Modeling the Impact of Road Grade on Driving Behavior, Vehicle Energy Consumption, and Emissions
Haobing Liu
Motor vehicle emissions and their impacts on local air pollutant concentrations are a primary concern in cities. Properly quantifying energy and emissions is the key step in identifying the major sources of air pollution, evaluating whether transportation activities are consistent with air quality goals, and providing decision makers with reference for implementation of new policies for sustainable development. Mathematical models are commonly used to predict vehicle energy consumption and emissions. Vehicle-specific power (VSP) is widely used in such models to evaluate engine load, and it is represented as a function of vehicle mass, vehicle dynamic parameters (rolling/drag coefficient), driving behavior (speed and acceleration) and road conditions (gravitational acceleration and road gradient). In the U.S. Environmental Protection Agency’s (USEPA’s) MOVES (MOtor Vehicle Emission Simulator) model, speed and VSP levels are tied to vehicle energy consumption and emission rates. Detailed and accurate speed-acceleration joint distributions (SAJDs, also known as Watson plots) can be used to reflect onroad activity required for calculating the distribution of activities in MOVES VSP and speed bins, and thus for estimating vehicle energy consumption and emissions. Road grade is also a critical variable that affects engine operations, as uphill grades require that the engine perform additional work against gravity in the direction of vehicle motion (while downhill grades obtain an energy benefit). More..
Advanced Transit Vehicle Modal Emissions Model for Optimizing Transit System Operations
Xiaodan Xu
Properly estimating transit energy use is a critical element of transit system planning. Reasonable predictions of energy consumption are needed by transit agencies and stakeholders to select proper fleet, arrange vehicle operations, develop improvement plans, etc. However, the current models used to estimate transit energy use at the vehicle level are quite limited, in part because few models were specifically designed for transit systems. Current energy models may fail to capture some key operation elements such as stop frequency and passenger load (“over-simplify”), or asking for input or configuration information which is too difficult for most people to obtain (“over-specify”). More..
A Framework for Optimizing Public Transit Bus Fleet Conversion to Alternative Fuels
Hanyan Li
Alternative fuel buses (hybrid-electric, battery-electric, compressed natural gas, etc.) have great potential to reduce lifecycle energy use and criteria pollutant emissions from urban and rural transit fleets. However, market penetration of alternative fuel transit buses in the U.S. is currently below 50%. There are a number of barriers to entry that discourages switching from traditional diesel vehicles. Alternative fuel buses have higher capital costs, and the uncertainty associated with fuel savings and potential increases in maintenance costs introduce uncertainty into estimated the time it will take to recover capital investments (whereas diesel vehicle costs are well-known). Discrepancies between the claimed fuel economy and real-world performance under variable and diverse traffic conditions, roadway configurations, and designated routings contribute to economic uncertainty. Some vehicles, such as battery-electric buses and even some hybrid-electric buses, have significant range and performance constraints (maximum speed and acceleration rates under load) that prevent their use on certain routes.More..
Traffic Control Measure Impacts on Mode Choice, Energy Use, and Emissions using an Activity Based Modeling Framework and MOVES
Yingping Zhao
“Transportation control measures” (TCMs) is a general term for a wide variety of strategies designed to improve transportation system efficiency to reduce congestion, energy use, and emissions. In transportation planning processes, it is critical to be able to assess the costs and potential congestion mitigation, energy reduction, emission reduction impacts of TCMs prior to implementing such strategies into transportation plans and programs. A background research effort between 2005 and 2017 reviewed more than 160 potential TCMs for the Metropolitan Atlanta region and divided the strategies into five categories: new vehicle standards, fleet turnover incentives, in-use vehicle controls, demand management, and transportation supply improvement measures. Five promising TCMs from this framework are identified for further analysis: More..
- Parking pricing in the morning peak period
- Doubling transit frequency doubling
- Cent/mile congestion pricing
- Implementing an increase in the gasoline tax
- Opting-in to California’s low emission vehicle (LEV) program
MOVES-Matrix and Distributed Computing For Region-Level Line Source Dispersion Analysis
Daejin Kim
This dissertation builds a framework for regional-level microscale pollutant dispersion analysis using MOVES-Matrix and distributed computing across multiple dispersion models (CALINE3, CALINE4, CAL3QHC, R-LINE, and AERMOD). The advanced framework for line source dispersion analysis results in huge savings in computing cost and time compared to traditional methods. However, due to the limited number of links allowed for individual model runs, line source dispersion analysis in regional-level is challenging. Preparing the extensive inputs for use in regional-level analysis across all models is also challenging (e.g., road geometry information, meteorology inputs, receptor locations, etc.). Therefore, advanced techniques to efficiently prepare the extensive input datasets are needed. This research addresses the variety of complexities across five dispersion models. Advanced techniques are implemented to efficiently prepare the extensive input datasets that are needed to undertake complex regional analyses. A case study for a large-scale transportation project (e.g., HOV to HOT conversion) is implemented to: 1) assess model performance, 2) and assess the relative environmental impacts defined by the tools for complex projects. More..
Integrating Car-following Models and Vehicle Specific Power Emission/Fuel Consumption
Hongyu Lu
Traffic simulation has been widely used for the evaluation of the traffic environmental impact, where the simulation model outputs are linked with energy/emission models. However, significant differences have been noted between field measurements of traffic operations and speed/acceleration predictions from car-following models which significantly affect energy consumption and emission predictions. Car-following models were originally developed from (and calibrated with) aggregate parameters, while fuel consumption and emissions models require instantaneous vehicle activity as inputs. In this research, widely used car-following models are re-assessed for use in emission/fuel consumption estimation, with their impact on vehicle specific power and instantaneous engine work as comparative indices. Second-by-second vehicle trajectories are used in these comparative analyses. Simulated VSP distributions and instantaneous engine work are compared with field distributions to verify these models. A new car-following model based on machine learning is proposed for more accurate estimation of emission/fuel consumption. More..
Mode Choice Behavior for Game Day Travel
Bingqing Liu
The new 71,000-seat Mercedes-Benz Stadium in Downtown Atlanta is home to Atlanta United FC and Atlanta Falcons football teams and hosts more than 20 major sporting events and concerts with attendance ranging from 40,000-70,000 fans. Fans attending these major events share the roadways with more than 120,000 downtown employees, 62,000 students, and 23,000 local residents. Downtown congestion before and after major stadium events has become a significant problem. To help reduce congestion and improve the stadium ingress and egress experience, Georgia Tech researchers are assessing stadium travel patterns (fan arrival and departure time, mode choice, ingress/egress routes, etc.). One goal of this research program is to assess how additional demand can be shifted to public transit. This thesis will use trajectory data from Commute Warrior, combined with traffic data, and stadium survey data, to develop a decision-tree based on the observed trip chains. The nested logit model will be based upon analysis of fans’ revealed preference behavior and the model will be used to assess potential methods designed to alleviate downtown game day congestion. More..
An Assessment of Pedestrian Infrastructure Quality and the Effect on Travel Time and Mobility for Users with Physical Limitations
Chelsea Dyess
Currently, the state of communities’ walking environments can be evaluated using tools that take into consideration proximity to amenities, block length, intersection density, and population density. However, a truly accessible pedestrian environment is characterized not only by sidewalk presence and proximity to goods and services, but also by well-maintained sidewalks, curb ramps, and curb cuts that help ensure the safety and comfort of pedestrians of all abilities. Sidewalk presence, coupled with sidewalk quality, are important factors when considering the ease of movement by users along the system. While individuals with full mobility are usually able to overcome problems in the pedestrian network, it is significantly more difficult for users with mobility impairments to traverse the same infrastructure. This thesis uses sidewalk, curb ramp, and curb cut quality data to assess the state of pedestrian infrastructure in Midtown, Atlanta. The assessment specifically focuses on how the state of the sidewalks in Midtown, Atlanta effect the movement of people with disabilities or mobility impairments. More..
Assessing the Feasibility of Autonomous Transit Vehicles as a First/Last Mile Public Transportation Solution
Daniel Walls
Using Atlanta’s MARTA rail system as a case study, this thesis will assess the feasibility of integrating autonomous transit vehicles (transit AVs) into the public transportation system as a first-mile and last-mile solution for riders. Numerous field-proven transit AVs are already on the market. The Navya Arma and Local Motors Olli are two such examples. These electric vehicles carry 8-15 people, operate at speeds up to 25 mph, and can run for 12-13 hours on a single charge. Their capabilities will only improve as technology advances. This thesis will examine a scenario in which a handful of transit AVs are based at each rail station and programmed to serve a 2-mile radius around the station. Riders within the service area would be able to summon the vehicles via a smartphone app. The AVs would pick-up and deliver passengers to or from the rail station, providing convenience and climate control but without the need for automobile ownership or on-site parking. During peak periods, the shuttles could pick-up multiple passengers, much like current private ridesharing services operate today. Such a system of transit AVs could significantly increase the catchment area and service population of rail infrastructure, improve mobility for transit-captive populations, and potentially increase transit ridership, increasing ROI for existing rail capital investments. The research will explore the economics of owning and operating AV shuttles to assess whether integrating AV service is compatible with MARTA’s business plan. This thesis will also assess travel time differences between the proposed AV service, and other commute alternatives. The primary objectives will be to determine 1) whether AV shuttles would be cost effective for MARTA, and 2) whether they would provide a time or productivity benefit for the public. More..
Sidewalk Asset Management – Investigation into the Financial Management of an Overlooked Transportation Asset
David Boyer
Americans walk less per day and are more likely to suffer from obesity than people from many other countries. By creating community environments that stimulate physical activity, such as walking, the prevalence of chronic illnesses and premature death may be reduced, and perhaps replaced with healthy aging and improved mental health. Pedestrian trips also help relieve vehicle congestion and promote local economic development. Proper management of sidewalks as assets preserves these essential connections for community members, but many cities are failing to meet the demand for repair and access. Sidewalks near residences, centers of employment, or schools may be in a state of disrepair, unsafe, or simply missing. Large backlogs of necessary sidewalk projects stymie decision-makers and rarely see an adequate influx of investment. Meanwhile, cities continue to grow and age, generating more opportunities for barriers to walking to develop when asset management practices are not keeping pace. More..
