Drivers’ parking location choice under uncertain parking availability and search times: A stated preference experiment

Chaniotakis, Emmanouil; Pel, Adam J. · 2015 · OpenAlex-citations

DOI: 10.1016/j.tra.2015.10.004

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates how drivers choose parking locations when facing uncertainty regarding parking availability and search times. The research is motivated by the significant contribution of parking-related cruising traffic to urban congestion, emissions, and safety issues. While pricing policies and Parking Guidance and Information (PGI) systems are common solutions, their effectiveness depends on understanding driver behavior under uncertainty. Specifically, the paper aims to quantify how probabilities of finding a vacant spot influence parking location choices, a factor often overlooked in previous models. The researchers conducted a stated preference experiment using internet-based questionnaires targeting drivers making shopping trips in the Netherlands. The survey included 397 respondents, a sample deemed representative of the Dutch driving population. Participants were presented with 12 choice scenarios, each offering two parking alternatives defined by six attributes: parking cost, walking distance to destination, travel time to the parking area, parking type (on-street vs. off-street), probability of finding a spot upon arrival, and probability of finding a spot after 8 minutes of searching. The experimental design was optimized using efficient design methods and refined through two pilot studies to ensure realistic attribute levels and minimize survey complexity. The data were analyzed using various Random Utility Maximization (RUM) discrete choice models, including Multinomial Logit (MNL), Nested Logit, Mixed Logit, and Panel Effect Mixed Logit models. The results indicate that drivers are willing to spend time searching for parking, but their choices are heavily influenced by the likelihood of success. Notably, the probability of finding a vacant spot after 8 minutes of searching was the second most important factor in determining parking location choice, ranking higher than the probability of finding a spot immediately upon arrival, which ranked fourth. Additionally, the study found that incorporating heterogeneity in preferences and inter-driver differences significantly improved the predictive power of the models compared to standard MNL specifications. The findings provide critical insights for the development of traffic assignment and simulation models. By quantifying the impact of parking uncertainty, the study supports the evaluation of PGI and reservation systems, which can mitigate cruising traffic by providing accurate availability information. The results suggest that providing information about future availability (e.g., after a short search period) may be more influential on driver behavior than immediate availability alone. These behavioral parameters can be integrated into microscopic and macroscopic traffic models to better assess the efficacy of parking policies and Intelligent Transport Systems in reducing urban congestion.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• speed choice