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This research explores correlations between travel time-based measures, comprehensively, by year, day-of-the-week (DoW), time-of-the-day (ToD), week-of-the-year (WoY), and the posted speed limit using raw one-minute interval travel time data for 3,290 road links in Charlotte, North Carolina. The data were processed, normalized, and categorized into 57 datasets accounting for the year, DoW, ToD, WoY, and the posted speed limit. Pearson correlation coefficient matrices were generated to explore the correlations between travel time measures (minimum, maximum, and average; 10th, 15th, 50th, 85th, 90th, and 95th percentile travel times), travel time reliability measures (buffer time – BT, buffer time index – BTI, planning time index – PTI, and travel time index – TTI), and travel time variability measures (based on 90th, 85th, 15th and 10th percentile travel times). The percentages based on scores associated with the correlations were also examined. Travel time measures and travel time variability measures are moderately or highly correlated with each other. BT is moderately or highly correlated with all other measures, while the correlation between BTI, PTI and TTI and travel time measures is relatively low. There is a positive correlation between BTI and PTI and a negative correlation between BTI and TTI in most instances.

This research is carried out to evaluate the efficacy of toll roads in reducing travel time and improving travel time reliability on links within its vicinity, using data for the Triangle Expresswa...

This paper provides insights pertaining to the validity of a regional travel demand model in mimicking real-world travel times. The estimated travel times from the regional travel demand model, for the base year 2015, for Mecklenburg County in the city of Charlotte, North Carolina (NC) were compared with travel time statistics from a private data source, for the same year. The results indicate that the estimated travel times from the regional travel demand model are typically lower than the 85th percentile travel times, irrespective of the link speed limit. The estimated travel times for the Central Business District (CBD) area type are moderately correlated with the travel time statistics from the private data source, irrespective of the time of the day. For all the other area types, stronger correlations were observed when the estimated travel times from the regional travel demand model are compared with 10th to 50th percentile travel times. The calculated Pearson correlation coefficients are low for morning and evening peak periods compared to mid-day and night-time period, indicating the inability of the regional travel demand model in mimicking congested traffic conditions accurately.

This paper focuses on quantifying energy loss associated with recurring and nonrecurring congestion components and understanding its spatio-temporal variations in a geospatial environment. Data gat...

This study aims at identifying risk factors attributed to fatal fixed-object crashes on noninterstate roads. Logistic regression modeling was used to understand the relation or extent of the effect of selected independent variables on fatal fixed-object crashes on noninterstate roads. A total of 30 independent variables were considered in this study. At a 95% confidence interval, nine independent variables were found to play a statistically significant role on fatal fixed-object crashes on noninterstate roads. The probability of getting involved in a fatal fixed-object crash on noninterstate roads with full access control is lower compared to noninterstate roads with no access control. Rolling terrain reduces the probability of getting involved in a noninterstate fatal fixed-object crash. Older drivers are more likely to be killed in a noninterstate fatal fixed-object crash. Drivers under the influence of alcohol are four times more likely to be killed in a noninterstate fatal fixed-object crash c...

The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature.Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity.Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway.The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.

This article focuses on whether hydrogen-power technology is suitable for light rail operation and how a hydrogen-powered train’s energy use and emission production compare with a conventional electric light rail train. The results of the simulations indicate that a hydrogen train and a hydrogen-hybrid train are technically feasible for operation on the Blue Line Extension light rail project. Both concept trains complete a round-trip journey quicker than the electric train and have similar power-to-weight ratios. Due to increased mass and volume requirements, the hydrogen and hydrogen-hybrid trains require additional energy at the wheels for propulsion, 10.1% and 10.7% more, respectively. The electric train, due to improved efficiencies throughout the energy pathway, uses substantially less feedstock energy. The hydrogen and hydrogen-hybrid trains produce 162% and 85% more CO2 emissions per year, respectively, than the electric train. Overall, while operational performance is comparable, the hydro...

This paper focuses on an analysis of pedestrian and motorists' actions at sites with pedestrian hybrid beacons and assesses their effectiveness in improving the safety of pedestrians. Descriptive and statistical analyses (one-tail two-sample T-test and two-proportion Z-test) were conducted using field data collected during morning and evening peak hours at three study sites in the city of Charlotte, NC, before and after the installation of pedestrian hybrid beacons. Further, an analysis was conducted to assess the change in pedestrian and motorists' actions over time (before the installation; 1 month, 3 months, 6 months, and 12 months after the installation). Results showed an increase in average traffic speed at one of the pedestrian hybrid beacon sites while no specific trends were observed at the other two pedestrian hybrid beacon sites. A decrease in the number of motorists not yielding to pedestrians, pedestrians trapped in the middle of the street, and pedestrian-vehicle conflicts were observed at all the three pedestrian hybrid beacon sites. The installation of pedestrian hybrid beacons did not have a negative effect on pedestrian actions at two out of the three sites. Improvements seem to be relatively more consistent 3 months after the installation of the pedestrian hybrid beacon.

This paper evaluates the direct and indirect effects of introducing a permitted phase, through the use of flashing yellow arrow (FYA) signal for left-turning vehicles, in reducing crashes at intersections. Data for 18 study intersections in the city of Charlotte, NC, USA were used to conduct a before-after comparison study through the use of Empirical Bayes (EB) method and examine the effects. The estimated number of left-turn crashes, had the FYA signal not been installed, was compared to the actual number of left-turn crashes to assess the direct effect, while the estimated total number of crashes, had the FYA signal not been installed, was compared to the actual total number of crashes to assess the indirect effect. Only left-turn crashes along a selected FYA leg were used to examine the direct effect as the number of legs (approaches) with the FYA signal varied between the selected study intersections. The results obtained indicate that the FYA signal helps reduce the left-turn crashes (direct effect). It does not lead to any negative consequences. Instead, the FYA signal has the potential to indirectly lower the total number of crashes (indirect effect) and contribute to improved safety at intersections.

The time left to cross the street displayed on pedestrian countdown signals can be used by pedestrians as well as drivers of vehicles, though these signals are primarily provided to help pedestrians make better crossing decisions at signalized intersections. This article presents an evaluation of the effect of pedestrian countdown signals in reducing vehicle-pedestrian crashes and all crashes at signalized intersections.A before-and-after study approach was adopted to evaluate the effect considering pedestrian countdown signals installed over a 5-month period at 106 signalized intersections in the city of Charlotte, North Carolina.Analysis conducted at 95 percent confidence level showed that there has been a statistically insignificant decrease in vehicle-pedestrian crashes but a statistically significant decrease in all (includes vehicle-pedestrian and vehicle(s) only involved) crashes after the installation of pedestrian countdown signals. No negative consequences were observed after the installation of pedestrian countdown signals. Sixty-eight percent of the signalized intersections saw a decrease in the total number of all crashes, and 4 percent of the signalized intersections have not seen any change in the number of all crashes after the installation of pedestrian countdown signals. Improvements in terms of decrease in the total number of all crashes was high at signalized intersections with greater than 10 crashes per year during the before period. Likewise, decrease in the number of all crashes was high at signalized intersections with traffic volume between 7 AM to 7 PM greater than 20,000 vehicles during the before period.Based on results obtained, it can be concluded that pedestrians as well as drivers are making better decisions using the time left to cross the street displayed on pedestrian countdown signals at signalized intersections in the city of Charlotte, North Carolina.