Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

Zhu, Shanjiang; Levinson, David

doi:10.1371/journal.pone.0134322

Cited by 161 publications

(136 citation statements)

References 46 publications

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“…Evidence from revealed route choice behavior finds after evaluating habitual routes, only 59 % of respondents from Cambridge, Massachusetts , 30 % from Boston (Ramming and Michael Scott 2001a), and 87 % from Turin, Italy (Prato et al 2006) chose paths with the shortest distance or shortest travel time. In the Minneapolis-St. Paul region, 90 % of subjects took paths one-fifth longer than average commute time (Zhu 2011;Zhu et al 2015) based on actual GPS data while more than half commute trips were at least 5 minutes longer than the shortest path based on TomTom GPS data (Tang et al 2015), and a high percentage of commuting routes were found to differ considerably from the shortest paths in Nagoya, Japan (Morikawa et al 2005 and Lexington, Kentucky (Jan et al 2000). All findings above revealed that people do not usually take the shortest paths and the utilized paths generally have higher costs than shortest ones.…”

Section: Literature Reviewmentioning

confidence: 99%

Indifference bands for boundedly rational route switching

Liu

Zhu

et al. 2016

Transportation

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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''. Indifference bands are assumed to follow lognormal distribution and are estimated in two specifications: the first one assumes every driver's indifference band is drawn from a population indifference band and the second one assumes that the mean of drivers' indifference bands is a function of their own characteristics. Route choices of 78 subjects from a GPS travel behavior study were analyzed before and after the addition of the new I-35W bridge to estimate parameters. This study provides insights into empirical analysis of bounded rationality and sheds light on indifference band estimation using empirical data.

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Section: Literature Reviewmentioning

confidence: 99%

Indifference bands for boundedly rational route switching

Liu

Zhu

et al. 2016

Transportation

Self Cite

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“…As a result, in the steady (equilibrium) state of the route switching process all the experienced travel costs for the same O-D pair are the same and minimum. However, in reality drivers do not always choose the least costly routes (Zhu and Levinson, 2015) due to a variety of reasons such as imperfect information and behavioural inertia. Rather, if the difference between the perceived travel cost of the current route and the cost of an alternative route is below a threshold, then drivers are not incentivised to switch to the alternative route.…”

Section: Bounded Rationalitymentioning

confidence: 99%

Agent-based day-to-day traffic network model with information percolation

Shang

Han

Ochieng

et al. 2016

Transportmetrica A: Transport Science

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This paper explores the impact of travel information sharing on road networks using a two-layer, agent-based, day-to-day traffic network model. The first layer (cyber layer) represents a conceptual communication network where travel information is shared among drivers. The second layer (physical layer) captures the day-to-day evolution in a traffic network where individual drivers seek to minimize their own travel costs by making route choices. A key hypothesis in this model is that instead of having perfect information, the drivers form individual groups, among which travel information is shared and utilized for routing decisions. The formation of groups occurs in the cyber layer according to the notion of percolation, which describes the formation of connected clusters (groups) in a random graph. We apply the novel notion of percolation to capture the disaggregated and distributed nature of travel information sharing. We present a numerical study on the convergence of the transport network, when a range of percolation rates are considered. The findings suggest a positive correlation between the percolation rate and the speed of convergence, which is validated through statistical analysis. A sensitivity analysis is also presented which shows a bifurcation phenomenon with regard to certain model parameters.

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“…In the traffic assignment step, if the relative excess travel cost is less than 0.001, the Wardrop user equilibrium (Wardrop 1952) is considered to be satisfied. In practice, it is unlikely that traffic is actually at equilibrium (Zhu and Levinson 2015); however, this is standard practice in models, and guarantees a unique set of link flows, but not paths, and allows solutions to be systematically compared with fewer confounds.…”

Section: Travel Demandmentioning

confidence: 99%

A model of the rise and fall of roads

Zhang

Levinson

2016

JTLU

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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 8000 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.

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Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

Cited by 161 publications

References 46 publications

Indifference bands for boundedly rational route switching

Indifference bands for boundedly rational route switching

Agent-based day-to-day traffic network model with information percolation

A model of the rise and fall of roads

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