study would eventually help to give more insight for decision makers whether to do any changes to their speed limit policies.
Most of the earlier studies (Literature reviews) about this matter, whether to choose between DSL or USL, didn’t have any actual results that would prove significant in giving a decision in this matter. In Europe, they even stated after most of their studies that “a strong case cannot be made on empirical ground in support of or opposition to differential speed limits. ”The data collected were tested using Statistical methods and having the three performance measures (mean speed, 85th percentile speed, and speed variance) on separate models helped to analyze the speed characteristics on the three states studied (Michigan, Indiana, and Ohio). Also, ordinary least squares (OLS) regression models were estimated with the field-collected spot-speed data.
The results of this study shows that the three speed measures that were analyzed had a huge impact on this study along with two primary factors: posted speed limit and percentage of trucks. Through the results and analyses we can see that the variability in travel speeds, as measured by the site-specific standard deviation, in general was lowest at locations with USLs; the minimum occurred at locations posted at 70 mph. Speeds were most variable at locations inMichigan with a 10 mph differential limit, as well as at urban locations in Michigan and Indiana where the speed limits were posted at a uniform 55 mph. the mean and 85th percentile was quite consistent for passenger vehicles across the three states tested, in comparison to truck and bus that had more variable speed probably because of DSLs. Some factors weren’t taken into this study that might have had a significant change into the results show.
For instance, Factors such as differences between states in levels of traffic law enforcement might have affected driving speeds and the inclusion of the state-specific speed limit variables for the urban sites could have accounted for potential differences in driving population to some extent. Also, the study focused narrowly on segments with limited horizontal or vertical curvature and didn’t take into consideration for the local factors. The study focus on the operational factors of speed limit and didn’t take into consideration the safety and environmental impacts.
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