Online incentive-compatible mechanisms for traffic intersection auctions

We present novel online mechanisms for traffic intersection auctions in which users bid priority service. assume that at the front of their lane are requested to declare delay cost, i.e. value time, and serviced decreasing order declared cost. Since expected arrive dynamically intersections, static pricing approaches may fail estimate user waiting time accurately, lead non-strategyproof payments. To address this gap, we propose two Markov chain models determine participants auction. Both take into account probability future arrivals intersection. In a first model, is uniform across lanes This queue-based model only tracks number lower- higher-bidding on access lanes, empty lanes. The uniformness assumption relaxed second, lane-based accounts lane-specific arrival probabilities expense an extended state space. then design mechanism incentive-compatible payments dynamic sense. resulting maximize social welfare long run. Numerical experiments four-lane reported compared mechanism. Our findings show misreport costs. turn, proposed shown be