# Estimation of urban traffic state with probe vehicles

arXiv: https://arxiv.org/abs/1811.05394 · HTML: https://mlsanity.com/paper/1811.05394/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Nov 2018.

## Built on by (most cited first, 1 of 1)

- [Deep Reinforcement Q-Learning for Intelligent Traffic Signal Control with Partial Detection](https://mlsanity.com/paper/2109.14337/) (2021)

## Abstract (arXiv)

We present in this paper a method to estimate urban traffic state with communicating vehicles. Vehicles moving on the links of the urban road network form queues at the traffic lights. We assume that a proportion of vehicles are equipped with localization and communication capabilities, and name them probe vehicles. First, we propose a method for the estimation of the penetration ratio of probe vehicles, as well as the vehicles arrival rate on a link. Moreover, we show that turn ratios at each junction can be estimated. Second, assuming that the turn ratios at each junction are given, we propose an estimation of the queue lengths on a 2-lanes link, by extending a 1-lane existing method. Our extension introduces vehicles assignment onto the lanes. Third, based on this approach, we propose optimal control laws for the traffic light and for the assignment of the arriving vehicles onto the lane queues. Finally, numerical simulations are conducted with Veins framework that bi-directionally couples microscopic road traffic and communication simulators. We illustrate and discuss our propositions with the simulation results.