Modeling the impact of on-line navigation devices in traffic flows

Abstract

We consider a macroscopic multi-population traffic flow model on networks accounting for the presence of drivers (or autonomous vehicles) using navigation devices to minimize their instantaneous travel cost to destination. The strategic choices of each population differ in the degree of information about the system: while part of the agents knows only the structure of the network and minimizes the traveled distance, others are informed of the current traffic distribution, and can minimize their travel time avoiding the most congested areas. In particular, the different route choices are computed solving eikonal equations on the road network and they are implemented at road junctions. The impact on traffic flow efficiency is illustrated by numerical experiments. We show that, even if the use of routing devices contributes to alleviate congestion on the whole network, it also results in increased traffic on secondary roads. Moreover, the generalized use of real-time information can even deteriorate the efficiency of the network.

Obscuring digital route choice information prevents delay-induced congestion

“…tion to all individuals may optimally improve system performance. Indeed, our results show that random route choices of the uninformed drivers lead to the same increase of the critical in-rate at which congestion occurs as observed for averaged information, similar to previous work that investigated this effect on selfish routing without explicitly discussing the role of information delay 14,31,32 . The combination of analytical insights in the minimal two street network and the observations in networks suggests that our results may robustly transfer to more complex settings as well.…”

“…Specifically, it has been shown from a systemic perspective that selfish routing may lead to non-optimal collective states in which the travel time averaged across all vehicles is higher than the theoretical optimum 6,[8][9][10][11] . Furthermore, unpleasant side-effects exist, such as increased usage of low-capacity roads through residential areas, use of complicated routes with higher accident risk, and increased noise and air pollution [12][13][14] .…”

Impact on Traffic of Delayed Information in Navigation Systems

“…In the literature, almost all relevant works within the macroscopic dynamic routing framework present models in which the route choice is based on the current state of traffic and no delay is considered [2], [4], [5], [6]. It is worth to mention that in [1] the authors propose a framework that allows for dynamic routing of drivers based on delayed information, but they do not elaborate on the effects caused by the latter.…”

A Macroscopic Model for Platooning in Highway Traffic

“…Macroscopic traffic flow models have known an increasing popularity in the last decades in the engineering and the applied mathematics literature, due to their capability of capturing traffic characteristics, their low computational cost and their relevance for solving optimal control problems [23,32]. Yet, new technical advances affecting transportation dynamics, like routing devices and autonomous vehicles, are changing the current traffic characteristics, requiring the design of new models [12,28,29]. In particular, vehicle automation paves the way to truck platooning, intended to optimize freight transportation and to reduce fuel consumption [2,18,24,33].…”