Abstract

Daily traffic congestions form major problems for businesses such as logistical service providers and distribution firms. They cause late arrivals at customers and additional hiring costs for the truck drivers. The additional costs of traffic congestions can be reduced by taking into account and avoid well-predictable traffic congestions within off-line vehicle route plans. In the literature, various strategies are proposed to avoid traffic congestions, such as selecting alternative routes, changing the customer visit sequences, and changing the vehicle-customer assignments. We investigate the impact of these and other congestion avoidance strategies in off-line vehicle route plans on the performance of these plans in reality. For this purpose, we develop a set of VRP instances on real road networks, and a speed model that inhabits the main characteristics of peak hour congestion. The instances are solved for different levels of congestion avoidance using a modified Dijkstra algorithm and a restricted dynamic programming heuristic. Computational experiments show that 99% of late arrivals at customers can be eliminated if traffic congestions are accounted for off-line. On top of that, almost 70% of the extra duty times caused by the traffic congestions can be eliminated by clever avoidance strategies.

Abstract

The effect of traffic congestion within an urban region can be eliminated by curbing the number of vehicles that use the congested part of the transport network. To do so, earlier work by the authors introduced a novel route-reservation architecture that manages the vehicle departure times and makes the appropriate routing decisions so that vehicles arrive at their destination at the earliest possible time avoiding the congested parts of the network Menelaou et al. (2017a,b). Under the proposed route-reservation architecture, the future state of each road segment is predicted based on the received reservations and assuming that all vehicles travel at a constant speed which is set equal with the free-flow speed. Even within a homogeneous region, this assumption is not always valid which can lead to non accurate estimation of the time that a vehicle occupies a road segment which in turn affects the accuracy of the overall architecture. Therefore, the key objective of this work is to investigate different prediction schemes that improve the prediction-accuracy of vehicles travel times within each road segment. In this paper we explore two prediction methods, an Exponential Moving Average (EMA) and a Multiple Linear Regression (MLR) method. The performance of the two prediction schemes is also presented. Finally, realistic simulation results across an urban region of San Francisco demonstrate the gains that can be achieved applying the proposed prediction methods. C. Menelaou and P. Kolios and S. Timotheou and C.G. Panayiotou, "Effective Prediction of Road Segment Occupancy for the Route-Reservation Architecture", 2018 15th IFAC Symposium on Control in Transportation Systems CTS 2018, IFAC-PapersOnLine, pp 470 - 475, doi: https://doi.org/10.1016/j.ifacol.2018.07.07. Copyrights belong to Elsevier 2018 LTD

Abstract

Aiming to alleviate traffic congestion, many congestion avoidance and traffic optimization systems have been proposed recently. However, most of them suffer from three main problems. Firstly scalability: they rely on a centralized server, which has to perform intensive communication and computational tasks. Secondly unpredictability: they use smartphones and other sensors to detect the congested roads and warn upcoming vehicles accordingly. In other words, they are used to solve the problem rather than avoiding it. Lastly, infrastructure dependency: they assume the presence of pre-installed infrastructures such as roadside unit (RSU) or cellular 3G/4G networks. Motivated by the above-mentioned reasons, in this paper, we proposed a fully distributed and infrastructure-less congestion avoidance and traffic optimization system for VANET (Vehicular Ad-hoc Networks) in urban environments named DIFTOS (Distributed Infrastructure-Free Traffic Optimization System), in which the city map is divided into a hierarchy of servers. The vehicles that are located in the busy road intersections play the role of servers, thus DIFTOS does not rely on any centralized server and does not need internet connectivity or RSU or any kind of infrastructure. As far as we know, in the literature of congestion avoidance using VANET, DIFTOS is the first completely infrastructure-free congestion avoidance system. The effectiveness and scalability of DIFTOS have been proved by simulation under different traffic conditions. Document type: Article