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Baltimore Highlands, MD, United States

Ginzburg H.,Parsons Brinckerhoff | Liu X.,Parsons Brinckerhoff | Baker M.,URS Corporation | Shreeve R.,Maryland State Highway Administration | And 3 more authors.
Journal of the Air and Waste Management Association | Year: 2015

The Maryland State Highway Administration (SHA) monitoring program monitored the impact of vehicular emissions on the concentrations of the fine particles smaller than 2.5 microns (PM2.5). PM2.5 concentrations were monitored in close proximity to a highway in order to determine whether traffic conditions on the roadway impact concentrations at this location. The monitoring program attempted to connect monitored concentrations with the roadway traffic exhaust or with the other sources of PM2.5. PM2.5 concentrations were collected near the Capital Beltway (I-495/I-95) in Largo, Maryland. The monitoring program was launched on May 13, 2009 and continued through the end of 2012. Two co-located monitors, one for continuous PM2.5 measurements and the other for speciation measurements, were used in this program. Meteorological and traffic information was also continuously collected at or near the monitoring site. Additionally, data from the two other monitoring locations, one at the Howard University-Beltsville, MD and one at McMillan Reservoir, DC, was used for comparison with the data collected at the SHA monitoring location. The samples collected by the speciation monitor were analyzed at the RTI and DRI Laboratories to determine the composition and the sources of the collected PM2.5 samples. Based on the apportionment analysis, the contribution of roadway sources is about 12 to 17 percent of PM2.5 at the near-road site. © 2015 A&WMA. Source


Maji A.,Maryland State Highway Administration | Jha M.K.,Morgan State University
Advances in Transportation Studies | Year: 2011

The available Highway Alignment Optimization (HAO) algorithms use either single-objective or multiobjective approaches. These algorithms consider different highway alignment costs along with restricted land use information such as forests, wetland, etc. as the primary objectives which are minimized in the process of highway alignment optimization. In single-objective HAO approaches, different highway alignment sensitive costs are formulated and added to obtain the total highway alignment cost in monetary value. The total highway alignment cost is used as the primary objective function in the single-objective HAO. This method, upon optimal search, yields a highway alignment with minimum total highway alignment cost. As part of the total highway alignment cost, the restricted land use is expected to be minimized in the optimization process. Whereas in the multi-objective optimization approach the highway alignment cost and restricted land use information are maintained separate and optimized simultaneously. This way, the multi-objective HAO helps to yield a set of Pareto-optimal solution with trade-off between highway alignment cost and the restricted land use information. The restricted land use information used in both optimization processes is derived from a geographical information system (GIS) database. It is cumbersome to express the highway alignment and associated objectives in mathematical formulations as required in classical optimization techniques. Hence, both methods use unconventional genetic algorithm (GA) based optimization approach. This paper compares single-objective HAO with multi-objective HAO and discusses their merits and demerits in a real-world example application. Source


Ogallo H.O.,Maryland State Highway Administration | Jha M.K.,Beulah Group | Jha M.K.,Morgan State University
Journal of Transportation Engineering | Year: 2014

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. © 2014 American Society of Civil Engineers. Source


Chang G.-L.,University of Maryland University College | Park S.Y.,University of Maryland University College | Paracha J.,Maryland State Highway Administration
Transportation Research Record | Year: 2011

Contending with recurrent congestion on commuting corridors has long been a challenging and pressing issue for responsible highway agencies. However, effective strategies to mitigate the congestion level and the accompanying safety issues on those highway segments remain to be developed. In response to such needs, this study presents an innovative system that integrates variable speed control and travel time information for alleviating day-to-day recurrent congestion on a highway corridor. The system presented in this study includes a set of algorithms for setting variable speeds for different highway segments based on traffic conditions detected from roadway sensors and a well-calibrated license-plate-recognition system for displaying the estimated travel time. Field experiments of the proposed system on MD-100 for 8 weeks showed that with proper speed control in real time, the congested highway segment can achieve a higher throughput, a stable traffic condition, and a shorter travel time. Source


Li Z.,University of Maryland University College | Tao R.,Maryland State Highway Administration
Transportation Research Record | Year: 2011

Congested freeway interchanges normally suffer from the spillback of off-ramp and on-ramp queues. The traffic signals around a congested interchange can also experience link-blockage and lane-blockage problems. For an overall system performance around an interchange to be improved, both freeway and arterial performance must be considered to optimize signal timings. This study extends the cell transmission concept and proposes a set of new formulations to capture the traffic dynamic with link blockage, lane blockage, and ramp spillback. On the basis of these formulations, an integrated control model for optimizing interchanges and a solution method based on a genetic algorithm are proposed. The model's performance was demonstrated in a case study with different traffic scenarios for the interchange connecting Georgia Avenue (MD-97) and the Capital Beltway (I-495) in Silver Spring, Maryland. The resulting signal timings were compared with those from TRANSYT-7F (Release 10). For fair comparison, this study used CORSIM, a third-party simulation package, as the performance evaluator. Results indicated that the proposed model was promising and could improve freeway and arterial performance. Source

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