Browsing by Author "Zhu, Shanjiang"

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Access to Destinations: Monitoring Land Use Activity Changes in the Twin Cities Metropolitan Region
(Minnesota Department of Transportation, 2008-07) Iacono, Michael; Levinson, David; El-Geneidy, Ahmed; Wasfi, Rania; Zhu, Shanjiang
This study presents an effort to track and model land use change in the Twin Cities Metropolitan Region. To that end, we make use of a unique, high-resolution, cell-level set of land use data for the Twin Cities. The data represent 75 meter by 75 meter land use cells, observed at several points in time during the period from 1958 to 2005. These data are used to validate three different types of land use models, which then are used to forecast land use several decades into the future. The models applied in this study include Markov Chain models, Markov Chain-Cellular Automata (MC-CA) models, and an empirical model based on a logistic regression specification. The models are intended to have a simple, transparent structure that allows the user to identify sources of forecast error. Forecasts of land use are made both for the entire study area and also for a specific corridor along State Highway 610 in the northwestern suburbs of the Twin Cities. The study concludes with a brief discussion of the limitations of the models, and how they might meaningfully be expanded and applied.
Agent-Based Model of Price Competition and Product Differentiation on Congested Networks.
(University of Bath, 2008) Zhang, Lei; Levinson, David M; Zhu, Shanjiang
Using consistent agent-based techniques, this research models the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Representations of road authorities making pricing and capacity decisions. Different from small-network equilibrium models in prior literature, this agent-based model is applicable to pricing and investment analyses on large complex networks. The subsequent economic analysis focuses on the source, evolution, measurement, and impact of product differentiation with heterogeneous users on a mixed ownership network (with tolled and untolled roads). Two types of product differentiation in the presence of toll roads, path differentiation and space differentiation, are defined and measured for a base case and several variants with different types of price and capacity competition and with various degrees of user heterogeneity. The findings favor a fixed-rate road pricing policy compared to complete pricing freedom on toll roads. It is also shown that the relationship between net social benefit and user heterogeneity is not monotonic on a complex network with toll roads.
An Agent-based Route Choice Model
(2007) Zhu, Shanjiang; Levinson, David M; Zhang, Lei
Travel demand emerges from individual decisions. These decisions, depending on individual objectives, preferences, experiences and spatial knowledge about travel, are both heterogeneous and evolutionary. Research emerging from fields such as road pricing and ATIS requires travel demand models that are able to consider travelers with distinct attributes (value of time (VOT), willingness to pay, travel budgets, etc.) and behavioral preferences (e.g. willingness to switch routes with potential savings) in a differentiated market (by tolls and the level of service). Traditional trip-based models have difficulty in dealing with the aforementioned heterogeneity and issues such as equity. Moreover, the role of spatial information, which has significant influence on decision-making and travel behavior, has not been fully addressed in existing models. To bridge the gap, this paper proposes to explicitly model the formation and spread- ing of spatial knowledge among travelers. An Agent-based Route Choice (ARC) model was developed to track choices of each decision-maker on a road network over time and map individual choices into macroscopic flow pattern. ARC has been applied on both SiouxFalls network and Chicago sketch network. Comparison between ARC and existing models (UE and SUE) on both networks shows ARC is valid and computationally tractable. To be brief, this paper specifically focuses on the route choice behavior, while the proposed model can be extended to other modules of travel demand under an integrated framework.
The Co-Evolution of Land Use and Road Networks
(Emerald Group, 2007) Levinson, David M; Xie, Feng; Zhu, Shanjiang
Disruptions to Transportation Networks: A Review
(Springer, 2011) Zhu, Shanjiang; Levinson, David M
Travel decisions may be very stable in a familiar environment. Major network disruptions such as the I-35W bridge collapse disrupt habitual behavior. Such "natural" experiments provide unique opportunities for behavioral studies, but the time window for such studies is limited. A well-developed methodology is crucial for both data collection and analysis, and thus the soundness of behavioral models , especially in such a limited time window. Therefore, this paper reviews both theoretical and empirical studies on traffic and behavioral impacts of network disruptions. Findings from this paper offers prospective ideas about capturing the impacts of network disruption.
Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle
(PLoS One, 2015) Zhu, Shanjiang; Levinson, David M
Most recent route choice models, following either Random Utility Maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. Such study could also help practitioners and researchers evaluate widely applied shortest path assumptions. This study aims at bridging the gap by evaluating morning commute routes followed by residents at the Twin Cities, Minnesota. Accurate GPS and GIS data were employed to reveal routes people utilized. Findings from this study could also provide guidance for future efforts in building better travel demand models.
An economic model for vehicle ownership quota and usage restriction policy analysis.
(2012-03) Zhu, Shanjiang
Rationing policies, including vehicle ownership quota and vehicle usage restrictions, have been implemented in several megaregions to address congestion and other negative transportation externalities. However, no model is available in the literature that allows direct comparison of these rationing policies. To bridge this gap, this study develops an analytical framework for analyzing and comparing transportation rationing policies, which consists of a mathematical model of joint household vehicle ownership and usage decisions and welfare analysis methods based on compensating variation and consumer surplus. Under the assumptions of homogenous users and single time period, this study finds that vehicle usage rationing performs better when relatively small percentages of users (i.e. low rationing ratio) are rationed off the roads and when induced demand resulting from congestion mitigation is low. When the amount of induced demand exceeds a certain level, it is shown analytically that vehicle usage restrictions will always cause welfare losses. When the policy goal is to reduce vehicle travel by a large portion (i.e. high rationing ratio), the net social benefits of vehicle ownership quota rationing policy become more obvious. The optimal rationing ratios for both rationing policies can be determined by the model, and are influenced by network congestion and congestibility. A comparison with pricing policy is also provided to illustrate their difference under various conditions. Various policy implications, as well as future research directions, are also discussed.
Enhancing Transportation Education through On-line Simulation using an Agent-Based Demand and Assignment Model
(American Society of Civil Engineers, 2011) Zhu, Shanjiang; Xie, Feng; Levinson, David M
This research explores the effectiveness of using simulation as a tool for enhancing classroom learning in the Civil Engineering Department of the University of Minnesota at Twin Cities. The authors developed a modern transportation planning software package, Agent-based Demand and Assignment Model (ADAM), that is consistent with our present understanding of travel behavior, that is platform independent, and that is easy to learn and is thus usable by students. An in-class project incorporated ADAM and the performance of this education strategy was evaluated through pre-class survey, post-class survey, scores in the quiz focusing on travel demand modeling and final scores. Results showed that ADAM effectively enhanced students' self-reported understanding of transportation planning and their skills of forming opinions, evaluating projects and making judgments. Students of some learning styles were found to benefit more than others through simulation-based teaching strategy. Findings in this research could have significant implications for future practice of simulation-based teaching strategy.
Indifference Bands for Route Switching
(2016) Di, Xuan; Liu, Henry; Zhu, Shanjiang; Levinson, David M
The replacement I-35W bridge in Minneapolis saw less traffic than the original bridge though it provided substantial travel time saving for many travelers. This observation cannot be explained by the classical route choice assumption that travelers always take the shortest path. Accordingly, a boundedly rational route switching model is proposed assuming that travelers will not switch to the new bridge unless travel time saving goes beyond a threshold or indifference band. To validate the boundedly rational route switching assumption, route choices of 78 subjects from a GPS travel behavior study were analyzed before and after the addition of the new I-35W bridge. Indifference bands are estimated for both commuters who were previously bridge users and those who never had the experience of using the old bridge. This study offers the first empirical estimation of bounded rationality parameters from GPS data and provides guidelines for traffic assignment.
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 Portfolio Theory of Route Choice.
(Elsevier, 2013) Zhu, Shanjiang; Levinson, David M
Although many individual route choice models have been proposed to incorporate travel time variability as a decision factor, they are typically still deterministic in the sense that the optimal strategy requires choosing one particular route that maximizes utility. In contrast, this study introduces an individual route choice model where choosing a portfolio of routes instead of a single route is the best strategy for a rational traveler who cares about both journey time and lateness when facing stochastic network conditions. The model is then tested with GPS data collected in metropolitan Minneapolis-St. Paul, Minnesota. Our data suggest strong correlation among link speed when analyzing morning commute trips. There is no single dominant route (defined here as a route with the shortest travel time for a 15 day period) in 18% of cases when links travel times are correlated. This paper demonstrates that choosing a portfolio of routes could be the rational choice of a traveler who wants to optimize route decisions under variability.
The roads taken: theory and evidence on route choice in the wake of the I-35W Mississippi River bridge collapse and reconstruction.
(2010-09) Zhu, Shanjiang
Route choice analysis investigates the path travelers follow to implement their travel plan. It is the most frequent, and thus arguably the most important decision travelers make on a daily basis. Long established efforts have been dedicated to a normative model of the route choice decision, while investigations of route choice from a descriptive perspective have been limited. Wardrop's first principle, or the shortest path assumption, is still widely used in route choice models. Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. Moreover, factors beyond travel time, such as preferences for travel time reliability, inertia in changing routes, and travel experience that could also have significant impacts on route choice, have not been fully explored and incorporated in route choice modeling. The phenomenon that people use more than one route between the same origin and destination during a period of time is not addressed by conventional route choice models either. To bridge these gaps, this dissertation systematically evaluates people's route choice behavior using data collected in the Minneapolis - St. Paul metropolitan area after the I-35W Bridge Collapse. Both aggregate traffic data and individual survey data show gaps between models based on shortest travel time assumption and traffic conditions observed in the field. This study then employs the individual GPS trajectory and GIS maps to systematically evaluate the characteristics of routes people actually use. Merits of route choice set generation algorithms widely used in practice are assessed. The phenomenon of route diversity is clearly revealed through analysis of field data. A route portfolio model is proposed to explain the rationale of choosing a portfolio of routes under uncertainty about network conditions. It is posited that a rule-based model, comprehensively considering travelers' characteristics, additional network metrics, and previous travel experience will better replicate observed route choices than the traditional assumption of simply minimizing travel time or travel cost. Findings from this dissertation could also inform other parts of travel demand modeling.
SIGNAL : System of Integrated Growth of Networks and Land Use
(2016-07-13) Xie, Feng; Zhu, Shanjiang; Levinson, David M; dlevinson@umn.edu; Levinson, David M; University of Minnesota Nexus Research Group
This software models the co-evolution of land use and transportation network as a bottom-up process by which re-location of activities and expansion of roads are driven by interdependent decisions of individual businesses, workers, and road owners according to simple decision rules. A Simulator of Integrated Growth of Networks And Land-use (SIGNAL) is developed to implement these decentralized decision making processes, in which the Gini index and equivalent radius were computed to describe and track down the spatial patterns of space and network.
The Traffic and Behavioral Effects of the I-35W Mississippi River Bridge collapse
(Elsevier, 2010) Zhu, Shanjiang; Levinson, David M; Liu, Henry; Harder, Kathleen
The collapse, on August 1, 2007, of the I-35W bridge over the Mississippi River in Minneapolis, abruptly interrupted the usual route of about 140,000 daily vehicle trips and substantially disturbed the ﬂow pattern on the network. It took several weeks for the network to re-equilibrate, during which period, travelers continued to learn and adjust their travel decisions. A good understanding of this process is crucial for traffic management and designing mitigation schemes. A survey collected behavioral responses to the bridge collapse. Traffic data were also collected to understand the traffic conditions experienced by road users. Data from both resources are analyzed and compared. Findings of behavioral effects of capacity changes could have significant implications for travel demand modeling, especially of day-to-day travel demand
Traffic Flow and Road User Impacts of the Collapse of the I- 35W Bridge over the Mississippi River
(Minnesota Department of Transportation, Research Services Section, 2010-07) Zhu, Shanjiang; Levinson, David; Liu, Henry; Harder, Kathleen; Dancyzk, Adam
Major network disruptions have significant impacts on local travelers. A good understanding of behavioral reactions to such incidents is crucial for traffic mitigation, management, and planning. Existing research on such topics is limited. The collapse of the I-35W Mississippi River Bridge (August 1, 2007) abruptly disrupted habitual routes of about 14,000 daily trips and forced even more travelers to adapt their travel pattern to evolving network conditions. The opening of the replacement bridge on November 18, 2008 generated another disturbance (this time predictable) on the network. Such “natural” experiments provide unique opportunities for behavioral studies. This study focuses on the traffic and behavioral reactions to both bridge collapse and bridge reopening and contributes to general knowledge by identifying unique patterns following different events. Three types of data collection efforts have been conducted during the appropriate frame of reference (i.e. before vs. after bridge reconstruction): 1) GPS tracking data and associated user surveys, 2) paper and internet-based survey data gauging travel behavior in the post-bridge reconstruction phase, and 3) aggregate data relating to freeway and arterial traffic flows, traffic control, and transit ridership. Differences in reactions to planned versus unplanned events were revealed. Changes in travel cost were evaluated and their temporal and spatial patterns were analyzed. This report concludes with thorough discussions of findings from this study and policy implications.
Travel Impacts and Adjustment Strategies of the Collapse and the Reopening of the I-35W Bridge
(Springer, 2011) Zhu, Shanjiang; Tilahun, Nebiyou J; Levinson, David M; He, Xiaozheng
Major network disruptions have significant impacts on local travelers. Understanding the behavioral reactions to such incidents is crucial for traffic management and planning. This study investigates travelers' reaction to both the collapse and reopening of the I-35W Mississippi River Bridge in Minneapolis, Minnesota. Web-based surveys conducted at residences in several communities across the metropolitan area supplement hand-out/mail-back paper-based surveys distributed to workers in areas around the bridge collapse (downtown Minneapolis and the University of Minnesota). Findings from the four surveys highlight differences in travel impacts and behavioral reactions after the unplanned bridge collapse and the planned bridge reopening.
Travels Impacts of Bridge Closures 1: Lafayette Bridge Final Report
(2010-09-13) Levinson, David M; Zhu, Shanjiang
This study evaluates traffic reactions to two alternative construction plans of Lafayette Bridge crossing the Mississippi River in downtown Saint Paul, Minnesota. We calibrate a travel demand model previously developed and evaluate network performance in dif- ferent construction phases of the two alternative scenarios. Most significant changes in traffic condition occur during the bridge closure phase of scenario 2. The measur- able impacts of bridge closure on traffic conditions are limited within the region of I-494 and US 61 to the east and I-35E to the west. The increases in freeway traffic are moderate. Most travelers choose to use the arterial bridges as alternative routes. The Robert Street Bridge and the Wabasha Street Bridge will see significant traffic increases. Overall changes in consumer surplus indicate that scenario 2 has a some- what higher user cost ($5,209/day). However, the magnitude of difference in consumer surplus is very small and well within “margin of error”. The ultimate decision needs to consider construction cost savings due to faster construction, and safety issues in addition to changes in user cost.
Travels Impacts of Bridge Closures 2: Saint Croix River Bridges Final Report
(2010-09-13) Levinson, David M; Zhu, Shanjiang
This report is prepared at the request Abby McKenzie and Ed Idzorek of MnDOT to assess the expected traveler impacts of replacing or not replacing the Saint Croix River Bridge in Stillwater, Minnesota. The model that has previously been used to evaluate different Lafayette Bridge replacement scenarios is applied, using the 20 county (“collar counties”) network from the Metropolitan Council and best estimates of 2010 land uses (population and employment). The model evaluates changes in travel cost due to network reconfigurations corresponding to different scenarios. These costs would need to be compared against construction and ongoing operations and maintenance costs, and do not account for factors such as travel time reliability, the value of a redundant network for planned or unplanned closures, or changes in land use. It can be safely assumed that were a wider, faster bridge constructed there would be more development, and thus more travel demand from the Wisconsin side of the Saint Croix River. If no replacement bridge were built, we can assume that less growth (if any) would occur, and cross-river traffic would diminish. This model does not account for changes in land use, as we do not believe this has been accurately forecast for scenarios both with and without the bridge, but does account for changes in demand given the current land use under different network configurations. This is denoted as “Variable Trip Tables” in the report. Compared to the baseline (a replacement 2 lane bridge in the same location) according to the model, Construction Alternative 1, a new 4 lane bridge, produces an economic gain of $1.8 million per year. Compared to that same baseline, Construction Alternative 3, no replacement bridge at all, results in an economic loss on the order of $34.1 million per year according to the model.
Zhu, Shanjiang, David Levinson, and Henry Liu (2012) Measuring Winners and Losers from the new I-35W Mississippi River Bridge. Transportation.
(2016) Zhu, Shanjiang; Levinson, David M; Liu, Henry
The opening of the replacement for the I-35W Mississippi River Bridge on September 18th, 2008 provides a unique opportunity to evaluate the impacts generated by this additional link on network performance. Using detailed GPS data to estimate travel times on links and for origin-destination pairs, this research finds that while on average travel time improved with the reopening of the bridge, the subsequent restoration of parts of the rest of the network to their pre-collapse configuration worsened travel times significantly on average. In all cases, the distribution of winners and losers indicates clear spatial patterns associated with these network changes.

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