scholarly journals Measuring the Reliability of Methods and Algorithms for Route Choice Set Generation: Empirical Evidence from a Survey in the Naples Metropolitan Area

2020 ◽  
Vol 14 (1) ◽  
pp. 50-66
Author(s):  
Fulvio Simonelli ◽  
Fiore Tinessa ◽  
Ciro Buonocore ◽  
Francesca Pagliara
Keyword(s):  
Metropolitan Area ◽  
Route Choice ◽  
Network Coverage ◽  
Trade Off ◽  
Network Loading ◽  
Data Collection Process ◽  
Choice Sets ◽  
And Performance ◽  
Choice Set Generation ◽  
Choice Set

Background: Route choice set definition is a very sensitive phase of the route choice simulation. Several heuristics, generally based on shortest path algorithm repetition, give as output choice sets that are very large, lading to questions about their behavioural consistency. Objective: This paper proposes a comparison of the main route choice set generation methods, contrasting the results of the commonly implemented heuristics with the revealed choice sets of a sample of employees and students moving within the Metropolitan Area of Naples. Methods: We described the data collection process and provided a statistical analysis of the sample data. In addition, since coverage measures and performance indicators, usually applied in the literature, do not take into account any possible biases related to the generated choice set cardinality. The current work proposes an analysis of the coverage of routes that are generated by the heuristics towards the revealed routes. Results: We observed that when the heuristics did not provide overlapped routes, although giving higher network coverage, they introduced a higher number of links not belonging to any observed route. In general, this may cause significant network loading errors. Therefore, the quality of a method for choice set generation should be measured as a function of the trade-off amongst network coverage and network loading bias due to excessive cardinality of the generated choice-sets. Conclusion: We found the randomization method, which is also less computational demanding, provided the best trade-off amongst network coverage and network loading bias

scholarly journals META-ANALYSIS OF CHOICE SET GENERATION EFFECTS ON ROUTE CHOICE MODEL ESTIMATES AND PREDICTIONS

Transport ◽  
2012 ◽  
Vol 27 (3) ◽  
pp. 286-298 ◽  
Author(s):  
Carlo Giacomo Prato
Keyword(s):  
Large Scale ◽  
Choice Model ◽  
Meta Analysis ◽  
Route Choice ◽  
Behavior Modeling ◽  
Path Generation ◽  
Choice Sets ◽  
True Model ◽  
Choice Set Generation ◽  
Choice Set

Large scale applications of behaviorally realistic transport models pose several challenges to transport modelers on both the demand and the supply sides. On the supply side, path-based solutions to the user assignment equilibrium problem help modelers in enhancing the route choice behavior modeling, but require them to generate choice sets by selecting a path generation technique and its parameters according to personal judgments. This paper proposes a methodology and an experimental setting to provide general indications about objective judgments for an effective route choice set generation. Initially, path generation techniques are implemented within a synthetic network to generate possible subjective choice sets considered by travelers. Next, ‘true model estimates’ and ‘postulated predicted routes’ are assumed from the simulation of a route choice model. Then, objective choice sets are applied for model estimation and results are compared to the ‘true model estimates’. Last, predictions from the simulation of models estimated with objective choice sets are compared to the ‘postulated predicted routes’. A meta-analytical approach allows synthesizing the effect of judgments for the implementation of path generation techniques, since a large number of models generate a large amount of results that are otherwise difficult to summarize and to process. Meta-analysis estimates suggest that transport modelers should implement stochastic path generation techniques with average variance of its distribution parameters and correction for unequal sampling probabilities of the alternative routes in order to obtain satisfactory results in terms of coverage of ‘postulated chosen routes’, reproduction of ‘true model estimates’ and prediction of ‘postulated predicted routes’.

STOCHASTIC ROUTE CHOICE SET GENERATION: BEHAVIORAL AND PROBABILISTIC FOUNDATIONS

2007 ◽  
Vol 3 (3) ◽  
pp. 173-189 ◽  
Author(s):  
Piet H.L. Bovy ◽  
Stella Fiorenzo-Catalano
Keyword(s):  
Route Choice ◽  
Choice Set Generation ◽  
Choice Set

scholarly journals Path complexity and bicyclist route choice set quality assessment

2019 ◽  
Author(s):  
Thomas Koch ◽  
Luk Knapen ◽  
Elenna Dugundji
Keyword(s):  
Shortest Paths ◽  
Route Choice ◽  
Large Set ◽  
Map Matching ◽  
Demand Modeling ◽  
Urban Road ◽  
Modeling Process ◽  
Choice Sets ◽  
Minimum Number ◽  
Choice Set

AbstractEveryday route choices made by bicyclists are known to be more difficult to explain than vehicle routes, yet prediction of these choices is essential for guiding infrastructural investment in safe cycling. Building route choice sets is a difficult task. Even including detailed attributes such as the number of left turns, the number of speed bumps, distance and other route choice properties we still see that choice set quality measures suggest poor replication of observed paths. In this paper we study how the concept of route complexity can help generate and analyze plausible choice sets in the demand modeling process. The complexity of a given path in a graph is the minimum number of shortest paths that is required to specify that path. Complexity is a path attribute which could potentially be considered to be important for route choice in a similar way. The complexity was determined for a large set of observed routes and for routes in the generated choice sets for the corresponding origin-destination pairs. The respective distributions are shown to be significantly different so that the choice sets do not reflect the traveler preferences, this is in line with classical choice set quality indicators. Secondly, we investigate often used choice set quality methods and formulate measures that are less sensitive to small differences between routes that can be argued to be insignificant or irrelevant. Such difference may be partially due to inaccuracy in map-matching observations to dense urban road networks.

scholarly journals Exploring Route Choice Behaviours Accommodating Stochastic Choice Set Generations

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Shin-Hyung Cho ◽  
Seung-Young Kho
Keyword(s):  
Radio Frequency Identification ◽  
Choice Model ◽  
Route Choice ◽  
Revealed Preference ◽  
Guidance System ◽  
Model Parameters ◽  
Generation Model ◽  
Choice Behaviour ◽  
Choice Set Generation ◽  
Choice Set

Modelling route choice behaviours are essential in traffic operation and transportation planning. Many studies have focused on route choice behaviour using the stochastic model, and they have tried to construct the heterogeneous route choice model with various types of data. This study aims to develop the route choice model incorporating travellers’ heterogeneity according to the stochastic route choice set. The model is evaluated from the empirical travel data based on a radio frequency identification device (RFID) called dedicated short-range communication (DSRC). The reliability level is defined to explore the travellers’ heterogeneity in the choice set generation model. The heterogeneous K-reliable shortest path- (HK α RSP-) based route choice model is established to incorporate travellers’ heterogeneity in route choice behaviour. The model parameters are estimated for the mixed path-size correction logit (MPSCL) model, considering the overlapping paths and the heterogeneous behaviour in the route choice model. The different behaviours concerning the chosen routes are analysed to interpret the route choice behaviour from revealed preference data by comparing the different coefficients’ magnitude. There are model validation processes to confirm the prediction accuracy according to travel distance. This study discusses the policy implication to introduce the traveller specified route travel guidance system.

Evaluation of choice set generation algorithms for route choice models

2006 ◽  
Vol 144 (1) ◽  
pp. 235-247 ◽  
Author(s):  
Shlomo Bekhor ◽  
Moshe E. Ben-Akiva ◽  
M. Scott Ramming
Keyword(s):  
Route Choice ◽  
Choice Models ◽  
Choice Set Generation ◽  
Choice Set
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