Journal articles: 'Autonomous Mobility on Demand'

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Salazar, Mauro, Nicolas Lanzetti, Federico Rossi, Maximilian Schiffer, and Marco Pavone. "Intermodal Autonomous Mobility-on-Demand." IEEE Transactions on Intelligent Transportation Systems 21, no. 9 (September 2020): 3946–60. http://dx.doi.org/10.1109/tits.2019.2950720.

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Azevedo, Carlos Lima, Katarzyna Marczuk, Sebastián Raveau, Harold Soh, Muhammad Adnan, Kakali Basak, Harish Loganathan, et al. "Microsimulation of Demand and Supply of Autonomous Mobility On Demand." Transportation Research Record: Journal of the Transportation Research Board 2564, no. 1 (January 2016): 21–30. http://dx.doi.org/10.3141/2564-03.

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Wen, Jian, Neema Nassir, and Jinhua Zhao. "Value of demand information in autonomous mobility-on-demand systems." Transportation Research Part A: Policy and Practice 121 (March 2019): 346–59. http://dx.doi.org/10.1016/j.tra.2019.01.018.

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Javanshour, Farid, Hussein Dia, and Gordon Duncan. "Exploring the performance of autonomous mobility on-demand systems under demand uncertainty." Transportmetrica A: Transport Science 15, no. 2 (October 3, 2018): 698–721. http://dx.doi.org/10.1080/23249935.2018.1528485.

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Dia, Hussein, and Farid Javanshour. "Autonomous Shared Mobility-On-Demand: Melbourne Pilot Simulation Study." Transportation Research Procedia 22 (2017): 285–96. http://dx.doi.org/10.1016/j.trpro.2017.03.035.

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Hao, Mingyang, Yanyan Li, and Toshiyuki Yamamoto. "Public Preferences and Willingness to Pay for Shared Autonomous Vehicles Services in Nagoya, Japan." Smart Cities 2, no. 2 (June 11, 2019): 230–44. http://dx.doi.org/10.3390/smartcities2020015.

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Shared autonomous vehicle systems are anticipated to offer cleaner, safer, and cheaper mobility services when autonomous vehicles are finally implemented on the roads. The evaluation of people’s intentions regarding shared autonomous vehicle services appears to be critical prior to the promotion of this emerging mobility on demand approach. Based on a stated preference survey in Nagoya, Japan, the preference for shared autonomous vehicle services as well as willingness to pay for these services were examined among 1036 respondents in order to understand the relationship between people’s socioeconomic characteristics and their preferred shared autonomous vehicle services. For this purpose, k-modes clustering technique was selected and six clusters were obtained. Six groups with respect to different interests on shared autonomous vehicle services were clustered. The result of correlation analysis and discussion of willingness to pay on services provided insightful results for the future shared autonomous vehicle services. This study not only aids in revealing the demands of customer different clusters, but also states the prospective needs of users for stakeholders from research, policymaker and industry field, who are preparing to work on promoting shared autonomous vehicle systems, and subsequently, develops an optimum transportation mode by considering both demand and services as a whole.

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Hogeveen, Peter, Maarten Steinbuch, Geert Verbong, and Auke Hoekstra. "Quantifying the Fleet Composition at Full Adoption of Shared Autonomous Electric Vehicles: An Agent-based Approach." Open Transportation Journal 15, no. 1 (May 17, 2021): 47–60. http://dx.doi.org/10.2174/1874447802115010047.

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Aims: Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Background: Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. Objective: To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. Methods: An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. Results: The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Conclusion: Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.

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Schnieder, Maren, Chris Hinde, and Andrew West. "Land Efficient Mobility: Evaluation of Autonomous Last Mile Delivery Concepts in London." International Journal of Environmental Research and Public Health 19, no. 16 (August 18, 2022): 10290. http://dx.doi.org/10.3390/ijerph191610290.

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Land efficient last mile delivery concepts are key to reducing the traffic in cities and to minimising its environmental impact. This paper proposes a decision support method that evaluates the autonomous delivery concept and applies it to one year’s worth of real parcel delivery data in London. Deliveries to modular and fixed lockers with autonomous delivery vans and road-based autonomous lockers (RAL) and sidewalk autonomous delivery robots (SADRs) have been simulated. Various types of autonomous delivery van fleets, depot locations, customer modes of transport, parcel demand levels, parcel locker network densities and adjustment frequencies of modular lockers are considered. A routing and scheduling algorithm is used to optimise delivery tours and vehicle choice. The optimisation algorithm finds both the optimal number of collection and delivery points (CDPs) and the delivery concept (e.g., modular lockers, sidewalk autonomous delivery robot) depending on the customer mode chosen. The results show that modular lockers which are adjusted weekly are the best option for the current or higher parcel demand levels and road-autonomous parcel lockers (RAL-R) are the best option at the lowest parcel demand level.

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Noh, Seungwon, Chang-Gyun Roh, Byeongsup Moon, and Jung-Ah Ha. "Defining Evaluation Criteria for Real-time Demand Response Autonomous Mobility." Journal of the Korea Academia-Industrial cooperation Society 23, no. 1 (January 31, 2022): 871–79. http://dx.doi.org/10.5762/kais.2022.23.1.871.

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Marczuk, Katarzyna A., Harold S. H. Soh, Carlos M. L. Azevedo, Der-Horng Lee, and Emilio Frazzoli. "Simulation Framework for Rebalancing of Autonomous Mobility on Demand Systems." MATEC Web of Conferences 81 (2016): 01005. http://dx.doi.org/10.1051/matecconf/20168101005.

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Hidaka, Ken, and Takahiro Shiga. "Forecasting Travel Demand for New Mobility Services Employing Autonomous Vehicles." Transportation Research Procedia 34 (2018): 139–46. http://dx.doi.org/10.1016/j.trpro.2018.11.025.

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Szigeti, Szilárd, Csaba Csiszár, and Dávid Földes. "Information Management of Demand-responsive Mobility Service Based on Autonomous Vehicles." Procedia Engineering 187 (2017): 483–91. http://dx.doi.org/10.1016/j.proeng.2017.04.404.

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Dai, Jiajie, Qianyu Zhu, Nan Jiang, and Wuyang Wang. "Rebalancing Autonomous Vehicles using Deep Reinforcement Learning." International Journal of Circuits, Systems and Signal Processing 16 (January 15, 2022): 646–52. http://dx.doi.org/10.46300/9106.2022.16.80.

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The shared autonomous mobility-on-demand (AMoD) system is a promising business model in the coming future which provides a more efficient and affordable urban travel mode. However, to maintain the efficient operation of AMoD and address the demand and supply mismatching, a good rebalancing strategy is required. This paper proposes a reinforcement learning-based rebalancing strategy to minimize passengers’ waiting in a shared AMoD system. The state is defined as the nearby supply and demand information of a vehicle. The action is defined as moving to a nearby area with eight different directions or staying idle. A 4.6 4.4 km2 region in Cambridge, Massachusetts, is used as the case study. We trained and tested the rebalancing strategy in two different demand patterns: random and first-mile. Results show the proposed method can reduce passenger’s waiting time by 7% for random demand patterns and 10% for first-mile demand patterns.

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Grahle, A., Y. W. Song, K. Brüske, B. Bender, and D. Göhlich. "AUTONOMOUS SHUTTLES FOR URBAN MOBILITY ON DEMAND APPLICATIONS – ECOSYSTEM DEPENDENT REQUIREMENT ELICITATION." Proceedings of the Design Society: DESIGN Conference 1 (May 2020): 887–96. http://dx.doi.org/10.1017/dsd.2020.100.

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AbstractFuture transport will change drastically with the introduction of automated vehicles. Here, Autonomous Mobility on Demand (AMoD) will play a major role, requiring a radical change of vehicle design, with many different conceivable concepts. This technology shift holds high potentials and high risks. Uncertainties about future usage profiles, operator and customer requirements have to be dealt with. An approach to elicit initial requirements for future vehicle concepts considering the entire ecosystem is introduced. The applicability is shown for a specific urban mobility scenario.

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König, Alexandra, Christina Wirth, and Jan Grippenkoven. "Generation Y’s Information Needs Concerning Sharing Rides in Autonomous Mobility on Demand Systems." Sustainability 13, no. 14 (July 20, 2021): 8095. http://dx.doi.org/10.3390/su13148095.

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Empirical studies show that autonomous vehicles can contribute to sustainability goals when rides are shared. However, sharing rides with strangers in shared autonomous mobility-on-demand systems (SAMODSs) might impede the adoption of these systems. The present study addresses the research question whether a comprehensive information provision about fellow passengers could increase acceptability of the shared rides in SAMODSs. A discrete choice experiment (N = 154) assessed the potential of different levels of information on fellow passengers: (1) no information, (2) name, (3) picture, (4) rating, (5) combination of name, picture and rating. The results show that the overall compensation demands for sharing a ride was a reduction of approximately 25% of the nonshared reference price. The provision of detailed information about fellow travelers proved beneficial for reducing the compensation demands of travelers while the provision of a name only resulted in higher compensation demands. A significant effect of the fellow passengers’ gender indicated that male gender information was related to a higher refusal rate than female gender information. This was particularly relevant when only names were presented. The study provides first empirical insights into the psychological factors concerning the emerging trend of shared mobility.

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Golbabaei, Fahimeh, Tan Yigitcanlar, Alexander Paz, and Jonathan Bunker. "Understanding Autonomous Shuttle Adoption Intention: Predictive Power of Pre-Trial Perceptions and Attitudes." Sensors 22, no. 23 (November 26, 2022): 9193. http://dx.doi.org/10.3390/s22239193.

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The capability of ‘demand-responsive transport’, particularly in autonomous shared form, to better facilitate road-based mobility is considered a significant advantage because improved mobility leads to enhanced quality of life and wellbeing. A central point in implementing a demand-responsive transit system in a new area is adapting the operational concept to the respective structural and socioeconomic conditions. This requires an extensive analysis of the users’ needs. There is presently limited understanding of public perceptions and attitudes toward the adoption of autonomous demand-responsive transport. To address this gap, a theory-based conceptual framework is proposed to provide detailed empirical insights into the public’s adoption intention of ‘autonomous shuttle buses’ as a form of autonomous demand-responsive transport. South East Queensland, Australia, was selected as the testbed. In this case study, relationships between perceptions, attitudes, and usage intention were examined by employing a partial least squares structural equation modeling method. The results support the basic technology acceptance model casual relationships that correspond with previous studies. Although the direct effects of perceived relative advantages and perceived service quality on usage intention are not significant, they could still affect usage intention indirectly through the attitude factor. Conversely, perceived risks are shown to have no association with perceived usefulness but can negatively impact travelers’ attitudes and usage intention toward autonomous shuttle buses. The research findings provide implications to assist policymakers, transport planners, and engineers in their policy decisions and system plans as well as achieving higher public acknowledgment and wider uptake of autonomous demand-responsive transport technology solutions.

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Medina-Tapia, Marcos, and Francesc Robusté. "Implementation of Connected and Autonomous Vehicles in Cities Could Have Neutral Effects on the Total Travel Time Costs: Modeling and Analysis for a Circular City." Sustainability 11, no. 2 (January 17, 2019): 482. http://dx.doi.org/10.3390/su11020482.

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Autonomous vehicles promise to revolutionize the automobile market, although their implementation could take several decades in which both types of cars will coexist on the streets. We formulate a model for a circular city based on continuous approximations, considering demand surfaces over the city. Numerical results from our model predict direct and indirect effects of connected and autonomous vehicles. Direct effects will be positive for our cities: (a) less street supply is needed to accommodate the traffic; (b) congestion levels decrease: travel costs may decrease by 30%. Some indirect effects will counterbalance these positive effects: (c) a decrease of 20% in the value of travel time can reduce the total cost by a third; (d) induced demand could be as high as 50%, bringing equivalent total costs in the future scenario; (e) the vehicle-kilometers traveled could also affect the future scenario; and (f) increases in city size and urban sprawl. As a conclusion, the implementation of autonomous vehicles could be neutral for the cities regarding travel time costs. City planning agencies still have to promote complementary modes such as active mobility (walking and bicycle), transit (public transportation), and shared mobility (shared autonomous vehicles and mobility as a service).

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Gurumurthy, Krishna Murthy, Kara M. Kockelman, and Natalia Zuniga-Garcia. "First-Mile-Last-Mile Collector-Distributor System using Shared Autonomous Mobility." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 10 (July 28, 2020): 638–47. http://dx.doi.org/10.1177/0361198120936267.

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High costs of owning fully-automated or autonomous vehicles (AVs) will fuel the demand for shared mobility, with zero driver costs. Although sharing sounds good for the transport system, congestion can easily rise without adequate policy measures. Many or all public transit lines will continue to exist, and carefully-designed policies can be implemented to make good use of fixed public assets, like commuter- and light-rail lines. In this study, a shared AV (SAV) fleet is analyzed as a potential solution to the first-mile-last-mile (FMLM) problem for access to and from public transit. Essentially, SAVs are analyzed as collector-distributor systems for these mass-movers and compared with a door-to-door (D2D) service. Results from an agent-based simulation of Austin, Texas, show that SAVs have the potential to help solve FMLM transit problems when fare benefits are provided to transit users. Restricting SAV use for FMLM trips increases transit coverage, lowers average access and egress walking distance, and shifts demand away from park-and-ride and long walk trips. When SAVs are available for both D2D use and FMLM trips, high SAV fares help maintain transit demand, without which the transit demand may decrease significantly, affecting the transit supply and the overall system reliability. Policy makers and planners should be wary of this shift away from transit and may be able to increase transit usage using policies tested in this study.

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Meneses-Cime, Karina, Bilin Aksun-Guvenc, and Levent Guvenc. "Optimization of On-Demand Shared Autonomous Vehicle Deployments Utilizing Reinforcement Learning." Sensors 22, no. 21 (October 29, 2022): 8317. http://dx.doi.org/10.3390/s22218317.

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Ride-hailed shared autonomous vehicles (SAV) have emerged recently as an economically feasible way of introducing autonomous driving technologies while serving the mobility needs of under-served communities. There has also been corresponding research work on optimization of the operation of these SAVs. However, the current state-of-the-art research in this area treats very simple networks, neglecting the effect of a realistic other traffic representation, and is not useful for planning deployments of SAV service. In contrast, this paper utilizes a recent autonomous shuttle deployment site in Columbus, Ohio, as a basis for mobility studies and the optimization of SAV fleet deployment. Furthermore, this paper creates an SAV dispatcher based on reinforcement learning (RL) to minimize passenger wait time and to maximize the number of passengers served. The created taxi-dispatcher is then simulated in a realistic scenario while avoiding generalization or over-fitting to the area. It is found that an RL-aided taxi dispatcher algorithm can greatly improve the performance of a deployment of SAVs by increasing the overall number of trips completed and passengers served while decreasing the wait time for passengers.

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Lu, Ying, Yanchang Liang, Zhaohao Ding, Qiuwei Wu, Tao Ding, and Wei-Jen Lee. "Deep Reinforcement Learning-Based Charging Pricing for Autonomous Mobility-on-Demand System." IEEE Transactions on Smart Grid 13, no. 2 (March 2022): 1412–26. http://dx.doi.org/10.1109/tsg.2021.3131804.

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Turan, Berkay, Ramtin Pedarsani, and Mahnoosh Alizadeh. "Dynamic pricing and fleet management for electric autonomous mobility on demand systems." Transportation Research Part C: Emerging Technologies 121 (December 2020): 102829. http://dx.doi.org/10.1016/j.trc.2020.102829.

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Alexander, Serena, Asha Weinstein Agrawal, and Benjamin Clark. "Local Climate Action Planning as a Tool to Harness Greenhouse Gas Emissions Mitigation and the Equity Potential of Autonomous Vehicles and On-Demand Mobility." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 3 (October 30, 2021): 521–34. http://dx.doi.org/10.1177/03611981211052541.

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This paper focuses on how cities can use climate action plans (CAPs) to ensure that on-demand mobility and autonomous vehicles (AVs) help reduce, rather than increase, greenhouse gas (GHG) emissions and inequitable impacts from the transportation system. We employed a three-pronged research strategy involving: (1) an analysis of the current literature on on-demand mobility and AVs; (2) a systematic content analysis of 23 CAPs and general plans (GPs) developed by municipalities in California; and (3) a comparison of findings from the literature and content analysis of plans to identify opportunities for GHG emissions reduction and mobility equity. Findings indicate that policy and planning discussions should consider the synergies between AVs and on-demand mobility as two closely related emerging mobility trends, as well as the key factors (e.g., vehicle electrification, fuel efficiency, use and ownership, access, and distribution, etc.) that determine whether the deployment of AVs would help reduce GHG emissions from transportation. Additionally, AVs and on-demand mobility have the potential to contribute to a more equitable transportation system by improving independence and quality of life for individuals with disabilities and the elderly, enhancing access to transit, and helping alleviate the geographic gap in public transportation services. Although many municipal CAPs and GPs in California have adopted several strategies and programs relevant to AVs and on-demand mobility, several untapped opportunities exist to harness the GHG emissions reduction and social benefits potential of AVs and on-demand mobility.

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Gandomani, Roxana, Moataz Mohamed, Amir Amiri, and Saiedeh Razavi. "System Optimization of Shared Mobility in Suburban Contexts." Sustainability 14, no. 2 (January 13, 2022): 876. http://dx.doi.org/10.3390/su14020876.

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Shared mobility is a viable choice to improve the connectivity of lower-density neighbourhoods or suburbs that lack high-frequency public transportation services. In addition, its integration with new forms of powertrain and autonomous technologies can achieve more sustainable and efficient transportation. This study compares four shared-mobility technologies in suburban areas: the Internal Combustion Engine, Battery Electric, and two Autonomous Electric Vehicle scenarios, for various passenger capacities ranging from three to fifteen. The study aims to provide policymakers, transportation planners, and transit providers with insights into the potential costs and benefits as well as system configurations of shared mobility in a suburban context. A vehicle routing problem with time windows was applied using the J-Horizon software to optimize the costs of serving existing intra-community demand. The results indicate a similar fleet composition for Battery Electric and Autonomous Electric fleets. Furthermore, the resulting fleet for all four technologies is dominated by larger vehicle capacities. Due to the large share of driver cost in the total cost, the savings using a fleet of Autonomous Electric Vehicles are predicted to be 68% and 70%, respectively, compared to Internal Combustion and Battery Electric fleets.

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Iglesias, Ramon, Federico Rossi, Rick Zhang, and Marco Pavone. "A BCMP network approach to modeling and controlling autonomous mobility-on-demand systems." International Journal of Robotics Research 38, no. 2-3 (June 28, 2018): 357–74. http://dx.doi.org/10.1177/0278364918780335.

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In this paper we present a queuing network approach to the problem of routing and rebalancing a fleet of self-driving vehicles providing on-demand mobility within a capacitated road network. We refer to such systems as autonomous mobility-on-demand (AMoD) systems. We first cast an AMoD system into a closed, multi-class Baskett–Chandy–Muntz–Palacios (BCMP) queuing network model capable of capturing the passenger arrival process, traffic, the state-of-charge of electric vehicles, and the availability of vehicles at the stations. Second, we propose a scalable method for the synthesis of routing and charging policies, with performance guarantees in the limit of large fleet sizes. Third, we explore the applicability of our theoretical results on a case study of Manhattan. Collectively, this paper provides a unifying framework for the analysis and control of AMoD systems, which provides a large set of modeling options (e.g. the inclusion of road capacities and charging constraints), and subsumes earlier Jackson and network flow models.

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Belakaria, Syrine, Mustafa Ammous, Sameh Sorour, and Ahmed Abdel-Rahim. "Fog-Based Multi-Class Dispatching and Charging for Autonomous Electric Mobility On-Demand." IEEE Transactions on Intelligent Transportation Systems 21, no. 2 (February 2020): 762–76. http://dx.doi.org/10.1109/tits.2019.2897121.

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Haj Salah, Imen, Vasu Dev Mukku, Malte Kania, Tom Assmann, and Hartmut Zadek. "Implications of the Relocation Type and Frequency for Shared Autonomous Bike Service: Comparison between the Inner and Complete City Scenarios for Magdeburg as a Case Study." Sustainability 14, no. 10 (May 11, 2022): 5798. http://dx.doi.org/10.3390/su14105798.

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Finding a sustainable mobility solution for the future is one of the most competitive challenges in the logistics and transportation sector nowadays. Researchers, universities, and companies are working intensively to provide novel mobility options that can be environmentally friendly and sustainable. While autonomous car-sharing services have been introduced as a very promising solution, an innovative alternative is arising using self-driving bikes. Shared autonomous cargo bike fleets are likely to increase the livability and sustainability of the city as the use of cargo bikes in an on-demand mobility service can replace the use of cars for short-distance trips and enhance connectivity to public transportation. However, more research is still needed to develop this new concept. To address this research gap, this paper examines the on-demand shared-use autonomous bikes service (OSABS) from a fleet management perspective. In fact, such a system requires good management strategies in order to ensure its efficiency. Through an agent-based simulation of a case study in Magdeburg, we investigate various parameters that can influence the performance and the service quality of OSABS such as the rebalancing frequency and the relocation type. Tests were performed for two different operational areas: the inner city and the complete city of Magdeburg. We conclude with different management insights for an optimized functioning of the system.

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Wang, Dengzhong, Tongyu Sun, Anzheng Xie, and Zhao Cheng. "Simulation Study on the Coupling Relationship between Traffic Network Model and Traffic Mobility under the Background of Autonomous Driving." Sustainability 15, no. 2 (January 13, 2023): 1535. http://dx.doi.org/10.3390/su15021535.

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Autonomous driving technology will bring revolutionary changes to the development of future cities and transportation. In order to study the impact of autonomous driving on urban transportation networks, this paper first summarizes the development status of autonomous driving technology, and then three space–traffic network coupling models are proposed based on the differences of speed and space, which are the traditional difference type, scale variation type, and slow-guided type. On this basis, a new 4 * 4 km grid city model is constructed. Based on the MATSim multi-agent simulation method, the traffic parameters of the three models are studied. The results show that under the same traffic demand, the service scale and level of the three traffic networks are significantly different. The optimal service level of the traditional differential type is 2.15 times the efficiency of the slow-guided type. Under the same demand and road network mode, the travel speed of the autonomous driving mode is 1.7–2.8 times that of the traditional mode. Under the same lane area ratio, the travel speed of traditional driving is much smaller than that of autonomous driving, which is about 2.6–3.6 times greater than the former. The research conclusion has certain reference significance for formulating urban spatial development strategies and policies under autonomous driving environments and for promoting the sustainable development of urban transportation.

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Haj Salah, Imen, Vasu Dev Mukku, Malte Kania, and Tom Assmann. "Towards Sustainable Liveable City: Management Operations of Shared Autonomous Cargo-Bike Fleets." Future Transportation 1, no. 3 (October 2, 2021): 505–32. http://dx.doi.org/10.3390/futuretransp1030027.

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Finding a sustainable mobility solution for the future is one of the most competitive challenges in the logistics and mobility sector at present. Policymakers, researchers, and companies are working intensively to provide novel options that are environmentally friendly and sustainable. While autonomous car-sharing services have been introduced as a very promising solution, an innovative alternative is arising: the use of self-driving bikes. Shared autonomous cargo-bike fleets are likely to increase the livability and sustainability of the city, as the use of cargo-bikes in an on-demand mobility service can replace the use of cars for short-distance trips and enhance connectivity to public transportation. However, more research is needed to develop this new concept. In this paper, we investigate different rebalancing strategies for an on-demand, shared-use, self-driving cargo-bikes service (OSABS). We simulate a case study of the system in the inner city of Magdeburg using AnyLogic. The simulation model allows us to evaluate the impact of rebalancing on service level, idle mileage, and energy consumption. We conclude that the best proactive rebalancing strategy for our case study is to relocate bikes only between neighboring regions. We also acknowledge the importance of bike relocation to improve service efficiency and reduce fleet size.

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Nemoto, Eliane Horschutz, Inna Morozova, Ralf Wörner, Ines Jaroudi, Guy Fournier, and Adrian Boos. "Substituting individual mobility by mobility on demand using autonomous vehicles - a sustainable assessment simulation of Berlin and Stuttgart." International Journal of Automotive Technology and Management 20, no. 4 (2020): 369. http://dx.doi.org/10.1504/ijatm.2020.10034385.

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Fournier, Guy, Adrian Boos, Ralf Wörner, Ines Jaroudi, Inna Morozova, and Eliane Horschutz Nemoto. "Substituting individual mobility by mobility on demand using autonomous vehicles - a sustainable assessment simulation of Berlin and Stuttgart." International Journal of Automotive Technology and Management 20, no. 4 (2020): 369. http://dx.doi.org/10.1504/ijatm.2020.112029.

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Fu, Mengying, Raoul Rothfeld, and Constantinos Antoniou. "Exploring Preferences for Transportation Modes in an Urban Air Mobility Environment: Munich Case Study." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 10 (May 21, 2019): 427–42. http://dx.doi.org/10.1177/0361198119843858.

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Urban Air Mobility (UAM) is a recent mobility concept with the potential to reduce travel time and change travel patterns. When evaluating the introduction of UAM, understanding the potential users’ choice behavior regarding current available urban transportation modes and autonomous transportation services is essential to demand estimation. This preliminary research intends to gain insight into the travel behavior impacts of autonomous transportation modes, especially UAM, by deriving measures for transportation service attributes and identifying characteristics of potential users who might adopt autonomous transportation services, particularly the services of UAM. Thus, a stated preference questionnaire was designed and distributed in Munich metropolitan region. A main mode choice multinomial logit model and several sub-models, based on market segmentation, were estimated regarding four transportation alternatives: private car, public transportation, autonomous taxi, and autonomous flying taxi. The results indicate that travel time, travel cost, and safety may be critical determinants in autonomous transportation mode adoption. The potential consumers may be willing to pay more for using autonomous transportation modes, especially the service of UAM. Among different market segments, younger individuals, as well as older individuals with high household income, are more likely to adopt UAM. In addition, during the market entry stage, potential travelers may favor UAM particularly for performing non-commuting trips.

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Signorile, Pierdomenico, Vincenzo Larosa, and Ada Spiru. "Mobility as a service: a new model for sustainable mobility in tourism." Worldwide Hospitality and Tourism Themes 10, no. 2 (April 9, 2018): 185–200. http://dx.doi.org/10.1108/whatt-12-2017-0083.

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Purpose Developing sustainable mobility can add value to the travel and tourism experience in alpine areas and can become a challenge for destinations in terms of interests, goals, skills and values involving both public and private subjects. Mobility as a Service (MaaS) is a new model for delivering sustainable transport services that in recent experiences seem to be an alternative to the use of owned cars by allowing the personalized use of a bundle of public and private transport means. This paper aims to identify the positive aspects in the two main Alpine regions affected by tourism demand coming mainly from Lombardy by implementing a mobility model inspired by Maas in the Lombardy capital. Design/methodology/approach The tourism demand of the Autonomous Province of Trento and the Aosta Valley Region is thus analyzed using descriptive statistics on tourist flows and mobility characteristics. Findings Technology and propensity to change are the determining factors to move from traditional to innovative mobility systems. Originality/value This work, by considering the recent studies on MaaS models, limited to sustainable urban mobility models, extends the MaaS approach to the key concepts of “sustainable mobility” and “sustainable tourism” by analyzing the tourist flow, which from Lombardy invest the main alpine regions.

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Tarkowski, Maciej, and Krystian Puzdrakiewicz. "Connectivity Benefits of Small Zero-Emission Autonomous Ferries in Urban Mobility—Case of the Coastal City of Gdańsk (Poland)." Sustainability 13, no. 23 (November 28, 2021): 13183. http://dx.doi.org/10.3390/su132313183.

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An increase in energy-efficient transportation is one way that cities try to mitigate climate change. In coastal cities, public water transit is also undergoing transitions. A small zero-emission autonomous ferry seems to be a cutting-edge technology in this field. This study aims to decrease the knowledge gap in research on the impacts of autonomous passenger ferry development on urban mobility. In particular, the central theme regards the extent to which the new transport solution can help improve sustainable mobility patterns. This study explores the local spatial context of ferry development, land-use patterns, and transport network structure, and moderates the shift in urban mobility practices. Regarding land use patterns, the case of the coastal city of Gdańsk has been documented in secondary qualitative and quantitative data, including in a large body of policy documents, accompanying expert opinions, and scholarly literature. This study strongly emphasises that a typical short river crossing, due to autonomous vessels, can regain a competitive position, which was partially lost due to linear routes along the river. The research identified crucial benefits of autonomous ferry shipping on urban mobility by increasing public transport network connectivity, reducing travel distance, and creating modal shifts towards foot travel and bike riding. It appears as an exciting scalable solution for cities where limited or dispersed demand prevents achievement of economies of scale, therefore diminishing the necessary expenditures.

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Belakaria, Syrine, Mustafa Ammous, Lauren Smith, Sameh Sorour, and Ahmed Abdel-Rahim. "Multi-Class Management With Sub-Class Service for Autonomous Electric Mobility On-Demand Systems." IEEE Transactions on Vehicular Technology 68, no. 7 (July 2019): 7155–59. http://dx.doi.org/10.1109/tvt.2019.2920104.

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Dolins, Sigma, Yale Z. Wong, and John D. Nelson. "The ‘Sharing Trap’: A Case Study of Societal and Stakeholder Readiness for On-Demand and Autonomous Public Transport in New South Wales, Australia." Sustainability 13, no. 17 (August 25, 2021): 9574. http://dx.doi.org/10.3390/su13179574.

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Focus groups on shared, autonomous vehicles (SAVs) in New South Wales expressed “sharing anxiety”—an intense concern about the prospect of sharing their mobility journey with strangers, without a driver or authority figure present. This presents a significant barrier to the acceptance of SAVs, particularly autonomous public and on-demand transport (ODT), which is a major focus for Transport for New South Wales (TfNSW). Given this potential barrier, we interviewed (N = 13) operators, academics, and regulators with TfNSW to assess their role and abilities in overcoming sharing anxiety. However, our findings revealed a relative lack of awareness from experts in the mobility industry about the existence of sharing anxiety in users, suggesting additional barriers to adoption. We make suggestions for policy considerations for stakeholders that could mitigate sharing anxiety: promoting dynamic ridepooling products in commercial services, using tax breaks as incentivization; requiring ODT services and operators in jurisdiction to use a standardized, unified interface for users (“single-app”); shared, on-demand transport services likely need longer incubation/pilot periods in order for the sharing behavior to become culturally established. We conclude with a reflection on how COVID-19 has impacted the development of shared mobility and suggest further exploration in policy implementation.

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Engesser, Valeska, Evy Rombaut, Lieselot Vanhaverbeke, and Philippe Lebeau. "Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda." Sustainability 15, no. 3 (February 3, 2023): 2774. http://dx.doi.org/10.3390/su15032774.

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The implementation of autonomous delivery solutions in last-mile logistics operations is considered promising. Autonomous delivery solutions can help in tackling urban challenges related to last-mile logistics operations. Urbanization creates higher mobility and transportation demand, which contributes to increased congestion levels, traffic, air pollution, and accident rates. Moreover, mega-trends, such as e-commerce, demand that logistics companies react to increased customer expectations in terms of delivery time and service. Concerning service, electrified autonomous delivery solutions have the potential to operate 24/7 and can help to overcome driver shortages. This paper conducts a systematic literature review. Based on the literature set, a snowballing procedure was applied. Complementary gray literature was included. This work discusses different autonomous delivery solutions such as Autonomous Delivery Robots (ADRs), Unmanned Aerial Vehicles (UAVs), two- or multi-tiered systems, and the concept of passenger and freight integration. The work presents advantages and disadvantages, enabling the comparison of solutions. Furthermore, a research agenda is provided, from which practical-managerial and theoretical implications can be derived. The research agenda can help researchers, manufacturers, businesses, and governmental institutions to prepare for the arrival and subsequent implementation of autonomous delivery services. Various implications related to energy demand, legislation, implementation strategy, training, and risk and safety are presented. The outcome of this work calls for collaboration among various stakeholders, encourages mutual learning, and hints at the importance of national and international development projects.

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Ferenc Stephen Kovacs. "Will Autonomous Vehicles address impediments to the mobility of ageing populations?" Magyar Gerontológia 12 (November 26, 2020): 6–7. http://dx.doi.org/10.47225/mg/12/kulonszam/8448.

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Background/Aims Autonomous Vehicles (AVs) have been touted as a ‘mobility panacea’ for ageing populations. The hopes invested in such technocentric solutions can be understood with reference to the spatial-temporal context of the Global Demographic Transition. The geography of ageing culminates in growing levels of social isolation of older populations in rural, regional and suburban areas. This spatial trend is superimposed on a temporal landscape of recurring economic crises, creating fiscal constraints impeding the efficacy of conventional solutions including scheduled and demand-responsive transport. To what extent can AVs respond to the mobility needs of older people at a time of fiscal crisis? Methods To address this knowledge gap, I undertook a systematic literature review with two academic colleagues from Curtin University in 2019. We reviewed the AV related papers and the wider transportation planning and gerontological research inclusive of factors known to influence the mobility of older people. The research informed a critical perspective exploring possible impacts, inclusive of risks and opportunities through the methodology of scenario analysis. Results We found the technology had the capability to address some aged mobility needs such as those resulting from declining driving ability, and might provide a framework supportive of ‘ageing in place’ solutions. Conclusions The ability to realise the full potential of this ‘socio-technical transition’ and effectively manage unintended impacts, will be informed by society’s institutional capacity inclusive of the State’s ability to implement timely interventions in mobility markets and provide an integrated approach to transport and land use planning.

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M. Azam, S.A. Hassan, O.C. Puan, S.F. Azhari, and R.U. Faiz. "Performance of Autonomous Vehicles in Mixed Traffic under different Demand Conditions." International Journal of Automotive and Mechanical Engineering 19, no. 4 (December 28, 2022): 10050–62. http://dx.doi.org/10.15282/ijame.19.4.2022.02.0776.

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Autonomous Vehicles (AVs) are considered one of the potential solutions to future urban mobility with several promised benefits regarding safety and traffic operation. Despite of expected benefits, these vehicles will take decades to have full market penetration and before that, AVs will co-exist with Conventional Vehicles (CVs), which may affect the performance of AVs owing to different driving logic than CVs. The aim of this study is to quantify the impacts of varying penetrations of AVs when introduced in mixed traffic conditions. The study employed simulation environment VISSIM to study the different scenarios based on the percentage of AVs in mixed traffic, category of AVs and varying demand levels. The findings show that at lower demand levels (1000 veh/hr and 2000 veh/hr), CVs and three categories of AVs produced similar results. However, cautious and normal AVs negatively affect traffic operations when the demand level is increased. At demand-3 (3000 veh/hr), the penetration rates of cautious AVs greater than 50% shows negative impact on performance. At demand-4 (4000 veh/hr), even a small proportion (25%) of cautious AVs can negatively affect performance, and a similar effect is observed for normal AVs with a penetration rate greater than 75%. For speed, the minimum reduction with the increase in demand is observed for aggressive AVs, followed by conventional vehicles, normal AVs and cautious AVs. It can be concluded that the aggressive AVs produced better delays, queue length, speed and conflicts than CVs, cautious AVs and normal AVs at the highest demand levels.

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Cohn, Jesse, Richard Ezike, Jeremy Martin, Kwasi Donkor, Matthew Ridgway, and Melissa Balding. "Examining the Equity Impacts of Autonomous Vehicles: A Travel Demand Model Approach." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (March 19, 2019): 23–35. http://dx.doi.org/10.1177/0361198119836971.

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As investments in autonomous vehicle (AV) technology continue to grow, agencies are beginning to consider how AVs will affect travel behavior within their jurisdictions and how to respond to this new mobility technology. Different autonomous futures could reduce, perpetuate, or exacerbate existing transportation inequities. This paper presents a regional travel demand model used to quantify how transportation outcomes may differ for disadvantaged populations in the Washington, D.C. area under a variety of future scenarios. Transportation performance measures examined included job accessibility, trip duration, trip distance, mode share, and vehicle miles traveled. The model evaluated changes in these indicators for disadvantaged and non-disadvantaged communities under scenarios when AVs were primarily single-occupancy or high-occupancy, and according to whether transit agencies responded to AVs by maintaining the status quo, removing low-performing routes, or applying AV technology to transit vehicles. Across the performance measures, the high-occupancy AV and enhanced transit scenarios provided an equity benefit, either mitigating an existing gap in outcomes between demographic groups or reducing the extent to which that gap was expanded.

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Martí, Pasqual, Jaume Jordán, Fernando De la Prieta, Holger Billhardt, and Vicente Julian. "Demand-Responsive Shared Transportation: A Self-Interested Proposal." Electronics 11, no. 1 (December 27, 2021): 78. http://dx.doi.org/10.3390/electronics11010078.

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With the world population highly increasing, efficient methods of transportation are more necessary than ever. On the other hand, the sharing economy must be explored and applied where possible, aiming to palliate the effects of human development on the environment. In this paper we explore demand-responsive shared transportation as a system with the potential to serve its users’ displacement needs while being less polluting. In contrast with previous works, we focus on a distributed proposal that allows each vehicle to retain its private information. Our work describes a partially dynamic system in which the vehicles are self-interested: they decide which users to serve according to the benefit it reports them. With our modelling, the system can be adapted to mobility platforms of autonomous drivers and even simulate the competition among different companies.

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Obaid, Mohammed, and Arpad Torok. "Macroscopic Traffic Simulation of Autonomous Vehicle Effects." Vehicles 3, no. 2 (April 29, 2021): 187–96. http://dx.doi.org/10.3390/vehicles3020012.

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The increasing worldwide demand on urban road transportation systems requires more restrictive measures and policies to reduce congestion, time delay and pollution. Autonomous vehicle mobility services, both shared and private, are possibly a good step towards a better road transportation future. This article aims to study the expected impact of private autonomous vehicles on road traffic parameters from a macroscopic level. The proposed methodology focuses on finding the different effects of different combinations of autonomous vehicle penetration and Passenger Car Units (PCU) on the chosen road traffic model. Four parameters are studied: traveled daily kilometers, daily hours, total daily delay and average network speed. The analysis improves the four parameters differently by implementing autonomous vehicles. The parameter total delay has the most significant reduction. Finally, several mathematical models are developed for the percentage of improvement for each chosen parameter.

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Lee, Sungwon, Devon Farmer, Jooyoung Kim, and Hyun Kim. "Shared Autonomous Vehicles Competing with Shared Electric Bicycles: A Stated-Preference Analysis." Sustainability 14, no. 21 (November 2, 2022): 14319. http://dx.doi.org/10.3390/su142114319.

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Understanding the factors that affect the uptake of emerging transport modes is critical for understanding if and how they will be used once they are implemented. In this study, we undertook a stated-preference analysis to understand the factors that affect the use of shared autonomous vehicles and shared personal mobility (micromobility) as competing modes on a university campus in Korea. We applied a binary logit model, which included time and cost variables as well as the perceptions of convenience (in-car congestion and availability) and safety. For autonomous vehicles, the cost- and time-related demand elasticities were estimated to be −0.45 and −0.25, respectively, while the cost elasticity for shared electric bicycles was −0.42. The elasticities of perceived convenience (availability) and safety for the shared electric bicycle system were estimated to be 0.72 and 0.29, respectively. Finally, the elasticity for perceived convenience (in-car congestion) of the shared autonomous vehicle was 0.42. Our results show that there is an innate preference for shared autonomous vehicles when these are compared to shared personal mobility, and that the effect of subjective variables (convenience and safety) on the use of emerging transport modes is as important as traditional cost and time variables.

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Hogeveen, Peter, Maarten Steinbuch, Geert Verbong, and Auke Hoekstra. "The Energy Consumption of Passenger Vehicles in a Transformed Mobility System with Autonomous, Shared and Fit-For-Purpose Electric Vehicles in the Netherlands." Open Transportation Journal 15, no. 1 (October 15, 2021): 201–9. http://dx.doi.org/10.2174/1874447802115010201.

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Aims: This article explores the tank-to-wheel energy consumption of passenger transport at full adoption of fit-for-purpose shared and autonomous electric vehicles. Background: The energy consumption of passenger transport is increasing every year. Electrification of vehicles reduces their energy consumption significantly but is not the only disruptive trend in mobility. Shared fleets and autonomous driving are also expected to have large impacts and lead to fleets with one-person fit-for-purpose vehicles. The energy consumption of passenger transport in such scenarios is rarely discussed and we have not yet seen attempts to quantify it. Objective: The objective of this study is to quantify the tank-to-wheel energy consumption of passenger transport when the vehicle fleet is comprised of shared autonomous and electric fit-for-purpose vehicles and where cheap and accessible mobility leads to significantly increased mobility demand. Methodology: The approach consists of four steps. First, describing the key characteristics of a future mobility system with fit-for-purpose shared autonomous electric vehicles. Second, estimating the vehicle miles traveled in such a scenario. Third, estimating the energy use of the fit-for-purpose vehicles. And last, multiplying the mileages and energy consumptions of the vehicles and scaling the results with the population of the Netherlands. Results: Our findings show that the daily tank-to-wheel energy consumption from Dutch passenger transport in full adoption scenarios of shared autonomous electric vehicles ranges from 700 Wh to 2200 Wh per capita. This implies a reduction of 90% to 70% compared to the current situation. Conclusion: Full adoption of shared autonomous electric vehicles could increase the vehicle-miles-travelled and thus energy use of passenger transport by 30% to 150%. Electrification of vehicles reduces energy consumption by 75%. Autonomous driving has the potential of reducing the energy consumption by up to 40% and implementing one-person fit-for-purpose vehicles by another 50% to 60%. For our case study of the Netherlands, this means that the current 600 TJ/day that is consumed by passenger vehicles will be reduced to about 50 to 150 TJ/day at full adoption of SAEVs.

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Benarbia, Taha, Kyandoghere Kyamakya, Fadi Al Machot, and Witesyavwirwa Vianney Kambale. "Modeling and Simulation of Shared Electric Automated and Connected Mobility Systems with Autonomous Repositioning: Performance Evaluation and Deployment." Sustainability 15, no. 1 (January 3, 2023): 881. http://dx.doi.org/10.3390/su15010881.

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The boom seen in artificial intelligence in recent years has led to a revolution in the automotive industry. Numerous automakers around the world, such as Tesla, Toyota, Honda, and BMW, have achieved giant strides in the development of e-autonomous vehicles. Consequently, shared electric automated vehicle mobility (SEAVM) systems, which are a crucial part of future innovative transportation solutions, have attracted significant attention from the research community, particularly from a design perspective. However, the flexibility of shared automated mobility systems may lead to a self-operating technology issue (unequal distribution of vehicles), since users in these systems can pick up and drop off electric vehicles wherever they like. With this in mind, this paper addressed the issues of autonomous repositioning and the assignment of shared autonomous electric vehicle systems to balance a system’s network and fulfill its demand. Modeling, analysis and assessment of the system’s performance were carried out using stochastic Petri nets formalism, which included determining the average time areas were empty/congested and the number of unserved consumers, and estimating the redistribution service launch moment. Furthermore, many simulation scenarios were analyzed, including repositioning and without repositioning scenarios, in order to evaluate the efficiency of the model and to show the potential of using Petri nets as a probabilistic formalism approach for the modeling of e-automated mobility systems.

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Beirigo, Breno A., Rudy R. Negenborn, Javier Alonso-Mora, and Frederik Schulte. "A business class for autonomous mobility-on-demand: Modeling service quality contracts in dynamic ridesharing systems." Transportation Research Part C: Emerging Technologies 136 (March 2022): 103520. http://dx.doi.org/10.1016/j.trc.2021.103520.

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Kocsis, Bence, Gábor Vida, Zsolt Szalay, and György Ágoston. "Novel Approaches to Evaluate the Ability of Vehicles for Secured Transportation." Periodica Polytechnica Transportation Engineering 49, no. 1 (October 24, 2019): 80–88. http://dx.doi.org/10.3311/pptr.13785.

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The assurance of process safety plays an important role in the field of information technology. Securing the information has become one of the biggest challenges in the present day. Whenever we think about the protected systems the first thing that comes to our mind can be malicious interventions which are increasing immensely day by day. Nowadays we live the world of huge automotive developments with the appearance of the demand for autonomous vehicles. On the other hand, technological developments also provide a lot of advantages for the society. The benefits of autonomous cars include reduced mobility costs, increased safety, increased mobility, significant reduction of traffic collisions. However, it cannot be forgotten that the extension of cyberspace affects the transportation increasingly. Accordingly, cars are produced with high level of connectivity and automation. Therefore, the risks arriving from the cyberspace can now endanger the safe and secured transportation. These tendencies shall motivate manufacturers and developers to permanently improve the ability of vehicles to protect themselves and their passengers.

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Klöppel, Manfred, Felix Römer, Michael Wittmann, Bijan Hatam, Thomas Herrmann, Lee Sim, Jun Lim, et al. "Scube—Concept and Implementation of a Self-balancing, Autonomous Mobility Device for Personal Transport." World Electric Vehicle Journal 9, no. 4 (December 5, 2018): 48. http://dx.doi.org/10.3390/wevj9040048.

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Public transportation (PT) systems suffer from disutility compared to private transportation due to the inability to provide passengers with a door-to-door service, referred to as the first/last mile problem. Personal mobility devices (PMDs) are thought to improve PT service quality by closing this first/last mile gap. However, current PMDs are generally driven manually by the rider and require a learning phase for safe vehicle operation. Additionally, most PMDs require a standing riding position and are not easily accessible to elderly people or persons with disabilities. In this paper, the concept of an autonomously operating mobility device is introduced. The visionary concept is designed as an on-demand transportation service which transports people for short to medium distances and increases the accessibility to public transport. The device is envisioned to be operated as a larger fleet and does not belong to an individual person. The vehicle features an electric powertrain and a one-axle self-balancing design with a small footprint. It provides one seat for a passenger and a tilt mechanism that is designed to improve the ride comfort and safety at horizontal curves. An affordable 3D-camera system is used for autonomous localization and navigation. For the evaluation and demonstration of the concept, a functional prototype is implemented.

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Fayyaz, Maryam, Esther González-González, and Soledad Nogués. "Autonomous Mobility: A Potential Opportunity to Reclaim Public Spaces for People." Sustainability 14, no. 3 (January 28, 2022): 1568. http://dx.doi.org/10.3390/su14031568.

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The advent of autonomous vehicles (AVs) has the potential to drastically change society and the way we understand, plan and design cities and regions, just as automobiles did a century ago. In the current context of climate change, sustainable urban environments based on active mobility (walking and cycling), urban proximity and green spaces, are increasingly in demand, leading to the emergence of new interventions and urban models. Although these trends may be affected by the arrival of AVs, most decision-makers and planners still do not address these issues in their current planning. This is because of the confusion associated with the diversity of impacts of AVs, but also by the lack of design recommendations and planning tools. To shed light on these aspects, this paper reviews the relationship between mobility and urban public space, the impacts of AVs on urban space and design proposals and strategies aimed at configuring driverless cities, with special focus on street design. The results of the review show that the implementation of AVs can be a great opportunity to liberate urban space and reclaim it for people, in line with new urban models such as the superblocks (Barcelona), the 15-minute city (Paris), or tactical urbanism interventions against COVID-19. However, it may also entail risks such as a reduction in active mobility or public transport use. The magnitude and direction of these impacts will depend on crucial decisions that need to be taken now, such as encouraging shared used over ownership, and establishing citizen-centred urban planning and design objectives and strategies to make AV deployment the most beneficial for all.

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Campisi, Tiziana, Alessandro Severino, Muhammad Ahmad Al-Rashid, and Giovanni Pau. "The Development of the Smart Cities in the Connected and Autonomous Vehicles (CAVs) Era: From Mobility Patterns to Scaling in Cities." Infrastructures 6, no. 7 (July 8, 2021): 100. http://dx.doi.org/10.3390/infrastructures6070100.

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Smart cities aim to integrate technological development with different functions/components such as mobility, management of energy, natural resources, water, and the waste cycle, air quality, land use, service network, construction, but also the economy, social participation, increased employment, and citizen safety. It includes a series of coordinated and integrated social, environmental and economic interventions to enhance human capital, reduce environmental impacts and solve ecological emergencies. The holistic approach is particular to smart cities, including several mobility aspects in the main European classifications. In particular, the development of smart cities depends on several factors related to transport supply (i.e., mobility service, infrastructure details, ICT) and demand (socio-demographic aspects), and the size of the city. This paper provides an overview of the development of smart cities by defining a methodology that allows the identification of criteria for determining the optimisation of urban mobility with a particular interest in the development of future autonomous mobility. The analysis of current literature on the concept of smart cities and new mobility technologies made it possible to analyse the compatibility between them and possible criticalities. The definition of criteria lays the groundwork for future research steps focused on the application of multicriteria analysis.

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Van den bergh, Ona, Simon Weekx, Cedric De Cauwer, and Lieselot Vanhaverbeke. "Locating Charging Infrastructure for Shared Autonomous Electric Vehicles and for Vehicle-to-Grid Strategy: A Systematic Review and Research Agenda from an Energy and Mobility Perspective." World Electric Vehicle Journal 14, no. 3 (February 23, 2023): 56. http://dx.doi.org/10.3390/wevj14030056.

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A shared autonomous electric vehicle (SAEV) fleet and the vehicle-to-grid (V2G) strategy both have great potential to reduce GHG emissions. As these concepts have complementary value, they are even more promising combined. However, to the best of our knowledge, no research has yet been conducted on locating charging infrastructure for SAEVs with V2G feasibility. For this construction, the challenge lies in the fact that both mobility demand (mainly for SAEVs) and energy (for any installation of charging infrastructure) have a major influence on this problem. To find the optimal charging infrastructure (CI) allocation for SAEVs with V2G operations, both mobility requirements and grid constraints must be considered. In this paper, we find that optimization models are the most frequently used method to solve the CI allocation problem. We conduct separate examinations of the V2G and SAEVs location optimization models that have been formulated in the literature, for which objective functions are used, and which constraints are considered (with respect to mobility and the electric grid). We find that SAEV and V2G models have overlapping elements, but remain disjunct in their respective perspectives. CI allocation for SAEVs mainly takes mobility into account, but tends to ignore grid constraints or impacts. On the other hand, CI allocation for V2G focuses on the distribution network and the grid, forgetting about mobility demand. To take advantage of the SAEV-V2G potential, future research should combine mobility and grid aspects to find the optimal CI locations for SAEVs with V2G feasibility.

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Journal articles on the topic 'Autonomous Mobility on Demand'

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