Knowing when a driver will quit cruising and either leave the area or park at an expensive off-street facility is critical for modeling parking search. We employ a serious game - PARKGAME for estimating the dynamics of drivers' decision making. 49 Participants of a game experiment were involved in three scenarios where they had to arrive on time to a fictional appointment or face monetary penalties, and to choose between uncertain but cheap on-street parking or a certain but costly parking lot. Scenarios diverged on the time to appointment and distance between the meeting place and parking lot locations. Players played a series of 8 or 16 computer games on a Manhattan grid road network with high on-street parking occupancy and nearby parking lot of unlimited capacity. Players' choices to quit or to continue search, as dependent on the search time, were analyzed with an accelerated-failure time (AFT) model. Results show that drivers are mostly risk-averse and quit on-street parking search very soon after potential loses begin to accumulate. The implications of game-based methods for simulation model development and sustainable parking policy are further discussed.
|Number of pages||7|
|Journal||CEUR Workshop Proceedings|
|State||Published - 1 Jan 2020|
|Event||11th International Workshop on Agents in Traffic and Transportation, ATT 2020 - Santiago de Compostela, Spain|
Duration: 4 Sep 2020 → …
ASJC Scopus subject areas
- Computer Science (all)