Demand-capacity coordination method in autonomous public transportation

As an emerging technology for sustainable, safe, energy-efficient, and smooth traffic flow, autonomous public transport (APT) has been widely studied in recent years. However, the influence of conventional public transport (CPT) on behavioural intentions toward APT is largely overlooked. While APT is in its nascent phase, users’ choices may be shaped by their perceptions and attitudes toward CPT. Therefore, identifying these perceptions and examining their effect on behavioural intention is crucial. In this study, the Unified Theory of Acceptance and Use of Technology (UTAUT) is integrated with the satisfaction-loyalty model to analyze the key factors influencing behavioural intentions toward APT. To obtain more precise findings, this study examined public transport by type, including rubber-tired systems, urban rail, and bus rapid transit, rather than as a single mode, unlike many previous studies. A survey (n = 1271) was employed to validate the theoretical model among CPT users in Istanbul. The results indicate that loyalty to CPT significantly influences behavioural intention toward APT. Moreover, users of different CPT types have distinct priorities influencing their intention to use APT. While users of rubber-tired systems prioritize effort expectancy, social influence and facilitating conditions, users of urban rail systems consider social influence, trust and loyalty to CPT to be decisive factors. Furthermore, users of bus rapid transit systems consider performance expectancy, effort expectancy, trust, and loyalty to CPT as key factors influencing their behavioural intention. The findings are expected to enrich theoretical research on behavioural intention toward APT and guide future integration and transition between CPT and APT.

Technology of autonomous vehicles (AVs) is getting mature and many AVs will\nappear on the roads in the near future. AVs become connected with the support\nof various vehicular communication technologies and they possess high degree of\ncontrol to respond to instantaneous situations cooperatively with high\nefficiency and flexibility. In this paper, we propose a new public\ntransportation system based on AVs. It manages a fleet of AVs to accommodate\ntransportation requests, offering point-to-point services with ride sharing. We\nfocus on the two major problems of the system: scheduling and admission\ncontrol. The former is to configure the most economical schedules and routes\nfor the AVs to satisfy the admissible requests while the latter is to determine\nthe set of admissible requests among all requests to produce maximum profit.\nThe scheduling problem is formulated as a mixed-integer linear program and the\nadmission control problem is cast as a bilevel optimization, which embeds the\nscheduling problem as the major constraint. By utilizing the analytical\nproperties of the problem, we develop an effective genetic-algorithm-based\nmethod to tackle the admission control problem. We validate the performance of\nthe algorithm with real-world transportation service data.\n

Connected vehicle (CV) and autonomous vehicle (AV) technologies are rapidly advancing. Traffic control for future hurricane evacuation can be radically different compared to the current approaches in use. Extensive modeling research and limited field deployments have demonstrated the benefits of CV, AV technologies in achieving higher mobility, safety, and environmentally friendly solutions. One area that has not been explored in prior research is the benefits these technologies may offer to the emergency evacuation performance. Specifically, evacuation traffic control is one area where CV and AV technologies can have a transformative effect. At-grade intersections and grade-separated interchanges on evacuation routes are susceptible to congestion due to the increased demand competing for road usage. Traffic control methods that efficiently route traffic at intersections and interchanges also enhance the overall evacuation performance. This paper proposes an autonomous reservation-based intersection control (AReBIC) system for evacuation traffic control. The AReBIC system receives and processes reservation requests from approaching vehicles in real-time and routes them free of conflict. The results of a case study of Hampton Roads, Virginia, showed that the AReBIC system outperformed the existing traffic control practice in terms of mobility and safety. The average speeds increased by 29% and total delays reduced by 88% when intersection control was changed to the AReBIC system. The number of crossing conflicts decreased by 88% and lane change conflicts decreased by 47%.

The integration of autonomous vehicles (AVs) into public transportation systems has the potential to transform urban mobility by enhancing efficiency, accessibility, and sustainability. As cities continue to expand, traditional transit systems face challenges such as traffic congestion, high operational costs, and limited coverage. AVs, with their ability to optimize routes, reduce human error, and operate continuously, offer a promising solution to improve public transit networks. The adoption of AV technology in public transportation can redefine mobility patterns, particularly by bridging first- and last-mile connectivity gaps, enhancing commuter convenience, and improving mobility for elderly and disabled passengers. Unlike conventional transit modes, autonomous buses, shuttles, and taxis can dynamically adjust routes based on real-time data, reducing travel time and increasing overall system efficiency. Additionally, AVs can function seamlessly with multi-modal transport networks, integrating with metro, rail, and bus services to create a more cohesive and accessible urban transit system. Beyond improving passenger experience, AVs offer significant economic and environmental benefits. Their reduced dependence on human drivers leads to lower labor costs, while advanced energy-efficient systems contribute to lower fuel consumption and carbon emissions. Autonomous public transit solutions also help alleviate traffic congestion by minimizing unnecessary stops and optimizing roadway usage through vehicle-to-infrastructure (V2I) and vehicle-to vehicle (V2V) communication. However, the transition to a fully autonomous public transport system is not without challenges. Cities and governments must address issues such as infrastructure readiness, regulatory frameworks, liability concerns, cyber security risks, and public acceptance to ensure a smooth and secure transition. By analyzing real-world case studies and pilot projects, this chapter provides insights into how different cities worldwide are integrating AVs into their transit systems. Several pilot programs have demonstrated the feasibility of self driving shuttle services, particularly in urban areas with high commuter demand and limited transit accessibility. Furthermore, technological advancements in artificial intelligence (AI), machine learning, and sensor-based navigation continue to refine AV capabilities, making them increasingly viable for large-scale deployment in public transportation. This chapter also explores future trends, policy recommendations, and best practices that can accelerate AV adoption in public transport. Governments, urban planners, and transportation authorities must collaborate to design regulatory policies that encourage innovation while ensuring passenger safety and data security. Investment in smart infrastructure, including intelligent traffic management systems and dedicated AV lanes, will be crucial for optimizing AV operations in public transit. Ultimately, the successful integration of AVs into public transportation can lead to a more efficient, inclusive, and sustainable urban mobility ecosystem. With the right combination of technological innovation, policy support, and public engagement, AVs have the potential to redefine how people commute in the cities of the future, offering safe, affordable, and environmentally friendly solutions.

Nowadays, scientific developments in the vehicle and infrastructure automation sectors are developing steadily to benefit end users in ways like reducing traffic congestion, enhancing safety, facilitating stress-free travel, reducing fuel costs, and enabling smart parking. Autonomous vehicles sometimes known as self-driving cars, can entirely replace conventional automobiles to accomplish safe and reliable intelligent transportation systems (ITS). Autonomous vehicles have improved sensing capabilities and can drive on roads that would be difficult for humans. Software, technology, and people, together with their interactions, are the building blocks of Autonomous vehicles. Even though Autonomous vehicles have been studied extensively, many issues have yet to be fixed. One of the biggest obstacles to developing Autonomous vehicles is improving their ability to communicate with other vehicles and pedestrians. Second, it's unclear whether society will benefit or suffer from people's tendency to place an excessive amount of faith in Autonomous vehicles and assume that they will never malfunction. Capabilities analysis is essential to making sure autonomous vehicles are safe and widely accepted. The proposed review outlines the key benefits, drawbacks, and difficulties of autonomous vehicle technology and provides a detailed analysis of the different autonomous vehicle mechanisms. Further, the developed review intends to formulate future prospects by examining the advantages and disadvantages of autonomous driving technology to encourage the development of innovative autonomous vehicle technologies to prevent human error and increase road safety and security.

Preparing drivers for the future: Evaluating the effects of training on drivers’ performance in an autonomous vehicle landscape

New road transportation systems solutions create significant changes in existing automotive manufacturing industry products and technologies, from design to use. The conveniences within the framework of new approaches brought by autonomous vehicle technologies primarily make individuals transition from driver duty to passenger and high-comfort alternative travel technologies. Therefore, the research: defining the path followed by the autonomous vehicle technologies, which lead to the development of the said new life model and automotive products within the future fiction, in the stages of designing new concept vehicles in practice or measuring the effect on the processes constitute important values for the future prediction of this sector. In addition, the research has focused on the effects of interdisciplinary studies at the automotive concept design stages, which are at the beginning of today’s lean and new product development process, where innovation goals or technologies emerge with more concrete needs. New autonomous vehicle technologies and the main purpose of revealing the interdisciplinary studies created by new disciplines in the current automotive concept design stages make significant contributions to the optimization of the lean product development process and value creation. For this reason, the automotive manufacturing industry, which is on the eve of a major transformation with the said new autonomous vehicle technologies; determining the needs or sustainable position in the flow of digital perception and orientation systems; determining value creation criteria related to the functioning of automotive concept design processes or new acceptance criteria through one-on-one interviews in the field; constitutes the focus of the research. The research has examined the new interdisciplinary studies and effects of new autonomous vehicle technologies in the automotive concept design phase, which is the first step of lean product development, with local and global automotive industry company comparisons in operation. Therefore, the differences and similarities between the concept design stages of global automotive companies that are both co-developers of new autonomous vehicle technologies and manufacturing automotive products and local automotive manufacturing companies that only assemble them determine the future competitive structuring of the industry.

As autonomous vehicle (AV) technology progresses, a substantial amount of AV simulation work has studied potential future outcomes that could occur given different assumptions, scopes and technologies. As a revolutionary technology, AVs could have significant impacts on urban economic, environmental and social systems. In many cases, the research is directed towards decisionmakers: transportation authorities, policymakers and fleet operators. However, due to the complexity and uncertainty of AV adoption in interconnected urban systems such as transportation and land use, it is difficult for policymakers to understand the overlapping policy suggestions and results across the many simulation studies. In this paper, we summarise the suggested policies in AV simulation research from 170 studies published during 2016–2024 and provide context for the policies being suggested. Specifically, the key question we try to answer is: what are the recommended AV policies based on simulation studies? Many simulation results have shown increased vehicle miles/kilometers travelled (VMT/VKT) due to induced demand, empty vehicle repositioning, or cruising instead of parking. In response, we found common policy recommendations such as congestion pricing, subsidising car-sharing and ride-pooling, increasing parking costs, investing in public transportation and restricting AV demand as ways to address the increase in VMT/VKT. We also identified common policy bundles, or joint recommendations, such as congestion pricing with increased parking costs. Finally, we compare and contrast simulation policy suggestions with a few qualitative AV policy studies, pointing out key research gaps for the future and possible mixed-methods opportunities.

Human acceptance of autonomous vehicles: Research status and prospects

Prelims

Different perspectives discuss autonomous vehicle (AV) as predicted future transportation that includes design, engineering, economics, computer science, social, economic, legislation, and ethical aspects. On the other hand, AV technology offers new problems such as new engineering aspects, social and ethical problems, and presents in the form of an idealized decision-making problem. There are many benefits to AV vehicles, which are at the forefront of technology development. However, the level of cybersecurity provided by this technology is poorly understood. Cyber-attacks against AV can have severe implications for safety, privacy, manufacturers' reputation, and overall perception. In this research, we examine public opinion regarding the implications and challenges that might face AV technology in the United Arab Emirates (UAE). We claim that the successful adoption of AV in future transport systems will be achieved by reasonable risk management approaches that deal with different potential threats of cybersecurity. This survey produced usable responses from 204 participants. The significant result was that the respondents had not previously heard of vehicle-related technology; however, most had a positive first opinion on technology. Around 85% of participants felt that the expected benefits were likely to occur. They expressed a high level of concern regarding security and performance issues. Respondents stated that safety is the most crucial aspect of driverless vehicles. Mostly, it stated that personal communication devices should integrate with the AV's internet connection. The primary outcomes are that the population feels positive about AV and have optimistic expectations regarding its benefits. While maintaining some concerns, most of the people are willing to drive the AV.

Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach

Problem definition: Autonomous vehicles (AVs) are predicted to enter the consumer market in less than a decade. There is currently no consensus on whether their presence will have a positive impact on users and society. The skeptics of automation foresee increased congestion, whereas the advocates envision smoother traffic with shorter travel times. We study the automation controversy and advise policymakers on how and when to promote AVs. Academic/practical relevance: The AV technology is advancing rapidly and there is a need to study its impact on social welfare and the likelihood of its adoption by the public. Methodology: We use supply-demand theory to find the equilibrium number of trips for autonomous and regular households. We develop a simulation model of peer-to-peer AV sharing. We compare the socially optimal level of automation with the selfish adoption patterns where households independently choose their vehicle type. Results: We establish that the optimal social welfare is influenced by: (i) the network connectivity, that is, the ability of the infrastructure to serve AVs, (ii) the additional comfort provided by AVs that allows passengers to engage in other productive activities instead of driving, and (iii) the AV sharing patterns that reduce ownership costs, but create empty vehicle trips that increase congestion. Managerial implications: We investigate the impact of AVs in a case study of Toronto and show that partial automation maximizes social welfare. We show that the comfort of AVs may add traffic that compromises social welfare. Moreover, although traffic increases with automation, travel times may decrease because of significant improvements in traffic flow caused by AV connectivity in the network.

As autonomous vehicles (AVs) revolutionize the global transportation landscape, their implications for emerging economies like Malaysia remain a subject of significant interest. This study delves into the multifaceted world of AV technology, focusing on Malaysia’s unique transportation challenges and opportunities. Through interviews with key stakeholders and experts, the research uncovers valuable insights into AV technology’s awareness, regulatory landscape, integration hurdles, potential benefits, and inclusivity impact in the Malaysian context. The study finds that while AVs hold the promise of improved road safety, reduced traffic congestion, and enhanced environmental sustainability, addressing challenges related to regulation, infrastructure, and public acceptance is imperative for successful integration. Additionally, AV technology has the potential to significantly enhance inclusivity in transportation, benefiting individuals with disabilities. The study underscores the need for holistic policy and infrastructure development to leverage the benefits of AV technology and pave the way for a sustainable and inclusive transportation future in Malaysia.

The invention of autonomous vehicles (AVs) is a new frontier for the twenty-first century. Thousands of people die, and millions of people get injured on roads due to traffic accidents each year. An overwhelming majority of these accidents result from various human errors. AVs promise to reduce the number of traffic accidents significantly will save fuel and decrease greenhouse gases due to needless idling and provide increased mobility to people with disabilities and seniors. This Chapter identifies the societal, environmental, and economic benefits that AV technology brings. Moreover, AV technology brings new risks that the public is worried about, such as safety, liability, and economic impacts. This Chapter describes in detail the benefits and risks of AV technology and identifies related legal problems to answer the question of "how we can safely introduce AV technology into our society."