English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The fast-growing market of autonomous vehicles, unmanned aerial vehicles, andfleets in general necessitates the design of smart and automatic navigationsystems considering the stochastic latency along different paths in the trafficnetwork. The longstanding shortest path problem in a deterministic network,whose counterpart in a congestion game setting is Wardrop equilibrium, has beenstudied extensively, but it is well known that finding the notion of an optimalpath is challenging in a traffic network with stochastic arc delays. In thiswork, we propose three classes of risk-averse equilibria for an atomicstochastic congestion game in its general form where the arc delaydistributions are load dependent and not necessarily independent of each other.The three classes are risk-averse equilibrium (RAE), mean-variance equilibrium(MVE), and conditional value at risk level $\alpha$ equilibrium(CVaR$_\alpha$E) whose notions of risk-averse best responses are based onmaximizing the probability of taking the shortest path, minimizing a linearcombination of mean and variance of path delay, and minimizing the expecteddelay at a specified risky quantile of the delay distributions, respectively.We prove that for any finite stochastic atomic congestion game, therisk-averse, mean-variance, and CVaR$_\alpha$ equilibria exist. We show thatfor risk-averse travelers, the Braess paradox may not occur to the extentpresented originally since players do not necessarily travel along the shortestpath in expectation, but they take the uncertainty of travel time intoconsideration as well. We show through some examples that the price of anarchycan be improved when players are risk-averse and travel according to one of thethree classes of risk-averse equilibria rather than the Wardrop equilibrium.

Risk-Averse Equilibrium for Autonomous Vehicles in Stochastic Congestion Games