A Portfolio Theory of Route Choice

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 choos- ing 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 net- work 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 (de- fined 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 port- folio of routes could be the rational choice of a traveler who wants to optimize route decisions under variability.Transportation planning, route choice, travel behavior, link performance

Disruptions to Transportation Networks: A Review

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.Network disruption; Travel survey; Travel behavior

The Hierarchy of Roads, the Locality of Traffic, and Governance

This study investigates the usage of road networks both within and outside of home jurisdictions (city (or town) and county of residence) by analyzing GPS data collected in the Minneapolis - Saint Paul metropolitan area, which tracked volunteers’ travel behavior to determine which roads (and thus which class of roads) users chose to accommodate their travel needs. More than half of the travel on county roads and city streets occur outside of one’s home city, but most travel is within one’s home county. The average share of travel distance in the home county is more than 70 percent for both county and city streets. The high share, which does not even account for non-residents destined for the county to work or shop, e.g., implies that the free rider problem on city and county streets at the county level is minimal. Of particular con- cern is travel on city roads in cities other than one’s own. To the extent that this is to go to a destination in that city, that travel is also local. However, because city and county roads are typically funded by those jurisdictions from land-based sources such as property taxes, through trips with neither end in the city through which they are traveling are in a very real sense "free riders", and pose a problem. With growing trip lengths and emerging economies of scale in road management, it may be appropriate to consider moving more roads from township, town, or city level to the county level of government.Transportation financing, GPS, road utilization, hierarchy of roads, transporta- tion governance

People don't use the shortest path

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.Rationality, travel behavior, transport geography, commuting, transportation networks

Agent-Based Model of Price Competition and Product Differentiation on Congested Networks

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.Network dynamics, road pricing, autonomous links, privatization, price competition, product differentiation, agent-based transportation model

Enhancing Transportation Education through On-line Simulation using an Agent-Based Demand and Assignment Model

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.

An Agent-based Route Choice Model

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.Agent-based model, route choice, traffic assignment, travel demand modeling

Measuring Winners and Losers from the new I-35W Mississippi River Bridge

The opening of the replacement for the I-35W Mississippi River Bridge bridge on September 18th, 2008 provides a unique opportunity to evaluate the impacts generated by this additional link on network performance, and thus empirically test whether a Braess Paradox occurred. Using detailed GPS data to estimate travel times on links and for origin-destination pairs, this research Þnds 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 conÞguration worsened travel times signiÞcantly on average. In all cases, the distribution of winners and losers indicates clear spatial patterns associated with these network changes. While no Braess paradox was found in this case, the research provides a method for measuring such phenomena.Network structure, travel behavior, transport geography, commuting, network disruption, Braess paradox

The traffic and behavioral effects of the I-35W Mississippi River bridge collapse

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 ßow 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 demandMinnesota, Minneapolis, I-35W bridge collapse, travel behavior, travel survey

Economic Model for Vehicle Ownership Quota Policies and Applications in China

AbstractTraffic congestion has caused huge economic loss and environmental pollution every year. As a demand management policy to reduce congestion, vehicle ownership quota system that directly controls the number of vehicles on the road has recently been adopted in some metropolitan areas including Beijing and Shanghai. When it comes to implementation of quota system, Beijing uses the plate lottery system, so that everyone interested in owning a vehicle can participate and there's no monetary transaction in the process. Shanghai, on the other hand, uses the plate auction system and participants bid for the limited number of vehicle plates available. This paper aims at building a theoretical model that quantitatively analyzes the benefits of such policies. This study extends the joint decision model of vehicle ownership and mileage model, and applied compensating variation method to measure the net social impact change of the different quota systems. Under this proposed framework, a numerical demonstration is conducted