Browsing by Subject "Traffic congestion"

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The ABC Parking Ramps in Minneapolis: A Unique Past. A Visionary Future.
(Minnesota Department of Transportation, 2019-03) Douma, Frank; Cao, Jason; Corcoran, Heidi; Fan, Yingling; Lari, Adeel; Rohde, Barbara; Alarcon, Frank; Dame, Rachel; Karner, Kevin
In 1992 the ABC Ramps were completed in downtown Minneapolis as part of the I-394 construction project. The purpose of the ramps is to have programs that support efforts to reduce congestion and improve air quality by reducing SOV trips from the I-394 corridor. At the time the ramps were built, the ramp goals were aligned with the city of Minneapolis' parking system goals and the I-394 Corridor Management Plan. Since that time, however, the transportation modes, technologies, and plans surrounding the ramps have changed as well as the travel behaviors of the users. As the ramps reach the midpoint of their design life, this study examined the programs, policies, and goals developed for the ramps to ensure they continue to address current transportation challenges and align with regional stakeholder's goals and emerging trends, behaviors, and technology. The project culminated in a series of recommendations with implementation strategies for the ABC ramp management to improve its practice towards reducing congestion and improving air quality in downtown Minneapolis through innovative programming and marketing.
Access Across America: Auto 2015
(Center for Transportation Studies, University of Minnesota, 2016-09) Owen, Andrew; Murphy, Brendan; Levinson, David
Accessibility is the ease of reaching valued destinations. It can be measured across different times of day (accessibility in the morning rush might be lower than the less-congested midday period). It can be measured for each mode (accessibility by walking is usually lower than accessibility by transit, which is usually lower than accessibility by car). There are a variety of ways to measure accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This report focuses on accessibility to jobs by car. Jobs are the most significant nonhome destination, but it is also possible to measure accessibility to other types of destinations. The automobile remains the most widely used mode for commuting trips in the United States. This study estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes. The report presents detailed accessibility and congestion impact values for each metropolitan area as well as blocklevel maps that illustrate the spatial patterns of accessibility within each area. It also includes a census tract-level map that shows accessibility patterns at a national scale.
Access Across America: Auto 2017
(Center for Transportation Studies, University of Minnesota, 2018-10) Owen, Andrew; Murphy, Brendan
Accessibility is the ease of reaching valued destinations. It can be measured across different times of day (accessibility in the morning rush might be lower than the less-congested midday period). It can be measured for each mode (accessibility by walking is usually lower than accessibility by transit, which is usually lower than accessibility by car). There are a variety of ways to measure accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This study estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to-access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes. The report presents detailed accessibility and congestion impact values for each metropolitan area as well as block-level maps that illustrate the spatial patterns of accessibility within each area. It also includes a census tract-level map that shows accessibility patterns at a national scale.
Access Across America: Auto 2017 Methodology
(Center for Transportation Studies, University of Minnesota, 2018-10) Owen, Andrew; Murphy, Brendan
Accessibility is the ease of reaching valued destinations. It can be measured across different times of day (accessibility in the morning rush might be lower than the less-congested midday period). It can be measured for each mode (accessibility by walking is usually lower than accessibility by transit, which is usually lower than accessibility by car). There are a variety of ways to measure accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This report describes the data and methodology used in the Access Across America: Auto 2017 report, which estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes.
Access Across America: Auto 2018
(Center for Transportation Studies, University of Minnesota, 2020-03) Owen, Andrew; Murphy, Brendan
Accessibility is the ease and feasibility of reaching valued destinations. It can be measured for a wide array of transportation modes, to different types of destinations, and at different times of day. There are a variety of ways to define accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This study estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-toaccess jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes. This report presents detailed accessibility values for each metropolitan area, as well as block-level maps which illustrate the spatial patterns of accessibility within each area. A separate publication, Access Across America: Auto 2018 Methodology, describes the data and methodology used in this evaluation.
Access Across America: Auto 2018 Methodology
(Center for Transportation Studies, University of Minnesota, 2020-04) Owen, Andrew; Murphy, Brendan
Accessibility is the ease of reaching valued destinations. It can be measured across different times of day (accessibility in the morning rush might be lower than the less-congested midday period). It can be measured for each mode (accessibility by walking is usually lower than accessibility by transit, which is usually lower than accessibility by car). There are a variety of ways to measure accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This report describes the data and methodology used in the Access Across America: Auto 2018 report, which estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-toaccess jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes.
Access Across America: Auto 2019
(Center for Transportation Studies, University of Minnesota, 2021-02) Owen, Andrew; Murphy, Brendan
Accessibility is the ease and feasibility of reaching valued destinations. It can be measured for a wide array of transportation modes, to different types of destinations, and at different times of day. There are a variety of ways to define accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This study estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to-access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes. This report presents detailed accessibility values for each metropolitan area, as well as block-level maps which illustrate the spatial patterns of accessibility within each area. A separate publication, Access Across America: Auto 2019 Methodology, describes the data and methodology used in this evaluation.
Access Across America: Auto 2019 Methodology
(Center for Transportation Studies, University of Minnesota, 2021-02) Owen, Andrew; Murphy, Brendan
Accessibility is the ease of reaching valued destinations. It can be measured across different times of day (accessibility in the morning rush might be lower than the less-congested midday period). It can be measured for each mode (accessibility by walking is usually lower than accessibility by transit, which is usually lower than accessibility by car). There are a variety of ways to measure accessibility, but the number of destinations reachable within a given travel time is the most comprehensible and transparent as well as the most directly comparable across cities. This report describes the data and methodology used in the Access Across America: Auto 2019 report, which estimates the accessibility to jobs by auto for each of the 11 million U.S. census blocks and analyzes these data in the 50 largest (by population) metropolitan areas. Travel times are calculated using a detailed road network and speed data that reflect typical conditions for an 8 a.m. Wednesday morning departure. Additionally, the accessibility results for 8 a.m. are compared with accessibility results for 4 a.m. to estimate the impact of road and highway congestion on job accessibility. Rankings are determined by a weighted average of accessibility, with a higher weight given to closer, easier-to-access jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weights as travel time increases up to 60 minutes.
Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data
(Journal of Transport and Land Use, 2017) Zhang, Kaisheng; Sun, Daniel (Jian); Shen, Suwan; Zhu, Yi
With the development of in-vehicle data collection devices, GPS trajectory has become a priority source to identify traffic congestion and understand the operational states of road network in recent years. This study aims to investigate the relationship between traffic congestion and built environment, including traffic related factors and land use. Fuzzy C-means clustering was used to conduct an exhaustive study on 24-hour congestion pattern of road segments in urban area, so that the spatial autoregressive moving average model (SARMA) was introduced to analyze the output from the clustering analysis to establish the relationship between built environment and the 24-hour congestion pattern. The clustering result classified the road segments into four congestion levels, while the regression explained 12 traffic-related factors and land use factors’ impact on road congestion pattern. The continuous congestion was found to mainly occur in the city center, and the factors, such as road type, bus station in the vicinity, ramp nearby, commercial land use and so on have large impact on congestion formation. The Fuzzy C-means clustering was proposed to be combined with quantitative spatial regression, and the overall evaluation process will assist to assess the spatial-temporal levels of service of traffic from the congestion perspective.
Automatic street widening: Evidence from a highway dedication law
(Journal of Transport and Land Use, 2017) Manville, Michael
Cities often require developers to widen streets or make other transportation improvements to account for the traffic impacts of new building. This article examines one parcel-level traffic mitigation law in depth—the highway dedication ordinance of the city of Los Angeles. I first show that the law emerged from a combination of happenstance and political and fiscal constraints, not from persuasive evidence it would be effective. I then show that the traffic predictions underlying the law are often inaccurate, and that, in fact, the standards the law is based on are in some ways unverifiable. Thus the law likely does little to reduce congestion and probably impedes housing development. Finally, I argue that the law persists precisely because its desired outcome is hard to verify: Without measurable goals, planners fall back on a measurable process. Parcel-level traffic mitigation becomes an exercise not in reducing traffic but in ensuring that developers carry out mitigations, regardless of whether those mitigations are effective.
College and University Campuses in Greater Minnesota as Traffic Generators
(University of Minnesota Center for Transportation Studies, 2009-06) Vandrasek, Barbara J.; Adams, John S.
This report evaluates the significance of selected Minnesota college and university campuses located in regional centers outside the Minneapolis-St. Paul metropolitan commuter field with respect to the highway traffic that they generate. It examines campuses as places that generate motor vehicle traffic each day, and analyzes the absolute and relative significance of campuses in Greater Minnesota as traffic generators within the counties and wider commuting field in which they are situated. Expanding upon findings from two previous studies that investigated land development trends and increasing highway traffic for a sample of Minnesota’s 49 regional centers and their adjacent commuting fields, the report examines the volume of personnel moving to and from campuses each day, estimates traffic generation rates for different types of schools and their varying impact on traffic generation using trip generation factors supplied by the Institute of Transportation Engineers. It provides 27 campus-based cases, and discusses societal trends likely to affect schools as traffic generators, and concludes with speculations on the implications of these trends for transportation planning in Greater Minnesota. The geographical scale of analysis matters in assessing the relative impact of a school or campus as a traffic generator. If the impact if extremely local, it is likely to be a city responsibility. If the scale of analysis is the county, both city streets and county roads experience traffic impacts. At the scale of the entire commuting field, state highways may be affected. In this analysis, counties were used as the most appropriate spatial unit of analysis.
Development of the Next Generation Stratified Ramp Metering Algorithm Based on Freeway Density
(Center for Transportation Studies, 2011-03) Geroliminis, Nikolas; Srivastava, Anupam; Michalopoulos, Panos
A new coordinated, traffic-responsive ramp metering algorithm has been designed for Minnesota’s freeways based on density measurements, rather than flows. This is motivated in view of recent research indicating that the critical value of density at which capacity is observed is less sensitive and more stable than the value of capacity, thereby resulting in m ore effective control. Firstly, we develop a methodology to estimate densities with space and time based on data from loop detectors. The methodology is based on solving a flow conservation differential equation (using LWR theory) with intermediate (internal) freeway mainline boundaries, which is fast er and more accurate from previous resear ch using only external boundaries. To capture the capacity drop phenomenon into the first-order model we utilize a fundamental diagram with two values of capacity and we provide a memory-based methodology to choose the appropriate value in the numerical solution of the problem. Secondly, with respect to ramp metering, the main goals of the algorithm are to delay the onset of the breakdown and to accelerate system recovery when ramp metering is unable due to the violation of maximum allowable ramp waiting time. The effectiveness of the new control strategy is being assessed by comparison with the currently deployed version of the Stratified Zone Algorithm (SZM) through microscopic simulation of a real 12-mile, 17 ramp freeway section. Simulations show a decrease in the delays of mainline and ramp traffic, an improvement 8% in the overall delays and avoidance of the maximum ramp delay violations.
Evaluation of the Effect of MnPASS Lane Design on Mobility and Safety
(Minnesota Department of Transportation, 2014-06) Stanitsas, Panagiotis; Hourdos, John; Zitzow, Stephen
Dynamically priced High Occupancy Toll (HOT) lanes have been recently added to the traffic operations arsenal in an attempt to preserve infrastructure investment in the future by maintaining a control on demand. This study focuses on the operational and design features of HOT lanes. HOT lanes’ mobility and safety are contingent on the design of zones (“gates”) that drivers use to merge in or out of the facility. Existing methodologies for the design of access zones are limited to engineering judgment or studies that take into consideration undersized amount of observations. Case in point is the fact that the design philosophes between the two HOT facilities in Minnesota are diametrically opposed. Specifically, the I-394 freeway, the first dynamically priced HOT lane, was designed with a closed access philosophy, meaning that for the greater length of the roadway access to the HOT lane is restricted with only specific short-length sections where access is allowed. In contrast I-35W, the second HOT corridor, was designed with an open access philosophy where lane changes between the HOT and the GPLs are allowed everywhere except for a few specific locations. This contradiction generated questions as to effect each case has on safety and mobility. This study presents an assessment of safety and mobility on the two facilities as they operate today and highlights the issues present on either design. In addition, two design tools were developed, the first assisting in the optimal design of access zones based on traffic measurements, and the second allowing the assessment of the influence congested General Purpose Lanes can have on the mobility and safety of the HOT under different traffic conditions and utilization due to changes in pricing strategy.
Measure of Truck Delay and Reliability at the Corridor Level
(Minnesota Department of Transportation, 2018-04) Liao, Chen-Fu
Freight transportation provides a significant contribution to our nation’s economy. A reliable and accessible freight network enables business in the Twin Cities to be more competitive in the Upper Midwest region. Accurate and reliable freight data on freight activity is essential for freight planning, forecasting and decision making on infrastructure investment. A report entitled “Twin Cities Metropolitan Region Freight Study” published by MnDOT and the Metropolitan Council in 2013, suggested a need to understand where and when trucks are most affected by congestion. A framework for truck data collection and analysis was recommended to better understand the relationships between truck traffic and congestion in rush hours. Building upon our previous study to measure freight mobility and reliability along 38 key freight corridors in the Twin Cities Metropolitan Area (TCMA), this study leveraged our previous effort to implement the performance measures using the National Performance Measurement Research Dataset (NPMRDS) from the USDOT. The researcher team first worked with stakeholders to prioritize a list of key freight corridors with recurring congestion in peak periods in the TCMA. We used 24 months of NPMRDS data to measure travel time reliability and estimate truck delay at the corridor level and to identify system impediments during the peak hours. The objective is to use performance measures for assessing impact of truck congestions and identifying operational bottlenecks or physical constraints. Trucking activity nearby a congested area is examined to analyze traffic pattern and investigate possible causes of recurring congestions.
A model of the rise and fall of roads
(Journal of Transport and Land Use, 2017) Zhang, Lei; Levinson, David
This paper analyzes the relationship between network supply and travel demand and describes a road development and degeneration mechanism microscopically at the link (road-segment) level. A simulation model of transportation network dynamics is developed, involving iterative evolution of travel demand patterns, network revenue policies, cost estimation, and investment rules. The model is applied to a real-world congesting network for Minneapolis-St. Paul, Minnesota (Twin Cities), which comprises nearly 8,000 nodes and more than 20,000 links, using network data collected since 1978. Four experiments are carried out with different initial conditions and constraints, the results of which allow us to explore model properties such as computational feasibility, qualitative implications, potential calibration procedures, and predictive value. The hypothesis that road hierarchy is an emergent property of transportation networks is corroborated and the underlying reasons discovered. Spatial distribution of capacity, traffic flow, and congestion in the transportation network is tracked over time. Potential improvements to the model, in particular, and future research directions in transportation network dynamics, in general, are also discussed.
Real-Time Prediction of Freeway Occupancy for Congestion Control
(Center for Transportation Studies, University of Minnesota, 1997-09) Cherkassky, Vladimir; Yi, Sangkug
Accurate traffic prediction is critical for effective control of on-ramp traffic (ramp metering). During congestion, traffic shock waves propagate back and forth between the detectors, and traffic becomes inherently non-stationary and difficult to predict. Recently, several adaptive non-linear time series prediction methods have been developed in statistics and in artificial neural networks. We applied these methods to develop real-time prediction of freeway occupancy during congestion periods, from current and time-lagged observations of occupancy at several (neighboring) detector stations. This study used the following function estimation methodologies for real-time occupancy prediction: two statistical techniques, multivariate adaptive regression splines (MARS) and projection pursuit regression; two neural network methods, multi-layer perceptrons (MLP) and constrained topological mapping (CTM). All these methods were applied to freeway occupancy data collected on I-35W during morning rush hours. Data collected on one day was used for training (model estimation), whereas the data collected on a different day was used for testing, i.e., estimating the quality of prediction (generalization). Results for this study indicate that the proposed methodology provides 10-15% more accurate prediction of traffic during congestion periods than the approach currently used by Minnesota DOT.
Using Archived Truck GPS Data for Freight Performance Analysis on I-94/I-90 from the Twin Cities to Chicago
(University of Minnesota Center for Transportation Studies, 2009-11) Liao, Chen-Fu
Interstate 94 is a key freight corridor for goods transportation between Minneapolis and Chicago. This project proposes to utilize the FPM data and information from ATRI to study the I-94/I-90 freight corridor. Freight performance will be evaluated and analyzed to compare truck travel time with respect to duration, reliability, and seasonal variation. This data analysis process can be used for freight transportation planning and decision-making and potentially will be scalable for nationwide deployment and implementation on the country’s significant freight corridors.

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