Empirical Estimation of Shortest Route Length along U.S. Interstate Highways Based on Great Circle Distance

In this study, 98 regression models were specified for easily estimating shortest distances based on great circle distances along the U.S. interstate highways nationwide and for each of the continental 48 states. This allows transportation professionals to quickly generate distance, or even distance matrix, without expending significant efforts on complicated shortest path calculations. For simple usage by all professionals, all models are present in the simple linear regression form. Only one explanatory variable, the great circle distance, is considered to calculate the route distance. For each geographic scope (i.e., the national or one of the states), two different models were considered, with and without the intercept. Based on the adjusted R-squared, it was observed that models without intercepts generally have better fitness. All these models generally have good fitness with the linear regression relationship between the great circle distance and route distance. At the state level, significant variations in the slope coefficients between the state-level models were also observed. Furthermore, a preliminary analysis of the effect of highway density on this variation was conducted.

Truck-Platoonable Pavement Sections in Illinois’ Network

Truck platooning has many benefits over traditional truck mobility. Literature shows that platooning improves safety and reduces fuel consumption between 5% and 15% based on platoon configuration. In Illinois, trucks carry more than 50% of freight tonnage and constitute 25% of the traffic on interstates. Deployment of truck platooning within interstate highways would result in significant fuel savings, but may have a direct impact on flexible pavement performance. The channelization of the platoon and reduced rest time between consecutive loads would accelerate the damage accumulation at the channelized position. Ultimately, this would lead to pavement service life reduction and a subsequent increase in maintenance and rehabilitation costs. Therefore, the main objective of this project is to quantify the effects of platooning on flexible pavements and provide guidelines for the state of Illinois by considering the aforementioned factors. Although the benefits of platooning are quantifiable, not every truck route is platoonable. For efficient platooning, trucks need to travel at a constant high speed for extended distances. The integrity of the platoon should be preserved because interfering vehicles would compromise the platooning benefits and road safety. An introduced high-level approach considers the volume/capacity of a roadway and the expected number of highway exit and entry conflicts. Using these parameters, each roadway section is assigned a level of platoonability, ranging from one to five—with five being the highest. A framework was developed to analyze the Illinois highway network. It was found that 89% of the network highway is platoonable under average capacity conditions.

Legal and Permit Loads Evaluation for Indiana Bridges

According to federal law, routine commercial vehicles must adhere to certain limits on their load configuration in order to operate legally on interstate highways. However, states may allow for heavier or different load configurations provided that bridges on the state and county highway system are load rated and, if necessary, posted with vehicles that appropriately represent these loads. The state of Indiana allows several classes of vehicles to operate with loads that exceed federal limits, and, presently, several LFD design loads are used to represent these exceptions as state legal loads. This study evaluates the MBE rating loads for their ability to encompass Indiana’s exception vehicles and recommends a set of state rating loads which can replace the current state legal loads and, combined with the MBE rating loads, satisfactorily encompass the load effects due to these exceptions. Comparing moment and shear envelopes on a representative set of bridges, the MBE rating vehicles were found to be insufficient for representing Indiana’s exception vehicles. Three new rating loads are proposed which encompass the exception vehicles efficiently and represent realistic legal loads. Conversely, acceptable HS-20 rating factors are also provided as an alternative to the adoption of these new vehicles. These rating factors, all 1.0 or greater, can ensure a similar level of safety by requiring a specific amount of excess capacity for the HS-20 design load.

Fatal Crashes Among Drivers Age 60+ in Connecticut, Massachusetts, New Hampshire, and Rhode Island

Fatal crashes are related with the spatial components of physical environments (e.g. roadways, land use, and political boundaries). This study compares rates of fatal crashes among drivers age 60+ by counties in 4 states of CT, MA, NH, and RI. The GIS application is used to visualize the location of fatal crashes and to identify whether it is clustered as hotspots. This study pooled data related to fatal crashes in CT, MA, NH, and RI from the Fatal Accident Recording System (2008-2018). Sample (n=2,373) inclusion criteria were subjects (driver age 60+) had to have complete data on variables of interest and be involved in a crash with at least one fatality. More than half (n=1,387, 58.5%) of drivers had a fatal injury. Results showed that the county with the highest incidents of fatal crashes was New Haven, CT (n=183 involved, 53% fatality), Worcester, MA (n=179, 61.5% respectively), Hillsborough, NH (n=75, 65.3% respectively), and Providence, RI (n=94, 59.6% respectively). The GIS spatial analysis showed that crashes were clustered along roads with the highest speed limits (interstate highways or multilane state routes) and found that the hotspots of clustered fatal crashes were located in counties with big cities with high population densities (New Haven CT, Hartford CT, Springfield MA, Worcester MA, Boston MA, Concord NH, and Providence RI). Identification of these crash hotspots will be beneficial for drivers and policy makers. The findings may alert drivers to high risk areas and policy makers can implement countermeasures.