Journal of Transportation Engineering, Part A: Systems

This study focuses on the comparison of operating mode distributions and other assumptions used in the estimation of transit bus emissions with the motor vehicle emission simulator (MOVES). The study area is the city of Montreal, Canada, where a single transit provider operates bus service along 220 routes. For this purpose, instantaneous speeds and passenger ridership data were collected onboard a total of 96 buses during the summer and fall of 2013. The data collection campaign covered eight bus routes in Montreal. The selected routes serve a range of corridor types capturing a variability in land use, road geometry, traffic flow, bus type, and transit service. Ultimately, the authors analyzed data from 3,702 road segments amounting to approximately 975.5 km (606 mi) with bus service. Significant differences between locally derived operating mode distributions and MOVES2014 default distributions were observed. The MOVES distributions assume a significantly larger portion of idling than that obtained from local data. The authors also investigated the drive cycle characteristics of different bus types and observed differences between standard and articulated buses, which are currently unaccounted for by MOVES. The findings illustrate the importance of collecting local bus data when estimating transit emissions.

Entry and exit areas are considered critical parts of freeways and expressways. In order to meet traffic safety and operation requirements, it is important that ramps and speed-change lanes have the appropriate design so that vehicles may complete sequential maneuvers. However, literature on risks associated with these freeway elements is limited and has often demonstrated contradictory results. The present research meta-analyzes the effects of ramp and speed-change lane characteristics on crash outcomes. A random-effects meta-analysis was conducted on the effect of ramp length on crash severity, and a nonsignificant overall effect is observed. Similarly, random-effects meta-analyses regarding deceleration lane length suggested a nonsignificant effect on road safety (both on frequency and severity) at a 95% level of confidence. There is no indication of strong publication bias in any of the meta-analyses performed. Overall, the results suggest that, although several individual studies reported significant effects of these design elements on road safety, there is a need for further research, especially in a broader geographical context because of heterogeneous results.

Maintenance management has been relying heavily on collecting asset condition information to plan for maintenance activities and budget allocation. Data collection is often conducted on a sampling basis because of resource constraints. There is thus a perceived need for the development of an effective sampling framework that can determine statistically representative samples, reflect the true level of maintenance (LOM) at state/region/station levels, and accommodate agencies’ requirements. The paper advances existing knowledge by presenting a systemic approach for a sampling scheme development to assist maintenance activity planning. The proposed method addresses how much and where the agencies need to collect asset condition data for accurate LOM estimation. The method integrates Fisher information with a spatial sampling technique that can be customized based on local agencies’ requirements, such as station balanced, spatially balanced, or others. The framework is showcased via an example application of the Signage Repair and Replace database maintained by the Utah Department of Transportation (UDOT). Four sampling methods that might be tempered to various needs are implemented. Sampling results are presented and compared against historical full asset inventory via similarity analysis. The proposed framework lays a strong theoretical foundation for maintenance asset sampling and is effective for estimating LOM at state, region, and station levels to assist with budget allocation. The method can be easily transferable and adaptable to other agencies for optimal maintenance management.

Checking roundabout sight distance is currently performed graphically. This paper develops analytical models for lateral clearance at symmetrical single-lane roundabouts based on intersection sight distance (ISD) and establishes related geometric design guidelines. The models are developed for two cases: an approach vehicle ahead of the yield line and before the crosswalk (Case 1), and a stationary vehicle at the yield line (Case 2). Sight distances to the respective conflicting-circulating and entering vehicles are analyzed. The maximum lateral clearance is formulated for each case using mathematical optimization. The results show that both cases of the approach and stationary vehicles are critical and therefore should be included in the ISD analysis at roundabouts. Using the developed models, design guidelines are established for the radius of the central island, entry-curve lateral clearance, exit crosswalk location, and driver’s field of peripheral vision.

Diverging diamond interchanges (DDIs) are one of most successful unconventional type of diamond interchanges in the United States. This paper examines additional lost time due to internal link queue presence in DDIs. First, an analytical approach was developed providing a step-by-step method to predict the additional lost time at the crossover movements. Second, actual field data were collected to validate the analytical approach of comparing additional lost time using the team’s analytically derived approach to that of actual field data. The analytical method was proven to be a valid prediction of the additional lost time at the ramp terminal intersections. In addition, unique signal timing of DDIs is presented, showing efficient interchange operation under heavy traffic condition on arterials.

Traffic flow, its characteristics, and road quality service are usually estimated by using aggregated and averaged data from multiple lanes; however, in real experiences, there is significant variability in traffic-flow parameters across the different freeway lanes. Among the numerous factors that affect traffic distribution are vehicular composition, driver behavior, regulations about passing and overtaking, lane discipline, and designated lanes. Because these factors are very specific, the models and values for traffic distribution in a multilane freeway segment are highly sensitive to their national context. This study starts from an analysis of the capacity of a three-lane test segment within the Italian freeway system, and then examines the manner in which the flow and density vary across the freeway lanes. The analysis is restricted to up-to-capacity conditions and nonlinear regression models of the distribution relationships are calibrated for each lane, for both flow and density ratios, as a function of the total flow. The nonhomogeneous use of freeway lanes in Italy can be qualified and quantified through the trends found in these ratios, and then compared with similar internationally focused studies. This provides a useful interpretation of driver behavior, and is also a reference for calibrating traffic models, supporting design and operational processes and the implementation of intelligent transportation systems (ITSs) that are consistent with the national context.