To investigate the impact of changes in pavement roughness on speed, this study developed a linear regression model to estimate free-flow speed on freeways in California. The explanatory variables include lane number, total number of lanes, day of the week, region (district), gasoline price, and pavement roughness as measured by the international roughness index (IRI). Data on the California freeway network from 2000 to 2011 were used to build the model. The results showed that pavement roughness has a very small effect on free-flow speed within the range of this study. For the IRI coverage in this study (90% of the records have an IRI of three $\mathrm{m}/\mathrm{km}$ or lower and 90% of the records have an IRI change of two $\mathrm{m}/\mathrm{km}$ or lower), a change of IRI of one $\mathrm{m}/\mathrm{km}$ ($63\mathrm{in.}/\mathrm{mi}$) results in a change of average free-flow speed of approximately $0.48–0.64\mathrm{km}/\mathrm{h}$ (0.3–0.4 mph). This result indicated that making a rough segment of pavement smoother through application of a maintenance or rehabilitation treatment will not result in substantially faster vehicle operating speeds, and therefore the energy and emission reductions gained from the reduced rolling resistance will not be offset by increased fuel consumption from faster speeds. However, developing a good model to predict the free-flow speed was not fully successful. The southern California interstate freeway model yielded the best result with an adjusted R-squared of 0.72. For the rest of the regions in the state, the selected explanatory variables can only explain approximately half of the total variance, indicating there are still other variables with more substantial effects on free-flow speed that were not covered in this study.

The ability of a pavement to withstand traffic loads and serve the motoring public in a safe and efficient manner is adversely affected by the observable pavement surface distresses. Therefore, monitoring the performance of pavement will help to objectively determine the current condition of the pavements and, consequently, a management plan for maintenance, rehabilitation, or reconstruction. The current study builds a complete vision system and integrates its output into geographic information systems (GIS) for automated pavement monitoring and management. The system consists of an image retrieval algorithm which increases the sampling of pavement image data and reduces the computational time for processing acquired data. Also, a novel model method for edge detection, called active contours or snakes, is introduced. The active contour models show promise in detecting pavement distresses in very noisy environments. Their ability to split and match different topologies of the image data is essential for accurate crack location and shape detection. Finally, the output of the vision system is successfully integrated into GIS through concepts such as automated georeferencing and vectorization. Overall, the system is designed to overcome challenges associated with platform differences, complete automation, and processing of massive data sets.

Existing geometric design guides provide deterministic design criteria for highway elements that ignore the uncertainty associated with many design parameters. Reliability analysis has been advocated as an approach to account for this uncertainty and to evaluate the risk associated with a particular design feature. This paper discusses one important application of reliability analysis: the calibration of geometric design models to yield consistent safety (risk) levels. The paper provides calibrated design charts for the middle ordinate $M$, defined as the lateral distance between edge of median barriers and centerline of the adjacent traffic lane, at different probability of noncompliance levels. The results show that the calibrated values of $M$ are generally lower than those derived from the AASHTO design guide. The calibrated design charts can offer designers dealing with highways with constricted right-of-way an option to use lower middle ordinate values and enable them to estimate the safety consequences of their decisions. Overall, the calibrated charts can aid the decision maker in determining the safety implications of deviating from geometric design standards and quantifying the safety level built in design values that are deemed acceptable.

A simulation process is presented for providing a point estimate of average traffic delay on minor roads at urban unsignalized intersections during peak hours. A performing process of microsimulation was carried out, and a good level of conformity was obtained between the traffic simulated in the peak hours and the corresponding amount of traffic measured in the field. Traffic performance measures expressed in terms of average delay suffered by vehicles on minor roads were used in the statistical analysis. A negative binomial regression model, jointly applied to conflict traffic volume (${\mathrm{VHP}}_c$) and traffic volume entering intersection from minor roads (${\mathrm{VHP}}_e$), was used to model the average delay. A dummy variable $D$ was also introduced to test the adequacy of the regression model through the range of hourly conflict traffic volumes. Regression parameters were estimated by the maximum likelihood method and the significance of the covariate was evaluated by using the likelihood ratio test (LRT). The results show that the average delay on minor roads is positively associated with ${\mathrm{VHP}}_c$, ${\mathrm{VHP}}_e$, and $D$, and these variables are all statistically significant. The regression model was found to fit well the average delays computed in simulation. Additionally, a stop-time model and a maximum queue length model were also developed.

Emergency medical service (EMS) providers participating in vehicle crash-induced incident management aim to offer as wide and efficient coverage as possible to meet the demand for incident responses effectively; however, the design and provision of efficient and cost-effective services are tough issues faced by emergency management authorities. This paper introduces a double standard model (DSM), along with a genetic algorithm (GA) for assigning EMS fleet from vehicle locations to intersection vehicle crash sites such that crash demand sites can be covered in accordance with two service coverage standards. Specifically, all demand sites are required to receive single coverage according to the secondary coverage standard and at least a portion ($\alpha$) of demand sites need to maintain single coverage as per the primary coverage standard. The proposed model is applied for top 200 intersections in the City of Chicago selected using intersection crash records for 2004–2010 according to crash frequency-based and severity-based scenarios. The top 200 intersections are split into high and low severity sites for model application. Using the EMS vehicle fleet size currently maintained by the Chicago Fire Department as 15 basic life support (BLS) and 60 advanced life support (ALS) ambulances, almost 100% of double vehicle coverage can be achieved. Extended model application is conducted by keeping 15 BLS ambulances unchanged and reducing the 60 ALS ambulances by 50% to 30. Results show that nearly 90% of double coverage according to the primary standard can still be reached.

Urban arterials in Shanghai usually have high intersection densities, which can lead to frequent and severe congestion. Research in this area of study focuses on urban arterial operating speed and its relationship with road geometry, traffic control, and traffic volume, and more study is needed before remedies to the congestion problems can be identified. In Shanghai, an opportunity exists to investigate urban arterial operating speed by accessing continuously updated global positioning system (GPS) data from taxis, hereafter called floating car data (FCD). With more than 50,000 taxis equipped with GPS running in the Shanghai road network, it is feasible to acquire comprehensive, citywide arterial speed measurements throughout the network. In this study, 45 arterials in Shanghai, which comprised of 177 two-direction segments bounded by signalized intersections, were selected for study. GPS data from taxis were captured during peak and off-peak hours to enable the calculation of the mean operating speed for each selected segment. Information of road geometry, traffic control, and traffic volume data was also acquired to examine their influence on operating speed. Multilevel linear regression models were utilized to analyze operating speed with the arterial level’s unobserved heterogeneity accounted for as well. It was identified that roadway design variables, including segment length, number of lanes, and horizontal degree of curvature, left-turn lane types, and presence of median along with saturation degree, are all significantly related to the operating speed. The results of this study shed some light on roadway design, roadway improvement, and traffic management.

This paper presents a methodology for critical gap analysis at signalized intersections with unprotected opposing left-turn movements. Highway capacity manual (HCM) methodology for estimating potential capacity uses base critical gap and base follow-up time, which are adjusted to reflect specific conditions of each intersection. That methodology assumes an unobstructed line-of-sight for drivers while executing left-turn maneuvers. However, the line-of-sight is not always unimpeded. Previous studies have shown that leading noncompact (larger and taller) vehicles and vehicles in the opposing left-turn lane may impede the line-of-sight. Specifically, the studies have demonstrated that the impedance may result in a capacity reduction. In order to quantify the capacity reduction, we present a methodology to modify the HCM critical gap and follow-up time model when the line-of-sight of unprotected left turn maneuver is obstructed. We introduce new adjustment factors to account for vehicles in the opposing left-turn lane obstructing the line-of-sight during the left-turn maneuver. Using field data from Baltimore and Annapolis, Maryland, we show that the obstruction increases the left-turn critical gap and the left-turn follow-up time, and hence decreases the potential capacity for left turns at intersections with unprotected left-turn movements. This capacity reduction may be a significant contributor to systemwide delay during rush hour, and may influence dilemma zone and red light running behavior, which are subjects of future research.

The capacity of a freeway segment is a critical factor for the planning, design, and analysis of freeway facilities. The Highway Capacity Manual (HCM) is considered to be one of the authoritative sources on capacity values for a variety of roadway types in the United States, particularly for planning purposes. For basic freeway segments, a single set of capacity values are provided as a function of free-flow speed. Although these values are considered to be reasonably representative values for freeways located throughout the United States, the HCM does not provide any guidance on how its recommended values can be adjusted to reflect significant differences in capacity due to local conditions, nor how to directly measure or estimate capacity values. With the recent development of a statewide freeway traffic data archive in Florida, the Florida Department of Transportation (FDOT) desired to use these data to determine if the freeway capacity values in the HCM were appropriate for Florida freeway level of service analyses for planning and preliminary engineering applications. This study evaluated two previously published methods for estimating freeway capacity, identified their advantages and disadvantages for use in planning applications, and ultimately recommended a method for use by FDOT. One of the chosen methods determines capacity from a mathematical function generated from speed-flow data points and the other chosen method uses the concept of breakdown probability distribution to determine capacity. Neither of these methods proved desirable for planning applications due to computational burden; thus, an alternate, simplified approach was developed that used a simple averaging method of highest flow rates to determine capacity.