Dr. David M. Levinson

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Access Across America: Transit 2016 Data
(2018-03-28) Owen, Andrew; Murphy, Brendan; aowen@umn.edu; Owen, Andrew; University of Minnesota Center for Transportation Studies, Accessibility Observatory
These data were created as part of a study that examined the accessibility to jobs by transit in 49 of the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study; Access Across America: Transit 2015 data are available at https://conservancy.umn.edu/handle/11299/183801. Access Across America: Transit 2014 data are available at http://hdl.handle.net/11299/168064.
Access Across America: Transit 2016
(Center for Transportation Studies, University of Minnesota, 2017-11) Owen, Andrew; Murphy, Brendan; Levinson, David M.
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 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 transit and walking for each of the United States’ 11 million census blocks, and analyzes these data in 49 of the 50 largest (by population) metropolitan areas. Transit is used for an estimated 5 percent of commuting trips in the United States, making it the second most widely used commute mode after driving. Travel times by transit are calculated using detailed pedestrian networks and full transit schedules for the 7:00 – 9:00 a.m. period. The calculations include all components of a transit journey, including “last-mile” access and egress walking segments and transfers, and account for minute-by-minute variations in service frequency. This report presents detailed accessibility values for each metropolitan area, as well as block-level maps that illustrate the spatial patterns of accessibility within each area. A separate publication, Access Across America: Transit 2016 Methodology, describes the data and methodology used in this evaluation.
Justice, Exclusion, and Equity: An Analysis of 48 U.S. Metropolitan Areas
(2017) Palmateer, Chelsey; Levinson, David M
Injustice in transportation services experienced by disadvantaged demographic groups account for much of these groups’ social exclusion. Unfortunately, there is little agreement in the field about what theoretical foundation should be the basis of measures of the justice of transportation services, limiting the ability of transportation professionals to remedy the issues. Accordingly, there is a need for an improved measure of the justice of the distribution of transportation services, which relates to the effectiveness of transportation services for all members of disadvantaged groups rather than for only segregated members of these disadvantaged groups. To this end potential measures of distributive justice, based on the accessibility to jobs provided by various modes, are evaluated in 48 of the top 50 largest metropolitan areas in the United States. The purpose of the study is to inform recommendations for appropriate use of each measure.
The Healthiest vs. Greenest Path: Comparing the Effects of Internal and External Costs of Motor Vehicle Pollution on Route Choice
(2017) Cui, Mengying
On-road emissions, a dominant source of urban air pollution, damage human health. The 'healthiest path' and the 'greenest path' are proposed as alternative patterns of traffic route assignment to minimize the costs of pollution exposure and emission, respectively. As a proof-of-concept, the framework of a link-based emission cost analysis is built for both internal and external environmental costs and is applied to the road network in the Minneapolis - St. Paul Metropolitan Area based on the EPA MOVES and RLINE models. The healthiest and the greenest paths are skimmed for all work-trip origin-destination pairs and then aggregated into work trip flows to identify the healthier or greener roads in a comparative statics analysis. The estimates show that highways have higher emission concentrations due to higher traffic flow, on which, but that the internal and external emission costs are lower. The emission cost that commuters impose on others greatly exceeds that which they bear. In addition, the greenest path is largely consistent with the traditional shortest path which implies that highways tend to be both greener and shorter (in travel time) for commuters than surface streets. Use of the healthiest path would generate more detours, and higher travel times.
Accessibility-oriented development
(2017) Deboosere, Robbin; Levinson, David M; El-Geneidy, Ahmed
Municipal governments worldwide have been pursuing transit-oriented development (TOD) strategies in order to increase transit ridership, curb traffic congestion, and rejuvenate urban neighborhoods. In many cities, however, development of planned sites around transit stations has been close to non-existent, due to, among other reasons, a lack of coordination between transit investments and land use at the regional scale. Furthermore, the ability to access transit differs from the ability to access destinations that people care about. Reframing transit-oriented development as accessibility-oriented development (AOD) can aid the process of creating functional connections between neighborhoods and the rest of the region, and maximize benefits from transport investments. AOD is a strategy that balances accessibility to employment and the labor force in order to foster an environment conducive to development. AOD areas are thus defined as having higher than average accessibility to employment opportunities and/or the labor force; such accessibility levels are expected to increase the quality of life of residents living in these areas by reducing their commute time and encouraging faster economic development. To quantify the benefits of AOD, accessibility to employment and the labor force are calculated in the Greater Toronto and Hamilton Area, Canada in 2001 and 2011. Cross-sectional and temporal regressions are then performed to predict average commute times and development occurring in AOD areas and across the region. Results show that AOD neighborhoods with high accessibility to jobs and low accessibility to the labor force have the lowest commute times in the region, while the relationship also holds for changes in average commute time between the studied time periods. In addition, both accessibility to jobs and accessibility to the labor force are associated with changes in development, as areas with high accessibility to jobs and the labor force attract more development. In order to realize the full benefits of planned transit investments, planning professionals and policy makers alike should therefore leverage accessibility as a tool to direct development in their cities, and concentrate on developing neighbourhoods with an AOD approach in mind.
Traffic Flow Variation and Network Structure
(2017) Ermagun, Alireza; Levinson, David M.
This study defines and detects competitive and complementary links in a complex network and constructs theories illustrating how the variation of traffic flow is interconnected with network structure. To test the hypotheses, we extract a grid-like sub-network containing 140 traffic links from the Minneapolis - St. Paul highway system. We reveal a real-world traffic network comprises both competitive and complementary links, and there is a negative network dependency between a competitive link pair and a positive network dependency between a complementary link pair. We validate a robust linear relationship between standard deviation of flow in a link and its number of competitive links, its link correlation with competitive links, and its network dependency with both competitive and complementary links. The results indicate the number of competitive links in a traffic network is negatively correlated with the variation of traffic flow in congested regimes as drivers are able to take alternative paths. The results also signify that the more the traffic flow of a link is correlated to the traffic flow of its competitive links, the more the flow variation is in the link. Considering the network dependency, however, it is corroborated that the more the network dependency between a link and its competitive links, the more the flow variation in the link. This is also true for complementary links.
Spatiotemporal Short-term Traffic Forecasting using the Network Weight Matrix and Systematic Detrending
(2017-08) Ermagun, Alireza; Levinson, David M
This study examines the dependency between traffic links using a three-dimensional data detrend- ing algorithm to build a network weight matrix in a real-world example. The network weight matrix reveals how links are spatially dependent in a complex network and detects the competi- tive and complementary nature of traffic links. We model the traffic flow of 140 traffic links in a sub-network of the Minneapolis - St. Paul highway system for both rush hour and non-rush hour time intervals, and validate the extracted network weight matrix. The results of the modeling indi- cate: (1) the spatial weight matrix is unstable over time-of-day, while the network weight matrix is robust in all cases and (2) the performance of the network weight matrix in non-rush hour traffic regimes is significantly better than rush hour traffic regimes. The results of the validation show the network weight matrix outperforms the traditional way of capturing spatial dependency between traffic links. Averaging over all traffic links and time, this superiority is about 13.2% in rush hour and 15.3% in non-rush hour, when only the 1st -order neighboring links are embedded in modeling. Aside from the superiority in forecasting, a remarkable capability of the network weight matrix is its stability and robustness over time, which is not observed in spatial weight matrix. In addition, this study proposes a naïve two-step algorithm to search and identify the best look-back time win- dow for upstream links. We indicate the best look-back time window depends on the travel time between two study detectors, and it varies by time-of-day and traffic link.
Safety in Numbers and Safety in Congestion for Bicyclists and Motorists at Urban Intersections
(2017) Carlson, Kristin; Ermagun, Alireza; Murphy, Brendan; Owen, Andrew; Levinson, David M.
This study assesses the estimated crashes per bicyclist and per vehicle as a function of bicyclist and vehicle traffic, and tests whether greater traffic reduces the per-car crash rate. We present a framework for comprehensive bicyclist risk assessment modeling, using estimated bicyclist flow per intersection, observed vehicle flow, and crash records. Using a two-part model of crashes, we reveal that both the annual average daily traffic and daily bicyclist traffic have a diminishing return to scale in crashes. This accentuates the positive role of safety in numbers. Increasing the number of vehicles and cyclists decelerates not only the probability of crashes, but the number of crashes as well. Measuring the elasticity of the variables, it is found that a 1% increase in the annual average daily motor vehicle traffic increases the probability of crashes by 0.14% and the number of crashes by 0.80%. However, a 1% increase in the average daily bicyclist traffic increases the probability of crashes by 0.09% and the number of crashes by 0.50%. The saturation point of the safety in numbers for bicyclists is notably less than for motor vehicles. Extracting the vertex point of the parabola functions examines that the number of crashes starts decreasing when daily vehicle and bicyclist traffic per intersection exceed 29,568 and 1,532, respectively.
Review of 'Forecasting Urban Travel: Past, Present and Future,' by David Boyce and Huw Williams
(Wiley, 2016-06) Levinson, David M
Unexpected versus expected network disruption: Effects on travel behavior
(Elsevier, 2017-02) Danczyk, Adam; Di, Xuan; Liu, Henry X; Levinson, David M
This paper discusses the observed evolution of traffic in the Minneapolis-St Paul (Twin Cities) region road network following the unexpected collapse of the I-35W Bridge over the Mississippi River. The observations presented within this paper reveal that traffic dynamics are potentially different when a prolonged and unexpected network disruption occurs rather than a preplanned closure. Following the disruption from the I-35W Bridge's unexpected collapse, we witnessed a unique trend: an avoidance phenomenon after the disruption. More specifically, drivers are observed to drastically avoid areas near the disruption site, but gradually return after a period of time following the collapse. This trend is not observed in preplanned closures studied to date. To model avoidance, it is proposed that the tragedy generated a perceived travel cost that discouraged commuters from using these sections. These perceived costs are estimated for the Twin Cities network and found to be best described as an exponential decay cost curve with respect to time. After reinstituting this calibrated cost curve into a mesoscopic simulator, the simulated traffic into the discouraged areas are found to be within acceptable limits of the observed traffic on a week-by-week basis. The proposed model is applicable to both practitioners and researchers in many traffic-related fields by providing an understanding of how traffic dynamics will evolve after a long-term, unexpected network disruption.
Access Across America: Transit 2015 Data
(2017-02-02) Owen, Andrew; Levinson, David M; Murphy, Brendan; aowen@umn.edu; Owen, Andrew
These data were created as part of a study that examined the accessibility to jobs by transit in 49 of the 50 largest (by population) metropolitan areas in the United States. It is the most detailed evaluation to date of access to jobs by transit, and it allows for a direct comparison of the transit accessibility performance of America's largest metropolitan areas. These data are part of a longitudinal study; Access Across America: Transit 2014 data are available at http://hdl.handle.net/11299/168064.
Access Across America: Transit 2015
(Center for Transportation Studies, University of Minnesota, 2016-12) Owen, Andrew; Murphy, Brendan; Levinson, David M.
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 examines accessibility to jobs by transit in 49 of the 50 largest (by population) metropolitan areas in the United States. Transit is used for an estimated 5 percent of commuting trips in the United States, making it the second most widely used commute mode after driving. This report complements Access Across America: Auto 2015, a report of job accessibility by auto in 50 metropolitan areas and follows the Access Across America: Transit 2014 report. A separate publication, Access Across America: Transit 2015 Methodology, describes the data and methodology used in this evaluation. Rankings are determined by a weighted average of accessibility, giving a higher weight to closer jobs. Jobs reachable within ten minutes are weighted most heavily, and jobs are given decreasing weight as travel time increases up to 60 minutes.
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.
Workshop 3 report: Sustainable funding sources and related cost benefit measurements
(2016) Stanley, John; Levinson, David M
Recognising that public transport services generally deliver substantial benefits for society but frequently require operating and capital funding support, this Workshop sought to find ways to bridge this benefit/funding gap, particularly through benefit monetization. It elaborated a wide range of benefits from public transport services, to both users and non-users. In regard to non-users, there was a particular focus on the role of public transport in promoting positive external benefits, such as agglomeration economies, and reducing the negative external costs of car use. A number of ways in which the service funding requirement might be reduced by improved system management were considered, such as better fare evasion practices and more effective public private partnerships. A range of funding opportunities was then reviewed, from which two preferred bundles were developed. Value capture was seen as a vital funding opportunity, both for supporting operating funding and capital funding requirements. Funding circumstances that were seen as more properly a governmental responsibility were identified.
Population exposure to ultrafine particles: size-resolved and real-time models for highways
(2016-09-14) Zhu, Shanjiang; Marshall, Julian D; Levinson, David M
Prior research on ultrafine particles (UFP) emphasizes that concentrations are especially high on-highway, and that time on highways contribute disproportionately to total daily exposures. This study estimates individual and population exposure to ultra-fine particles in the Minneapolis – St. Paul (Twin Cities) metropolitan area, Minnesota. Our approach combines a real-time model of on-highway size-resolved UFP concentrations (32 bins, 5.5 to 600 nm); individual travel patterns, derived from GPS travel trajectories collected in 144 individual vehicles (123 hours at locations with UFP estimates among 624 vehicle-hours of travel); and, loop-detector data, indicating real- time traffic conditions throughout the study area. The results provide size-resolved spatial and temporal patterns of exposure to UFP among freeway users. On-highway exposures demonstrate significant variability among users, with highest concentrations during commuting peaks and near highway interchanges. Findings from this paper could inform future epidemiological studies in on- road exposure to UFP by linking personal exposures to traffic conditions.
A random walk down Main Street
(2016-08) Levinson, David M
US suburbs have often been characterized by their relatively low walk accessibility compared to more urban environments, and US urban environments have been characterized by low walk accessibility compared to cities in other countries. Lower overall density in the suburbs implies that activities, if spread out, would have a greater distance between them. But why should activities be spread out instead of developed contiguously? This brief research note builds a positive model for the emergence of contiguous development along “Main Street” to illustrate the trade-offs that result in the built environment we observe. It then suggests some policy interventions to place a “thumb on the scale” to choose which parcels will develop in which sequence to achieve socially preferred outcomes.
Intra-household Bargaining for School Trip Accompaniment of Children: A Group Decision Approach
(2016-08-01) Ermagun, Alireza; Levinson, David M
This paper tests a group decision-making model to examine the school travel behavior of students 6-18 years old in the Minneapolis-St. Paul Metropolitan area. The school trip information of 1,737 two-parent families with a student is extracted from Travel Behavior Inventory data collected by the Metropolitan Council between the Fall 2010 and Spring 2012. The proposed model has four distinct characteristics including: (1) considering the student explicitly in the model, (2) allowing for bargaining or negotiation within households, (3) quantifying the intra-household interaction among family members, and (4) determining the decision weight function for household members. This framework also covers a household with three members, namely, a father, a mother, and a student, and unlike other studies it is not limited to dual-worker families. To test the hypotheses we developed two models, each with and without the group-decision approach. The models are separately developed for different age groups, namely students 6-12 and 12-18 years old. This study considered a wide range of variables such as work status of parents, age and gender of students, mode of travel, and distance to school. The findings of this study demonstrate that the elasticities of the two modeling approaches differ not only in the value, but in the sign in some cases. In 63 percent of the cases the unitary household model underestimates the results. More precisely, the elasticities of the unitary household model are as large as 2 times more than that of the group-decision model in 20 percent of cases. This is a direct consequence of model misspecification that misleads both long- and short-term policies where the intra-household bargaining and interaction is overlooked in travel behavior models.
Does poor road condition increase crashes?
(2016-08-01) Yokoo, Toshihiro; Levinson, David M; Marasteanu, Mihai
In a region well known for its severe weather, maintaining pavements to meet high standards remains a challenge. Changes in weather states (such as the freeze-thaw cycle) leads to distresses in the pavement materials. There exist claims that poor pavement quality reduces the ability of roads to drain and reduces the ability of vehicles to resist skidding, and is thus associated with more crashes. In order to improve road safety, several pavement maintenance treatments are carried out, such as “rout and seal cracks” and “hot-mix patching” for improving pavement roughness and distress (Tighe et al., 2000). Others have found that crash rate depends on the pavement type and pavement condition. Crash rate of tined pavement sites is larger than the rate of ground pavement sites. When the pavement condition is wet or icy, crashes are more likely than under dry conditions (Drakopoulos et al., 1998). , When the pavement condition is poor, severe crashes are more likely, but when the pavement condition is very poor, severe crashes are less likely to occur than poor pavement conditions (Li et al., 2013). In accident rate estimation models, the results indicate that most important independent variable is “AADT”, and “geometric design” (lane width and access control) and “pavement condition” (friction, serviceability index, and pavement type) are also important variables (Karlaftis and Golias, 2002). Our research proposes to statistically test such claims of a relationship between incident number and road quality, while controlling for traffic data (AADT and percent truck), segment length, crash conditions (date, road characteristics, and road surface), and pavement type. To investigate the relationship, we combine data from various sources. We then conduct a statistical analysis for ascertaining the effects of good road quality on incident number and severity. This paper de- scribes the data, methods, hypotheses, and results in turn.
Cross-Elasticities in Frequencies and Ridership for Urban Local Routes
(2016-08-01) Totten, Joseph C; Levinson, David M
Observational data from the Minneapolis-Saint Paul region’s Metro Transit, are analyzed to determine the effects of service levels on ridership levels at different intervals. This research is innovative because it compares changes in service levels and ridership in several service intervals, and includes the elasticities and cross elasticities, or the influence that these service levels have on different service intervals’ ridership. These cross-elasticities are not known to have been researched previously, and are found to have little effect during the week; however, weekend ridership was found to be influenced by rush hour and overnight frequencies. Future research should replicate this study in other cities, and should use express and suburban routes.
The Safest Path: Analyzing the Effects of Crash Costs on Route Choice and Accessibility
(2016-08-01) Cui, Mengying; Levinson, David M
The "safest path" is proposed to optimize the on-road safety of individuals and minimize the cost of crashes. In this study, the framework of a link-based crash cost analysis is built and applied to assess the crash cost of each link segment on the road network of the Minneapolis - St. Paul area based on Safety Performance Functions from the perspective of travelers. The safest path is then found for all OD pairs to compare flow patterns and accessibility distributions with those based on the traditional shortest travel time path. While, the safest path does not coincide with the shortest path, the accessibility distributions have similar patterns.