Blocking Avoidance in Transportation Systems

TL;DR

This paper models the blocking problem in transportation systems with connected vehicles, proposing a cloud-based traffic control system and a shortest delay routing algorithm that reduces waiting times at intersections.

Contribution

It introduces a queuing model considering blocking probability and vehicle communication capabilities, and develops a shortest delay algorithm based on this model.

Findings

Simulation confirms the model's accuracy.

The proposed algorithm significantly reduces intersection waiting times.

Communication-enabled vehicles improve traffic flow efficiency.

Abstract

The blocking problem naturally arises in transportation systems as multiple vehicles with different itineraries share available resources. In this paper, we investigate the impact of the blocking problem to the waiting time at the intersections of transportation systems. We assume that different vehicles, depending on their Internet connection capabilities, may communicate their intentions (e.g., whether they will turn left or right or continue straight) to intersections (specifically to devices attached to traffic lights). We consider that information collected by these devices are transmitted to and processed in a cloud-based traffic control system. Thus, a cloud-based system, based on the intention information, can calculate average waiting times at intersections. We consider this problem as a queuing model, and we characterize average waiting times by taking into account (i) blocking probability, and (ii) vehicles' ability to communicate their intentions. Then, by using average waiting times at intersection, we develop a shortest delay algorithm that calculates the routes with shortest delays between two points in a transportation network. Our simulation results confirm our analysis, and demonstrate that our shortest delay algorithm significantly improves over baselines that are unaware of the blocking problem.