Browsing by Author "Levin, Michael W."
Now showing 1 - 4 of 4
Results Per Page
Sort Options
Item Cost/Benefit Analysis of Fuel-Efficient Speed Control Using Signal Phasing and Timing (SPaT) Data: Evaluation for Future Connected Corridor Deployment(Minnesota Department of Transportation, 2023-03) Levin, Michael W.; Sun, Zongxuan; Wang, Shi’an; Sun, Wenbo; He, Suiyi; Suh, Bohoon; Zhao, Gaonan; Margolis, Jacob; Zamanpour, MaziarThe objective of this methodology is to refine the preliminary results from previous work (11% fuel savings for one vehicle, one intersection) to an entire corridor of SPaT signals, with different CV market penetration, and with driver awareness of fuel savings benefits. The research will proceed in three parts. First, several vehicles will be instrumented with DSRC receivers and GPS tracking to record SPaT data and the vehicle trajectories together. Offline, the project team will optimize the speed and powertrain control based on recorded SPaT data, using the recorded vehicle trajectories to identify the constraints of traffic flow. A living lab consisting of a GM car engine loaded by a transient hydrostatic dynamometer will be used to measure the fuel consumption with and without speed control. Second, the project team will conduct traffic flow simulations to study the impacts of higher market penetration on the overall fuel benefits, including the benefits to legacy vehicles which unintentionally use SPaT based speed controls by following CVs. Third, network models will be used to predict changes in route choices as drivers recognize the benefits of fuel savings in the route utility. The numerical predictions of fuel savings will be combined into cost/benefit analyses to inform MnDOT on the future deployment of SPaT on other corridors.Item Efficient Pedestrian and Bicycle Traffic Flow Estimation Combining Mobile-Sourced Data with Route Choice Prediction(2023-12-08) Barman, Simanta; Stern, Raphael; Levin, Michael W.; Lindsey, Greg; rstern@umn.edu; Stern, Raphael; University of Minnesota CAVe LabAccurate estimate of traffic flow measures like annual average daily traffic (AADT) is vital to making decisions about roadway planning, safety, maintenance, operation etc. Methodology to inexpensively obtain an accurate estimate of traffic flow especially for pedestrian and bicyclist traffic is lacking in the literature. High expenses of conducting household surveys and setting up traffic monitoring stations to collect data motivated us to look for cheaper solutions. In this study, we develop a methodology to inexpensively obtain a good estimate of pedestrian and bicyclist traffic flow from mobile data sources while avoiding the privacy issues associated with models based on household survey data. However, the accuracy of mobile data is unknown and may vary in different locations. To deal with erroneous data sources we use different techniques to estimate and keep improving an origin-destination (OD) matrix from the observed link flows to ultimately get the actual link flows. In our model, we enforce the consistency between the number of productions and attractions of trips for different regions with the OD-matrix. Using the network topology, we use trip distribution based on the gravity model to generate an initial OD-matrix. Then we use an optimization formulation to improve the initial OD-matrix so that the link flow obtained using the improved OD-matrix matches with the partially observable link flows. Furthermore, we present the performance of the solution algorithm for the Twin Cities' bicycle and pedestrian networks. We also compare the accuracy of our estimate with manually collected traffic flow data for the real networks.Item How does eco-routing affect total system emissions? City network predictions from user equilibrium models(2022) Cotta Antúnez, Rocío; Levin, Michael W.Transportation contributes a substantial fraction of all greenhouse gas emissions. One approach for reducing such emissions is to modify vehicles' route choices to minimize their fuel consumption or emission, which is known as eco-routing. Most eco-routing is based on vehicles choosing routes that minimize their individual fuel consumption or emissions. The Braess paradox demonstrates that when vehicles choose routes to minimize their individual goals, the aggregate effect may paradoxically result in the opposite net effect due to changes in congestion patterns. We construct a multiclass user equilibrium model in which some vehicles use eco-routing and others seek to minimize their individual travel times. Using this model, we show that the Braess paradox exists for eco-routing. If a large number of vehicles are trying to minimize their fuel consumption or emissions, the total fuel consumption or emissions may increase. We then solve the multiclass user equilibrium on publicly available city network data, and find that eco-routing results in increases in fuel consumption and emissions on some city networks as well.Item Towards Implementation of Max-Pressure Signal Timing on Minnesota Roads(Minnesota Department of Transportation, 2022-12) Barman, Simanta; Levin, Michael W.; Robbennolt, Jake; Hu, Jeffrey; Odell, Michael; Kang, DiMax-pressure control is a new adaptive method for signal timing that is mathematically proven to achieve maximum throughput for the entire city road network. This throughput guarantee is nevertheless achieved by a decentralized control algorithm that depends only on local traffic information and is easy to compute. These mathematical properties suggest high potential for use in Minnesota, but the method?s performance in practice is not well-known. Furthermore, it lacks some practical constraints on signal timing that could cause confusion to drivers. This project conducted methodological improvements and simulation experiments on a calibrated model of 7 intersections in Hennepin County. We modified the theory behind max-pressure control to model first-in-first-out behaviors on lanes shared by multiple turning movements, and to force max-pressure control to follow a signal cycle. After making these significant methodological improvements, we proved that the maximum throughput properties still hold. Then, we calibrated SUMO (Simulation of Urban MObility) microsimulation models of 2 Hennepin County corridors with 7 intersections using signal timing data and 15-minute observed counts, and compared different versions of max-pressure control with existing actuated-coordinated signals. We varied the maximum cycle length and the time step (signal phases can only change once per time step). The performance depended on the control parameters. Overall, for most intersections and demand periods, we were able to find max-pressure control settings that significantly improved over current signal timings. Large reductions in delay (sometimes over 50%) suggested that max-pressure signal timing both achieved higher throughput during peak demand and was more responsive to queues.