A novel intrusion detection system against spoofing attacks in connected electric vehicles

The Electric Vehicles (EVs) market has seen rapid growth recently despite the anxiety about driving range. Recent proposals have explored charging EVs on the move, using dynamic wireless charging that enables power exchange between the vehicle and the grid while the vehicle is moving. Specifically, part of the literature focuses on the intelligent routing of EVs in need of charging. Inter-Vehicle communications (IVC) play an integral role in intelligent routing of EVs around a static charging station or dynamic charging on the road network. However, IVC is vulnerable to a variety of cyber attacks such as spoofing. In this paper, a probabilistic cross-layer Intrusion Detection System (IDS), based on Machine Learning (ML) techniques, is introduced. The proposed IDS is capable of detecting spoofing attacks with more than accuracy. The IDS uses a new metric, Position Verification using Relative Speed (PVRS), which seems to have a significant effect in classification results. PVRS compares the distance between two communicating nodes that is observed by On-Board Units (OBU) and their estimated distance using the relative speed value that is calculated using interchanged signals in the Physical (PHY) layer

Assessing the potential of the strategic formation of urban platoons for shared automated vehicle fleets

This paper addresses the problem of studying the impacts of the strategic formation of platoons in automated mobility-on-demand (AMoD) systems in future cities. Forming platoons has the potential to improve traffic efficiency, resulting in reduced travel times and energy consumption. However, in the platoon formation phase, coordinating the vehicles at formation locations for forming a platoon may delay travelers. In order to assess these effects, an agent-based model has been developed to simulate an urban AMoD system in which vehicles travel between service points transporting passengers either forming or not forming platoons. A simulation study was performed on the road network of the city of The Hague, Netherlands, to assess the impact on traveling and energy usage by the strategic formation of platoons. Results show that forming platoons could save up to 9.6% of the system-wide energy consumption for the most efficient car model. However, this effect can vary significantly with the vehicle types and strategies used to form platoons. Findings suggest that, on average, forming platoons reduces the travel times for travelers even if they experience delays while waiting for a platoon to be formed. However, delays lead to longer travel times for the travelers with the platoon leaders, similar to what people experience while traveling in highly congested networks when platoon formation does not happen. Moreover, the platoon delay increases as the volume of AMoD requests decreases; in the case of an AMoD system serving only 20% of the commuter trips (by private cars in the case-study city), the average platoon delays experienced by these trips increase by 25%. We conclude that it is beneficial to form platoons to achieve energy and travel efficiency goals when the volume of AMoD requests is high.Industrial Ecolog

Software Protection and Secure Authentication for Autonomous Vehicular Cloud Computing

Artificial Intelligence (AI) is changing every technology we deal with. Autonomy has been a sought-after goal in vehicles, and now more than ever we are very close to that goal. Vehicles before were dumb mechanical devices, now they are becoming smart, computerized, and connected coined as Autonomous Vehicles (AVs). Moreover, researchers found a way to make more use of these enormous capabilities and introduced Autonomous Vehicles Cloud Computing (AVCC). In these platforms, vehicles can lend their unused resources and sensory data to join AVCC. In this dissertation, we investigate security and privacy issues in AVCC. As background, we built our vision of a layer-based approach to thoroughly study state-of-the-art literature in the realm of AVs. Particularly, we examined some cyber-attacks and compared their promising mitigation strategies from our perspective. Then, we focused on two security issues involving AVCC: software protection and authentication. For the first problem, our concern is protecting client’s programs executed on remote AVCC resources. Such a usage scenario is susceptible to information leakage and reverse-engineering. Hence, we proposed compiler-based obfuscation techniques. What distinguishes our techniques, is that they are generic and software-based and utilize the intermediate representation, hence, they are platform agnostic, hardware independent and support different high level programming languages. Our results demonstrate that the control-flow of obfuscated code versions are more complicated making it unintelligible for timing side-channels. For the second problem, we focus on protecting AVCC from unauthorized access or intrusions, which may cause misuse or service disruptions. Therefore, we propose a strong privacy-aware authentication technique for users accessing AVCC services or vehicle sharing their resources with the AVCC. Our technique modifies robust function encryption, which protects stakeholder’s confidentiality and withstands linkability and “known-ciphertexts” attacks. Thus, we utilize an authentication server to search and match encrypted data by performing dot product operations. Additionally, we developed another lightweight technique, based on KNN algorithm, to authenticate vehicles at computationally limited charging stations using its owner’s encrypted iris data. Our security and privacy analysis proved that our schemes achieved privacy-preservation goals. Our experimental results showed that our schemes have reasonable computation and communications overheads and efficiently scalable

Designing innovative transport systems, electric and automated on priority corridors

This study focuses on two great technologies improvements, they are vehicle automation and newest fast charging methods that could enable new and innovative transport systems. Automated and electric vehicles could will enable first/last mile efficient transport services, economically and environmentally sustainable that could be useful to improve transportation services in rural sprawled areas with a low density of transport demand. It is proposed an innovative system concerning electric and automated vehicles in specific paths called priority corridors, it is described a methodology of designing leaving the detailed analysis and impacts analysis to future studies. Automation, Internet of Things and smartphones are revolutionising mobility and with it the economy. With such mobility revolution all aspects of our life, economic, social and environmental will be impacted. Automated vehicles can be deployed as personal vehicles or as shared vehicles; while personal vehicles are not yet ready for deployment shared vehicles are. This work aims to propose an innovative transport system with off the shelf technologies and a methodology of design dealing with vehicle automation, current designing methods and environmental impacts. The methodology foresees six steps, they could be repeated with an iterative change of parameters in order to compare different results. These steps are: Parameters and input data, Itinerary analysis and corridors identification, Corridor choice and speed profile generation, Vehicle choice and fleet dimensioning, Electric traction needs and specifications, Results evaluation. Four categories of results are considered: vehicles and operators needed, energy consumption, transportation and socio-economic evaluation. After the results calculation, it is required an evaluation of them. Methodology is applied to Mentana, a little town in the outskirts of Rome. Mentana has only one corridor that links city centre to train station be distant eight kilometres. Economic results are positive, revenues cover operative costs and the whole system doesn’t require subsides

Intersection control with connected and automated vehicles: a review

Purpose: This paper aims to review the studies on intersection control with connected and automated vehicles (CAVs). Design/methodology/approach: The most seminal and recent research in this area is reviewed. This study specifically focuses on two categories: CAV trajectory planning and joint intersection and CAV control. Findings: It is found that there is a lack of widely recognized benchmarks in this area, which hinders the validation and demonstration of new studies. Originality/value: In this review, the authors focus on the methodological approaches taken to empower intersection control with CAVs. The authors hope the present review could shed light on the state-of-the-art methods, research gaps and future research directions

Routing of Electric Vehicles in a Stochastic Network with Non-recurrent Incidents

An approach for mapping an electric vehicle (EV) driver’s travel time constraints and risk-taking behavior to real-time routing in a probabilistic, time-dependent (or stochastic) network is proposed in this paper. The proposed approach is based on a heuristic algorithm that finds the shortest path according to the driver’s preferences. Accounting for en-route delays and alternate routes, the EV routing problem in stochastic networks is shown to exhibit other than the First-In-First-Out (FIFO) property; i.e., the traveling time for those who depart earlier may not reach sooner of those who depart later or wait en-route in the charging stations. The proposed approach provides EV drivers the option to manage their trip and reach the destination on time, while by taking advantage of the non-FIFO characteristics of the traffic network, charge their cars en-route. The proposed routing algorithm is tested on a given stochastic transportation network. The best routes based on the driver’s preferences are identified while accounting for the best-planned delays at the charging stations or en-route