Traffic congestion is a major societal challenge. By advising drivers on the optimal lane to drive, traffic flow can be improved, and congestion reduced. In this paper we describe the development of a lane-specific advice Human Machine Interface (HMI). Persuading drivers to follow an advice that is beneficial to the traffic situation, but may not be immediately beneficial to the drivers themselves

This paper presents a novel blockchain-based energy trading architecture for electric vehicles (EVs) within smart cities. By allowing local renewable energy providers to supply public charging stations, EV drivers can gain access to affordable energy and optimally plan for their charging operations. For this purpose, we present a smart-contract based trading platform that runs on top of a private Ethereum

Increasing demands on reliability and safety of automated driving functions require an augmented usage of simulation tools for the efficient calibration of these functions. However, finding an optimal solution can be costly, especially when the objective function is represented by scenario simulations. To face these challenges, a novel optimization scheme for simulation based calibration problems,

Cooperation is an enabler for autonomous vehicles. A promising application of cooperative driving is high-density platooning, where trucks drive with low inter-vehicle distances. It aims at increasing the road and fuel efficiency whilst guaranteeing safety. The safe and efficient coordination of the control requires the regular and reliable exchange of V2V messages. The performance of the vehicular

Internet of Things (IoT) and Cloud Computing (CC) technologies are becoming critical requirements to the advancement of intelligent transportation systems (ITSs). ITSs generally rely on captured images to evaluate the status of traffic and perform vehicle statistics. However, such images may contain confidential information, and thus, securing such images is paramount. Therefore, we propose in this

License plate recognition (LPR) technology has been used to combat vehicle-related crime in urban areas in many developed contexts. However, commercially available LPR systems are expensive and not feasible for large scale adoption in developing countries. The development of a low-cost crowd-sourced solution requires an informed approach to the selection of an appropriate camera, as well as a realistic

Connected and autonomous vehicles have been significantly studied. They are connected to a network and communicate by exchanging information with each other, so they can detect blind spots that cannot be recognized by non-connected (conventional) vehicles. Therefore, they are expected to contribute to traffic efficiency and safety. However, even if connected vehicles are put to practical use in the

Dear readers, It is with pleasure and pride that we present the first issue of the IEEE Open Journal of Intelligent Transportation Systems (OJ-ITS). Responding to a world-wide demand for Gold Open Access Journals, ‘OJ-ITS’ has been developed as one of seven new Open Journals published by IEEE. Published by the IEEE Intelligent Transportation System Society, OJ-ITS publishes both scientific as well

This paper presents a surround vehicle motion prediction algorithm for multi-lane turn intersections using a Long Short-Term Memory (LSTM)-based Recurrent Neural Network (RNN). The motion predictor is trained using the states of subject and surrounding vehicles, which are collected by sensors mounted on an autonomous vehicle. Data on 484 vehicle trajectories were collected from real traffic situations

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