Shared Vehicles Research Articles

Research on dynamic game operation behavior of multi‐oligopoly car‐sharing operators considering off‐peak pricing factors

AbstractIn the practical evolution of shared vehicle systems, numerous societal factors come into play, such as inadequate parking infrastructure, battery capacity, and the budget for technological improvement. This study integrates the operational realities of shared vehicle systems with governmental carbon emission reduction policies and “double control” initiatives. Considering various perturbations, the paper constructs a Stackelberg short‐term model among diverse oligopolistic shared vehicle operators with technique sharing. It also develops a long‐term repeated game framework to scrutinize the impact of pertinent parameters on operators' decision variables and profits, along with system stability and complexity. The findings, elucidated through numerical analyses, reveal that the burgeoning sensitivity of users to energy conservation augments the overall shared vehicle market. The technique sharing mechanism boosts the benefit of the whole group of shared vehicle operators while diminishing the start‐up operators' revenue. In the long term, however, excessive price adjustments by SEV operators may lead to market chaos and profit erosion. Conversely, enhancing the adjustment coefficient of technological level levels by start‐up SEV2 operators may result solely in their own decision‐making becoming unmanageable. Finally, we found that both the methods of external force feedback control and parameter control are effective in restoring the chaotic market to stability.

A Proposal for a Mobility-Control Data Transfer Mechanism Based on a Block Network Utilizing End-to-End Authentication Data

Advances in communications technology have had tremendous influence on network implementation to date, and as communication devices get smaller and technologies more intelligent, a great number of solutions are emerging that converge communications with a multitude of domains. In particular, as transportation modes assisting with mobility have developed, many studies are in the pipeline on the domain of mobility. The development of mobility services has prompted the spread of car sharing, which also highlights the need for a system that controls shared vehicles. The data of such control system can be used not only for the operational management of vehicles but also the management of users in terms of user driving analysis or monitoring safe driving. In addition, it can be utilized in a variety of other applications that analyze traffic flow based on vehicle driving data, determine required vehicle maintenance intervals, or schedule vehicle maintenance in advance. However, if forged/altered by a third party, control data might pose a lot of challenges to data utilization. This study proposes a mechanism that manages control data on a blockchain to enhance the integrity of control data created in the communications process. In this paper, we propose a mechanism for applying a blockchain to the communication process between clients and servers. In the proposed mechanism, platform operators generate and provide independent identification information and identification numbers for users. The identification information and identification numbers are used to prove that the generated blocks were created by specific users. Data generated by clients create a block with a hash including user identification information alongside the user identification number. Verification of the generated block is performed on the platform vendor’s server, validating that the user identification number in the block matches the server-side user identification information and the hash of the data within the block. Thus, even when the contents of the block are shared in a public blockchain environment, user identification information is only held by the server and clients, preventing third parties from impersonating specific users to create data blocks. Furthermore, the verification process of the data includes hashes received from other nearby vehicles, preventing data tampering by the block creator.

Electronic Driving License-based for Secure Sharing Vehicles in Wireless IoT Networks

In this paper we study electronic driving license (EDL) for secure sharing of vehicles in wireless IoT networks. The process of authentication and data transmission to the server is a very challenging problem to solve. To solve this problem, we propose the use of a wireless IoT network to overcome the transmission speed from the vehicle to the server, and the use of EDL for the driver authentication process. Two devices are installed on the vehicle side and on the server side while the wireless IoT network is used to make data transmission efficient. EDL is used to authenticate drivers who rent vehicles. When the device authentication process on the vehicle will send geographic information obtained through the global positioning system (GPS) to the server. The server will verify the user, if it matches then the server will send a command to the vehicle to be used. To run the considered system, we proposed Algorithm 1 and 2 to run the vehicle device and server, respectively. Experiment result shows the proposed system has maximum accuracy in 95.5%, packet delivery ratio 90%, delay propagation less than 60 seconds. Thus, the security of the shared vehicle will be increases.

Integrated optimization of planning and operation of a shared automated electric vehicle system considering the trip selection and opportunity cost

<abstract> <p>Shared autonomous electric vehicle systems (SAEVS) combine autonomous driving technology with shared electric vehicle services to provide advantages over traditional shared vehicle systems, including autonomous vehicle relocation and rapid response to user needs. In this study, we seek to enhance the operational efficiency and profitability of SAEVS by considering trip selection and the potential opportunity cost associated with unmet user demands. An integer linear programming (ILP) model is developed using a spatio-temporal state network to optimize the system design planning (e.g., charging facility, vehicle fleet sizing and distribution) and operational decisions (e.g., vehicle operational relocation and trip selection strategy). To handle the computational complexities of this model, we propose a Lagrangian relaxation (LR) algorithm. The performance of the LR algorithm is evaluated through a case study. The results, along with a parameter sensitivity analysis, reveal several key findings: (ⅰ) Allocating vehicles to stations with concentrated early peak demand, distributing charging facilities to stations with high total demand throughout the day and implementing vehicle relocation after the early demand peak can mitigate uneven vehicle distribution; (ⅱ) Implementing trip selection enhances SAEVS profitability; (ⅲ) Increasing opportunity cost meets user demands but at the expense of reduced profit; (ⅳ) It is recommended that SAEVS be equipped with charging facilities of suitable charging power based on operational conditions.</p> </abstract>

Elastic Gateway SoC design: A HW-centric architecture for inline In-Vehicle Network processing

The concepts of future mobility such as autonomous, connected, electric and shared vehicles are bringing a huge revolution to the automotive sector. We are seeing technologies typical from data centers fully embedded into vehicles, shifting from a mechanical-centric product, to an electronics-centric one. All the sensors and actuators embedded in vehicles need to exchange data in real time, in a safe and reliable way. As a result, the field of in-vehicle network (IVN) processing is currently an active research area. In previous work, we derived the requirements of future vehicle network processors and analyzed the state of the art of network processing platforms. From our study we concluded that there is currently no solution available capable of fulfilling all the requirements with the right level of performance. Now, in this work, we evaluate the novel Elastic Gateway (eGW) architecture which aims at fulfilling this gap, advancing towards future Gateway System/Network on Chip (SoC/NoC) solutions. Elastic Gateway SoC concept aims at synthesizing a scalable and future proof architecture embracing all new and already established functions and features demanded in a zonal gateway controller for the new era of mobility. It is composed of a set of configurable IP cores that allow for a full HW-based datapath implementation targeting good enough Quality of Service (QoS) and the minimum possible latency. We provide details of the internal architecture and how the different technologies required in future IVNs are integrated in eGW. With this, we are able to show how eGW meets the requirements of future network processing devices, enabling thus the current revolution.

Real-time vehicle relocation and staff rebalancing problem for electric and shared vehicle systems

ABSTRACT This study addresses the challenging real-time vehicle relocation and staff rebalancing (RT-VR&SR) problem in electric carsharing services. The complexity arises from ad-hoc demand, charging requirements of electric vehicles (EVs), and staff scheduling constraints. The problem aims to maximize the profit of carsharing operators by determining strategies for vehicle relocation, vehicle charging, and staff rebalancing in real-time. It considers the uncertainty of demand and the practical nonlinear charging profile of EVs. We formulate this problem as a Markov Decision Process (MDP), and propose an efficient concurrent-scheduler-based policy. Numerical experiments are conducted to demonstrate the effectiveness of the proposed policy and methodology. The results show that the proposed policy significantly improves service level and profitability compared to a benchmark policy. It is also found that ignoring staff rebalancing in decision making can lead to overestimation of service level and profitability. In conclusion, this study presents a real-time solution for vehicle relocation and staff rebalancing in one-way electric carsharing services. The proposed policy and methodology improve performance and highlight the importance of considering staff rebalancing in decision making.

Consistent routing for local same-day delivery via micro-hubs

An increasing number of local shops offer same-day delivery in order to compete with the online giants. However, the distribution of parcels from individual shops to customers reduces the rare consolidation opportunities in the last mile even further. Thus, shops start collaborating on urban same-day delivery by using shared vehicles and micro-depots for consolidated transportation of parcels. At this, many stakeholders (storekeepers, drivers, and customers) need to be coordinated. Consistent routes between micro-hubs simplify the distribution process and increase reliability for all stakeholders involved. The shared vehicles thus conduct consistent daily routes between micro-hubs in the city, serving as transshipment and consolidation centres. This allows stores to bring orders to the next micro-hub, where the parcel is picked up by a vehicle and delivered to the micro-hub closest to its destination—if it is feasible with respect to the vehicle’s consistent daily schedule. Creating effective schedules is therefore very important. The difficulty of finding an effective consistent route is amplified by the daily uncertainty in order placements. We model the problem as a two-stage stochastic program. While the first stage determines the vehicle schedules, the second stage optimises the flow of realised orders. The goal is to satisfy as many orders per day as possible with the shared vehicles. We propose a time-expanded network formulation of the problem which is solved to optimality using commercial MIP-software. We assess our model against a non-consistent upper bound and a practically-inspired heuristic to evaluate the cost of consistency and the consolidation of goods. We analyse the performance of our method for a variety of instance settings. We observe that collaborative delivery via micro-hubs is worthwhile for delivery time promises of two hours or more. Noticeably, for these service promises, the costs of consistency are surprisingly low.

Efficient and privacy-preserving multi-agent systems for smart city carpooling with k-regret queries and differential privacy

Multi-Agent Systems are characterized by the presence of multiple independent agents and find diverse applications. In the context of smart cities, MAS is employed in traffic management to enhance operational efficiency, optimize resource utilization, and improve the quality of life for residents. This research paper focuses on the design of a multi-agent intelligent scheduling system, where passengers, vehicles, and carpooling platforms serve as intelligent agents. The primary objective of passengers is to identify suitable shared vehicles based on criteria such as waiting time, budget constraints, and willingness to carpool. Vehicles, on the other hand, organize their schedules based on passenger demands and designated routes. The carpooling platform takes into account resource allocation priority and optimization problems to ensure the efficient operation of the system. To address the issue of vehicle ordering, k-regret queries are utilized, while passenger preferences provide insight into determining loss factors. To safeguard privacy, differential privacy techniques and a random response mechanism are employed when dealing with multiple passenger queries. Furthermore, a direction-preserving insertion verification method is implemented to mitigate computational complexity. The effectiveness and efficiency of the proposed approach are validated through experimentation.

E-Scooter-Related Maxillofacial Fractures: A New Emerging Epidemic During the COVID-19 Period in the Province of Rome, Lazio, Italy: A Monocentric Study Review of 843 Patients Compared With the Pre-COVID-19 Two-Year Period.

Shared vehicles, such as e-scooters and electric bicycles, could potentially accelerate the transition toward sustainable mobility. Focusing on e-scooters, the aim of this study is to show, compared with previous years when e-scooter use was significantly reduced, the increased incidence of maxillofacial bone injuries from e-scooters and the most frequent type of fractures. We conducted a monocentric observational retrospective and prospective analysis during the pandemic, from January 1, 2020, until December 31, 2022, on patients' access for maxillofacial traumas at the San Giovanni Addolorata emergency department, trauma hub center, for Lazio district. A total of 383 patients were included. Data on the causes of traumas, type of injury produced, age, gender, nationality, and helmet use were collected. Especially, we analyzed the e-scooter-related facial traumas that had gained a lot of popularity in this period due to the restriction in mobility because of Covid-19, subsequent reduced use of public transport, and the new benefits introduced by the government for e-scooters or bikes. We compared e-scooter facial trauma with all the other kinds of facial fracture etiologies during this period. In our study, the most frequent causes of trauma were assaults (32.6%), accidental falls (24.2%), and sports activities (7.8%). The percentage of trauma among road traffic injuries was almost 24% of the total; in particular, motorcycle/e-scooter traumas was 7.1%, car crashes was 5.5%, pedestrian hits was 4.2%, and bike accidents was 3.1%. Other causes detected were syncope (5.5%), accidental traumas (1.8%), and epileptic crisis (1.1%). Focusing on road traffic injury access in our emergency department, compared with those between 2017 and 2019, it emerged that e-scooter-related facial traumas in the past two years have had a remarkable rise. In fact, there was a total of 27 patients (52% male and 48% female) instead of 5 between 2017 and 2019. The average age was 29 years. The most frequent types of e-scooter-related fractures were those to the nasal bones (29.7%), followed by mandibular fractures (unifocal 7.4%, bifocal 18.5%, trifocal 7.4%, and condylar 7.4%), zygomatic-maxillo fractures (18.4%), complex fractures (7.4%), and maxilla (3.7%). Among 27 observed electric scooter riders, nobody wore a helmet. Injuries associated with the use of e-scooters are a new phenomenon and mainly affect the craniofacial region due to the dynamic nature of the trauma. Although these vehicles have become increasingly common over the years and accepted within regulatory frameworks, the traffic rules are not ready to integrate e-scooters into the transport systems due to the lack of adequate legislation, and the lack of implementation in the form of facial safety devices or safety skills training for e-scooter riders.

Pushing towards shared mobility

This paper provides a theoretical argument for preferential treatment of shared vehicles (SV) over private ones by municipal parking authorities. When all parked vehicles are treated equally, multiple equilibria may exist: (i) a “private” one, in which travellers are hesitant to switch to SV because the latter are hard to find, and (ii) a “shared” equilibrium, in which travellers use shared mobility because the city is saturated with vacant SV. The latter equilibrium, if it exists, is shown to yield higher welfare. Municipal parking discounts for SV reduce the amount of investment required for a “big push” towards the shared equilibrium, or even make it the only equilibrium.

Cycling under the influence of alcohol and other drugs: An exploratory analysis

We explore several aspects of Cycling Under the Influence (CUI) of alcohol and other drugs. CUI remains a relatively under researched topic, even though evidence suggests that it is a rising safety risk as both cycling mileage and alcohol consumption are increasing. We present the results of a quantitative survey designed to (i) assess the amplitude of the problem among Parisians and (ii) identify precursors for bicycle accident involvement and CUI practices. Our research provides evidence proving that CUI is indeed a common practice among Parisian cyclists (F(alcohol) = 46 % and F(drugs) = 10 %). Cyclists declare to be aware of related risks, but rarely adapt their drinking/cycling behavior to avoid them, even when they have previous accident involvement record. Shared vehicles’ users are more prone to CUI during night leisure outings when public transport is not available. Also, increased previous experience in cycling or in alcohol or drug consumption seems to make riders overconfident and therefore raise the probability of CUI.

Light electric vehicles: the views of users and non-users

PurposeLight electric vehicles (LEVs), such as e-bikes, e-scooters and electric two-wheelers, can potentially assist the transition to a sustainable transport system due to their low energy and spatial demands. This exploratory survey study investigated and compared the views of LEV users and interested non-users on the vehicles’ advantages in Finland, Austria, Spain and Italy among urban residents (n = 4090) to understand factors influencing their adoption. Additionally, differences between personal and shared vehicles were investigated.MethodThe survey queried respondents on the advantages of either the LEV they used most often, or the LEV they were most interested in using. Of respondents, 26% were LEV users, 37% were non-users interested in using an LEV and 37% were uninterested non-users. Factors concerning comfort, accessibility, safety, and practicality of travel were formed. The effects of respondent type (user vs. non-users), LEV type, whether the LEV was shared or personal, age, gender and country were examined with a full-factorial ANOVA for each factor and some additional variables.FindingsIn general, LEVs were regarded well for travel comfort and supporting accessibility, but less positively for safety and assisting with practical aspects of travel. LEVs were also perceived environmentally friendly. Furthermore, users perceived LEVs more positively than non-users, while age and gender only mildly influenced views. The results suggest that increased familiarity with LEVs is associated with more favourable views concerning them. Existing positive views may have led to LEV use; however, experience could have changed these views as well. LEVs are novel vehicles with recognised benefits, but low familiarity may hinder adoption. Increasing familiarity with LEVs among non-users could encourage uptake, potentially supporting modal shifts from the car to LEVs and thus assist the transition to a more sustainable transport system.

Stakeholder expectations and contributions to creating a market for automated, connected, electric and shared vehicles

An increasing number of companies develop innovative vehicle solutions to further sustainable transportation. One promising direction is the combination of automated, connected, electric and shared (ACES) vehicles. Due to the multitude of stakeholders involved in such an undertaking and their diverging interests, capabilities and roles, a shared vision is essential to foster productive collaboration. This study takes a brand development perspective and evaluates the degree to which stakeholders align regarding the ambition, potential and strategic pathway of the ACES brand. An expert survey involving 28 ACES stakeholders identifies numerous themes on which stakeholders agree, for example, the potential social and environmental benefits of ACES, but also a number where they disagree, for example, the legitimacy of different stakeholders in managing the stakeholder network or the degree to which all four technologies are necessary to create more sustainable mobility solutions. Consequently, the research proposes a shared brand understanding for ACES to help align the often conflicting expectations of different stakeholders. The key recommendation is to ask consumers and cities to play a central role in fostering stronger co-creation and cooperation within the stakeholder network. While the former group is essential to motivate technology providers to continue research efforts, the latter plays a decisive role in creating a regulatory framework that enhances the appeal of ACES in comparison to alternative modes of transport. Further research is necessary to understand the most appealing incentives (whether economic, social or moral) to leverage joint efforts in shaping the ACES brand.

Condition-based Maintenance of Brake Pads and Tires in Shared Vehicles using Cloud-based Health monitoring and prognostics.

Cloud-based prognostics and health management is a centralized method for monitoring the condition of individual shared vehicles and determining their maintenance schedules.In this study, we focused on monitoring the condition of brake pads and tires, as these crucial components require frequent and regular maintenance for safety. We developed a data acquisition system to transmit data from acoustic and vibration sensors to the cloud server. Useful and efficient features were extracted and selected from time and frequencydomains to assess the degradation of brake pads and tires. Moreover, based on feature extraction using the KruskalWallis method, we confirmed that diagnosing brake pad conditions with support vector machines (SVM) provides consistent result for classification of sevierities.. Our preliminary results suggest that cloud-based conditionmonitoring can be an effective approach to managing shared vehicles.

Toward A Traffic Metaverse With Shared Vehicle Perception

Toward A Traffic Metaverse With Shared Vehicle Perception

A multi-subgroup decision-making method for design selection based on subjective reports and objective physiological index data

Selecting an optimal product design scheme requires considering multiple criteria and engaging the wisdom of crowds. However, existing studies regarding design selection rarely considered the participation of group wisdom, and few studies considered subjective reports and physiological index data comprehensively for evaluation. This study developed a multi-subgroup decision-making method based on the participation of designers, experts, and customers. Multi-modal aggregation strategies are applied to aggregate subjective evaluations of both individuals and groups represented in probabilistic linguistic term sets (PLTSs), objective eye movement, and Electroencephalogram feature data. Specifically, a probabilistic linguistic information aggregation operator based on the Choquet integral is proposed to aggregate the values of subjective criteria with correlations, and the double normalization-based multi-aggregation method is then applied to aggregate objective criteria values, which can avoid information loss in the normalization and aggregation. Finally, the Choquet integral-based Borda operator is developed to integrate the evaluation results of multiple subgroups. An example of evaluating intelligent shared vehicle design schemes is presented to validate the proposed method.

Secure Decentralized Vehicle Sharing System Using Blockchain

Abstract: Shared vehicles provided by car-sharing systems can help address several issues in cities, such as reducing the use of personal cars. The popularity of the Internet of Things has made it easier for people to access shared cars through simple mobile operations. However, the car-sharing system has vulnerabilities in terms of security, such as sensitive user data transmitted through public channels, which could be accessed by attackers for illegal purposes. Therefore, it's crucial to establish a secure authentication protocol. In addition, the traditional centralized car-sharing system has a single point of failure, necessitating a decentralized car-sharing scheme, which was proposed in this study using blockchain technology. This model ensures data integrity and offers a decentralized vehicle-sharing service with anonymous authentication of participating entities. The proposed car-sharing system provides mutual authentication, protects against several attacks, and was analyzed for computation and communication costs. The proposed blockchain-based decentralized car-sharing scheme has several advantages over the traditional centralized model. For example, it eliminates the need for a trusted third party. the proposed blockchain-based decentralized car-sharing scheme offers a more secure and efficient approach to car-sharing, addressing several security issues associated with traditional centralized models. It ensures data integrity and provides mutual authentication while offering anonymity to participating entities, making it a promising solution for car-sharing systems in smart cities. to maintain the integrity of the system, as blockchain technology is based on a distributed ledger that allows participants to validate transactions. Additionally, the anonymity of the participating entities ensures privacy while providing security against unauthorized access to sensitive data. Moreover, the proposed scheme's security was analyzed using several methods, such as informal analysis, AVISPA simulation, and BAN logic evaluation, to ensure the system's resilience to various attacks.

Multi-objective Optimization in a “Specified Driver’s Origin and Destination” Ridesharing System

<div>Ridesharing is a shared vehicle service with the potential to meet the growing travel demand and shortage in transportation infrastructure capacity. Ridesharing services reduce the number of vehicles and reduce traffic congestion and emissions while providing mobility services to the same number of people with no additional transportation infrastructure investment. One of the significant challenges in implementing ridesharing services is matching drivers and riders. Conflicts between matching objectives in satisfying the interests of diverse stakeholders influence ridesharing efficiency in a transportation system. This study investigates the conflicts between two ridesharing matching objectives (i.e., minimization of system-wide trip time [TT] and minimization of system-wide vehicle miles traveled [VMT]) by applying a multi-objective optimization technique. The results indicate that an acceptable performance of a ridesharing system in terms of TT and VMT can be achieved by optimizing a ridesharing system for conflicting objectives. A trade-off analysis was performed to evaluate the compromise needed between two conflicting objectives in satisfying diverse stakeholders’ interest in a ridesharing system.</div>

Charging scheduling and energy management for mobile chargers in a grid-interactive transportation system

Mobile charging refers to the mobility-on-demand battery packages that can provide flexible charging services and regulation capacities in a grid-interactive transportation system, especially for ridesharing fleets. In this study, we use real-world data to understand the impact of mobile charging in ridesharing operations, and propose a data-driven optimization framework to identify optimal integration scenarios for mobile chargers in urban transportation systems. A mixed-integer linear program is developed to determine how many mobile chargers are required to satisfy the charging demands of shared vehicles, and when and how much to store or discharge energy to the microgrid or to other shared vehicles vs. the time-of-use charging prices regimes during a day. The objective is to minimize the daily operating cost of mobile chargers. In the proposed optimization framework, we first analyze real-world datasets that include information on trips and charging demands of fleets sharing more than one thousand shared vehicles. We then investigate a microgrid power profile that consists of base load analysis and solar photovoltaic generation forecasting. Lastly, we implement our framework in a real-world case study to evaluate model performance. The results show that our approach can reduce the total costs by about 21 % compared to a non-scheduling greedy policy, and thus help stabilize the power profile by vehicle-to-grid implementation.

PSO-DE-Based Regional Scheduling Method for Shared Vehicles

PSO-DE-Based Regional Scheduling Method for Shared Vehicles