Exploring Route Choice Behaviours Accommodating Stochastic Choice Set Generations

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.

From Delay to Disruption: Impact of Service Degradation on Public Transport Networks

Public transport networks (PTN) are affected daily by different types of disturbances. In fact, between a single delay and a long service interruption, there is a range of disruptions with different impacts, depending on their characteristics. Despite this, in literature, the common definition of disruption is a link closure for a certain amount of time. Low interest is given to different types of disruptions or to the connection between delays and disruptions. In addition, in multimodal PTN a physical link closure is not always observable, but rather people experience delays or cancelled stops on different lines. The aim of this work is to explore the relationship between delays and disruptions, analyzing different degrees of disruptions, in relation to duration, delay, size, and network characteristics. Real disturbances of the PTNs in Zürich and Bern, Switzerland, are analyzed to identify disruptions with different characteristics. Therefore, the disruption impact is computed on simulated origin–destinations (ODs), based on the sets of possible paths with and without the disruption. For this purpose, a choice set generation algorithm is used. Finally, relationships between the disruption characteristics and the impact are analyzed to identify the main features of a disruption.

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

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

Toll Choice and Stochastic User Equilibrium: Ticking All the Boxes

Stochastic user equilibrium is a behaviorally realistic framework for strategic demand modeling and forecasting in cities/regions where there are multiple tolled facilities, especially when it comes to patronage forecasting for existing or planned tolled facilities. However, there is currently no algorithm available in the literature or in commercial software that provides a comprehensive approach for stochastic user equilibrium assignment that addresses the generation of route choice sets for tolled roads, path overlap, and high levels of convergence. This paper presents a novel choice set generation algorithm combined with the path-size logit model and the bi-conjugate Frank-Wolfe equilibrium assignment in a comprehensive algorithm for forecasting tolled road patronage, along with the results of its application to a real-life model in Brisbane, Australia.

Comprehensive Exploratory Analysis of Truck Route Choice Diversity in Florida

This study presents a comprehensive exploratory analysis of truck route choice diversity in the state of Florida, for both long-haul and short-haul truck travel segments. It employs six metrics to measure three different dimensions of diversity in truck route choice between any given origin–destination (OD) pair. These dimensions are: (a) number of distinct routes used to travel between the OD pair, (b) the extent of overlap (or lack thereof) among the routes, and (c) the evenness (or dominance) in the usage of different unique routes. The diversity metrics were applied to a large database of 73,000 truck routes derived from 200 million GPS records. Descriptive analysis and statistical modeling of the diversity metrics offered insights into the determinants of various dimensions of truck route choice diversity between any OD pair. The results are useful for improving choice set generation algorithms for truck route choice modeling and in truck route policies and investments.