Automated Vehicles, On-Demand Mobility, and Environmental Impacts

A survey on 3D object detection in real time for autonomous driving

This survey reviews advances in 3D object detection approaches for autonomous driving. A brief introduction to 2D object detection is first discussed and drawbacks of the existing methodologies are identified for highly dynamic environments. Subsequently, this paper reviews the state-of-the-art 3D object detection techniques that utilizes monocular and stereo vision for reliable detection in urban settings. Based on depth inference basis, learning schemes, and internal representation, this work presents a method taxonomy of three classes: model-based and geometrically constrained approaches, end-to-end learning methodologies, and hybrid methods. There is highlighted segment for current trend of multi-view detectors as end-to-end methods due to their boosted robustness. Detectors from the last two kinds were specially selected to exploit the autonomous driving context in terms of geometry, scene content and instances distribution. To prove the effectiveness of each method, 3D object detection datasets for autonomous vehicles are described with their unique features, e. g., varying weather conditions, multi-modality, multi camera perspective and their respective metrics associated to different difficulty categories. In addition, we included multi-modal visual datasets, i. e., V2X that may tackle the problems of single-view occlusion. Finally, the current research trends in object detection are summarized, followed by a discussion on possible scope for future research in this domain.

Environmental impacts of shared mobility: a systematic literature review of life-cycle assessments focusing on car sharing, carpooling, bikesharing, scooters and moped sharing

Evidence about the environmental impacts of shared mobility is fragmented and scattered. In this article a systematic literature review is presented. The review focuses on assessments that use Life-Cycle Assessment to quantify the environmental impacts of car sharing, carpooling, bikesharing, and scooter/moped sharing. The results of these assessments were analyzed, as well as the factors that influence these impacts. Business-to-consumer car sharing, peer-to-peer car sharing, carpooling, bikesharing, and scooter/moped sharing can all cause gains and losses in terms of changing the environmental impacts of passenger transportation. The findings presented here refute unconditional claims that shared mobility delivers environmental benefits. Factors that influence changes in environmental impacts from passenger transportation from shared mobility include travel behaviour, the design of shared mobility modes, and how such schemes are implemented, as well as the local context. Local governments and shared mobility organisations can benefit from the analysis presented here by deepening their understanding of these factors and considering the life-cycle phase where the greatest impacts are caused.

Training for the safe activation of Automated Vehicles matters: Revealing the benefits of online training to creating glaringly better mental models and behaviour

Automated Vehicle (AV) systems are expected to reduce the frequency and severity of on-road collisions. Unless drivers have an appropriate mental model for the capabilities and limitations of the automation, they may not activate the automation safely or appropriately on the road, potentially leading to a collision. As such, a training package (L4DTP) was developed to improve drivers' decisions and behaviour when activating an AV system and this was evaluated in a between-subjects simulator experiment. Drivers received no training (NT, control group), read an owner's manual (OM, experimental group 1: current training provision) or underwent the L4DTP (experimental group 2: new training programme). All drivers then experienced five scenarios in a driving simulator where they encountered road conditions which were safe and unsafe for activation. Their activation decisions, behaviour, trust in automation, workload and mental models were measured. This experiment found that drivers who read the OM or underwent the L4DTP made better activation decisions and showed better activation behaviour compared to drivers who received NT. Additionally, drivers who underwent the L4DTP found it easier, less demanding and felt under less time pressure when making their decisions, had to expend less effort to reach the same activation performance and had more appropriate and comprehensive mental models for when the automation can be activated compared to drivers who read the OM. This L4DTP can make roads safer by reducing collisions linked to poor activation decisions and behaviour. Therefore, there is the potential for a real benefit for society if this training programme is adopted into mandatory AV driver training.

Barriers to the sustainable adoption of autonomous vehicles in developing countries: A multi-criteria decision-making approach

The acceptance of AI-based intelligent transportation systems requires addressing the existing barriers and the adoption of macro-decisions and policies by policymakers and governments. This study evaluates the potential barriers to the adoption of Autonomous Vehicles (AVs) in developing countries by considering the sustainability dimensions. The barriers are identified by conducting a comprehensive literature review and studying the academic experts' opinions in related industries. By identifying the main barriers to the sustainable adoption of AVs, a synthesized approach of the Rough Best-Worst Method (RBWM) and Interval-Rough Multi-Attributive Border Approximation Area Comparison (IR-MABAC) is utilized for weighting and evaluating each barrier in this context. According to the results of this study, the "inflation rate", "lack of internet connection quality", and "learning challenges and difficulties to use the AVs" are the top challenges and barriers to the AV adoption which need to be considered by policymakers. As the main contribution of this research, we provide efficient insights on a macro policy scale for decision-makers with respect to the main barriers to the implementation of AVs technology. From the AVs literature and to the best of our knowledge, this is the first study of its kind that considers the barriers to the AV technology implementation through the sustainability concept.

Could Technology and Intelligent Transport Systems Help Improve Mobility in an Emerging Country? Challenges, Opportunities, Gaps and Other Evidence from the Caribbean

Apart from constituting a topic of high relevance for transport planners and policymakers, support technologies for traffic have the potential to bring significant benefits to mobility. In addition, there are groups of “high potential” users, such as young adults, who constitute an essential part of the current market. Notwithstanding, and especially in low and middle-income countries (LMICs), their knowledge and acceptance remain understudied. This study aimed to assess the appraisal of intelligent transport systems (ITS) and other technological developments applicable to mobility among Dominican young adults. Methods: In this study, we used the data gathered from 1414 Dominicans aged between 18 and 40, responding to the National Survey on Mobility in 2018 and 2019. Results: Overall, and although there is a relatively high acceptance, attributed value, and attitudinal predisposition towards both intelligent transportation systems and various support technologies applicable to mobility, the actual usage rates remain considerably low, and this is probably exacerbated by the low and middle-income status of the country. Conclusions: The findings of this study suggest the need to strengthen information and communication flows over emerging mobility-related technologies and develop further awareness of the potential benefits of technological developments for everyday transport dynamics.

Potential Analysis for a New Vehicle Class in the Use Case of Ride-Pooling: How New Model Developments Could Satisfy Customers and Mobility Makers

Due to changes in mobility and the emergence of new services, it is becoming necessary to establish new vehicle classes between conventional buses and privately owned vehicles. New mobility scenarios need concrete specifications to develop the most user-centered shuttle buses. As a result, we are looking for the requirements and needs of operators and customers. Initially, we want to determine the status quo, as there is no preliminary work in this regard. During the course of extensive literature research, expert interviews, and follow-up workshops, the respective solution space was highlighted and narrowed down. Services such as ride-pooling require adapted vehicle concepts to ensure optimal implementation of their offer. Due to its optimized processes, the automotive industry depends on producing vehicles in a certain quantity and manner. Faster changes and extensive experiments are not possible with the current production approach. Purpose-built vehicle concepts can make mobility services more attractive to customers while facilitating business operations. For instance, potential improvements can be identified in the seating concept.

Analysis of the Influential Factors towards Adoption of Car-Sharing: A Case Study of a Megacity in a Developing Country

Motorization has been escalating rapidly in developing countries, posing a severe challenge to sustainable urban mobility. In the past two decades, car-sharing has emerged as one of the most prominent alternatives to facilitate smart mobility solutions, thereby helping to reduce air pollution and traffic congestion. However, before its full-scale deployment, it is essential to understand the consumers’ acceptance of car-sharing systems. This study aimed to assess the public perception and acceptance of the car-sharing system through a stated preference (SP) questionnaire in the city of Lahore, Pakistan. The collected data contained detailed information on various service attributes of three alternative modes (car-sharing, private car, and taxi) in addition to the sociodemographic attributes of respondents. Data analysis and interpretation were performed using econometric models such as the Multinomial Logit Model (MNL), the Nested Logit Model (NL), and the Random Parameter Logit Model (RPL). Study findings revealed that several generic attributes such as travel time, travel cost, waiting time, and privacy were predicated as significant influential factors towards the adoption of car-sharing. Sociodemographic attributes, including age, education, monthly income, the individuals who had driver’s licenses, and frequency of travel in a week, were also found to be significant. The findings of the current study can provide valuable insights to stakeholders and transportation planners in formulating effective policies for car-sharing.

Evaluating Low-Carbon Transportation Technologies When Demand Responds to Price

The carbon intensity (CI) of travel is commonly used to evaluate transportation technologies. However, when travel demand is sensitive to price, CI alone does not fully capture the emissions impact of a technology. Here, we develop a metric to account for both CI and the demand response to price (DR) in technology evaluation, for use by distributed decision-makers in industry and government, who are becoming increasingly involved in climate change mitigation as the costs of lower-carbon technologies fall. We apply this adjusted carbon intensity (ACI) to evaluate ethanol-fueled, hybrid, and battery electric vehicles individually and against policy targets. We find that all of these technologies can be used to help meet a 2030 greenhouse gas emissions reduction target of up to 40% below 2005 levels and that decarbonized battery electric vehicles can meet a 2050 target of 80%, even when evaluated using the ACI instead of CI. Using the CI alone could lead to a substantial overshoot of emissions targets especially in markets with significant DR, including in rapidly growing economies with latent travel demand. The ACI can be used to adjust decarbonization transition plans to mitigate this risk. For example, in examining several transportation technologies, we find that accelerating low-carbon technology transitions by roughly 5-10 years would mitigate the risk associated with DR estimates. One particularly robust strategy is to remove carbon from fuels through faster decarbonization of electricity and vehicle electrification.

Dashboard Layout Effects on Drivers' Searching Performance and Heart Rate: Experimental Investigation and Prediction

Carsharing scale has been increasing rapidly with sharing economy. However, many users are reluctant to rent cars any longer due to the low-quality of interactive experience and usability, especially in terms of the dashboard design. This challenge should be urgently addressed in order to maintain the sustainable development of car-sharing industry and its environmental benefits. This study aims to investigate the relationship between users' driving activities (e.g., searching time, reading time, eye movement, heart rate) and dashboard layout. This study was conducted based on the experimental investigation among 58 respondents who were required to complete driving tasks in four types of cars with different dashboard layouts. Afterwards, a prediction model was developed to predict users heart rate (HR) based on the long short-term memory model, and logistic models were used to examine the relationship between the occurrence probability of minimum HR and dashboard reading. The results showed that the system usability of a dashboard was related to the drivers' eye movement characteristics including fixation duration, fixation times and pupil diameter. Most indicators had significant effects (p < 0.05) on the system usability score of corresponding dashboard. The long short-term memory model network (RMSE = 1.105, MAE = 0.009) was capable of predicting heart rate (HR) that happened in the process of instrument reading, which presented a periodic pattern rather than a continuous increase or decrease. It reflected that the network could better fit the non-linear and time-sequential laws of HR data. Furthermore, the probability of the lowest heart rate occurrence during the interaction with four dashboards was influenced by the average searching time, reading time and reading accuracy that were related to a specific layout. Overall, this study provided a theoretical reference for uncovering users' adaptive behaviors with the central control screen and for the optimal choice of a suitable dashboard layout in interface design.

Shared Automated Electric Vehicle Prospects for Low Carbon Road Transportation in British Columbia, Canada

This study explores the long-term energy use implications of electrification, automation and sharing of road vehicles in British Columbia, Canada. Energy use is first analyzed for the years 1990–2016 for forward forecasting, and hypothetical scenarios ranging from conservative to disruptive, incorporating various effects of road vehicle electrification, sharing and automation, as well as influences of other technology disruptions, such as online shopping and e-learning are presented and used to project the road transportation energy use in B.C. to 2060. Transportation energy use projections are compared to those of the Canadian Energy Regulator (CER). When considering only the effect of vehicle electrification, the scenarios show higher energy savings compared to CER’s scenarios. The combined impact of vehicle electrification and automation leads to decreased energy use to 2060 for all scenarios considered. The energy savings for all scenarios, except for the conservative one, are higher than CER’s projections. When the effects of vehicle electrification, automation and sharing are merged, all scenarios yield energy savings beyond the CER projections. Inclusion of other technology disruptions and the effects of pandemics like COVID-19 reduce transportation demand and provide further energy savings. The BAU scenario given in this study shows energy use decreases compared to 2016 of 26.3%, 49%, 62.24%, 72.1% for the years 2030, 2040, 2050, and 2060 respectively.

Parents’ Willingness to Allow Their Unaccompanied Children to Use Emerging and Future Travel Modes

This study investigated parents’ willingness to allow their unaccompanied child(ren) to use emerging and future travel modes (e.g., rideshare vehicles and automated vehicles). An online survey was completed by 631 Australian respondents (M = 39.2 years, SD = 10.5 years, Male: 36.6%) who reported that they currently lived with one or more children (17 or below). Approximately one-third (37.9%) of the respondents reported a willingness to allow their child to use a rideshare vehicle alone and more than half of the respondents (57.2%) reported a willingness to allow their child to use an automated vehicle alone. Respondents who expressed willingness to allow their child to use a rideshare vehicle alone were more likely to express a willingness to use an automated vehicle alone (79.1%) compared to respondents who were unwilling to use a rideshare vehicle (43.9%), χ2(1) = 75.158, p < 0.001, Phi = 0.345. Two separate logistic regression models revealed key similarities and differences related to respondents’ willingness to allow their unaccompanied child to use both transport modes. Respondents’ willingness to allow their unaccompanied child to use a rideshare vehicle was significantly related to their previous use of a rideshare vehicle with their child, having an optimistic view of technology, annual mileage, their aberrant driving behaviours, and their desire for route-control and assurance features within the rideshare vehicle, χ2(7) = 159.594, p < 0.001. Respondents’ willingness to allow their child to use an automated vehicle alone was significantly related to awareness of automated vehicles, education level, positive views towards technology, seeing technology to be innovative, and requirements for route control features within the automated vehicle, χ2(6) = 113.325, p < 0.001. Despite the potential for emerging or future travel modes to provide additional personal transportation options, these results suggest that Australian parents are unwilling to allow their unaccompanied child to use these modes of transport. These findings will have significant implications for transport planning, particularly in growing communities where pressures on parents to transport their child(ren) to activities and events with minimal adult supervision is increasing.

Autonomous Mobility: A Potential Opportunity to Reclaim Public Spaces for People

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.

Ride-Hailing Service Adoption and Local Context in Motorcycle-Based Societies: Case Study in Hanoi, Vietnam

The ride-hailing service (RHS) has emerged as a major form of daily travel in many Southeast Asian cities where motorcycles are extensively used. This study aims to analyze the local context in motorcycle-based societies, which may affect the establishment of travelers’ choice set after the appearance of RHSs. In particular, it empirically compares three types of choice-set structures in the context of urban travel mode choice by estimating standard logit and nested logit models to test six hypotheses on the associations of RHS adoption with its determinants. Revealed preference data of 449 trips from both RHS users and non-RHS users were collected through a face-to-face interview-based questionnaire survey in Hanoi, Vietnam, in December 2020. The results of model estimations revealed: (1) a substitutional effect for two-wheelers but not for four-wheelers, (2) a significant positive influence of car ownership on car RHS adoption but not on motorcycle RHS adoption, (3) significantly high sensitivity to travel time of motorcycle RHS but not of car RHS, (4) a significant negative effect of traffic congestion on car RHS adoption but an insignificant one on motorcycle RHS adoption, and (5) a significant positive association of an individual’s experience in using a smartphone with car RHSs but insignificant association with motorcycle RHSs. Our findings suggest that transportation policies of RHS motorcycles should be different from those of RHS cars because of the heterogeneity in travel behaviors of RHS users between them. They also indicate that the transition from motorcycles to cars as well as the difference in service availability among different types of RHSs should be incorporated into the development of transportation policies in Southeast Asian cities.

Exploring the implications of autonomous vehicles: a comprehensive review

Over the last few years, a large emphasis has been devoted to autonomous vehicles (AVs), as vehicle automation promises a large number of benefits such as: improving mobility and minimization of energy and emissions. Additionally, AVs represent a major tool in the fight against pandemics as autonomous vehicles can be used to transport people while maintaining isolation and sterilization. Thus, manufacturers are racing to introduce AVs as fast as possible. However, laws and regulations are not yet ready for this change and the legal sector is following the development of autonomous vehicles instead of taking the lead. This paper provides a comprehensive review of the previous studies in the transportation field that involve AVs with the aim of exploring the implications of AVs on the safety, public behaviour, land use, economy, society and environment, public health, and benefits of autonomous vehicles in fighting pandemics.

The Automation of the Taxi Industry – Taxi Drivers’ Expectations and Attitudes Towards the Future of their Work

Advoc ates of autonomous driving predict that the occupation of taxi driver could be made obsolete by shared autonomous vehicles (SAV) in the long term. Conducting interviews with German taxi drivers, we investigate how they perceive the changes caused by advancing automation for the future of their business. Our study contributes insights into how the work of taxi drivers could change given the advent of autonomous driving: While the task of driving could be taken over by SAVs for standard trips, taxi drivers are certain that other areas of their work such as providing supplementary services and assistance to passengers would constitute a limit to such forms of automation, but probably involving a shifting role for the taxi drivers, one which focuses on the sociality of the work. Our findings illustrate how taxi drivers see the future of their work, suggesting design implications for tools that take various forms of assistance into account, and demonstrating how important it is to consider taxi drivers in the co-design of future taxis and SAV services.

Industry 4.0 an empirical analysis of users’ intention in the automotive sector

Purpose

This paper aims to study the automotive 4.0 context to understand the consumers’ propensity towards high-tech automated cars. The paper analyses the antecedents that lead to the use of innovative vehicles. Theory of planned behaviour (TPB) is adopted and extended by including further constructs, such as environmental aspects and inhibitors.

Design/methodology/approach

The advent of smart technologies and the internet of things has given rise to several contributions that look at consumers’ intention towards innovation adoption in the automotive industry. Furthermore, this study rises from the growing interest that sustainable mobility achieved. Based on the previous technology acceptance models and particularly TPB, this paper develops a structured questionnaire. After a pilot survey, the final questionnaire was administered online through email and social media in the Italian context. Structural equation modelling technique has been used for analysing data and testing the conceptual model.

Findings

The number of questionnaires filled out was 310, with a sample composed of young adults, characterised by different addiction levels towards technology. The results explain the drivers that lead to accept and adopt high-tech automated vehicles. This topic is still under investigation and offers potential research opportunities, considering the evolution of the market and the consumers’ habits and needs. Future research studies in this area should focus on generalising the present findings in other countries. Moreover, once this technology starts to be adopted, other constructs could be discovered, investigated and included in the model.

Originality/value

Mobility has raised a growing interest with the fast increasing demand for sustainability and growth of innovative solutions embedded in mobility. This research explores the TPB model’s application and the relation between its constructs, environmental aspects, inhibitors and intention to adopt automated vehicles. On this strength, it is possible to identify each construct’s relevance for obtaining social consensus on the market.

Sharing Anxiety Is in the Driver’s Seat: Analyzing User Acceptance of Dynamic Ridepooling and Its Implications for Shared Autonomous Mobility

As connected, electric, and autonomous vehicle (AV) services are developed for cities, the research is conclusive that the use of these services must be shared to achieve maximum efficiency. Yet, few agencies have prioritised designing an AV system that focuses on dynamic ridepooling, and there remains a gap in the understanding of what makes people willing to share their rides. However, in 2017, the Australian transport authority Transport for New South Wales launched over a dozen trials for on-demand, shared public transport, including AVs. In this paper, we investigate the user willingness-to-share, based on experiences from one of these trials. Four focus groups (19 participants in total) were held in New South Wales with active users of either the trialled on-demand dynamic ridepooling service (Keoride) or commercial ridepooling (UberPool). Through thematic analysis of the focus group conversations, the cost, comfort, convenience, safety, community culture, and trust in authority emerged as factors that influenced the willingness-to-share. When presented with driverless scenarios, the focus group participants had significant concerns about the unknown behaviour of their co-passengers, revealing sharing anxiety as a significant barrier to the adoption of shared AVs. This paper identifies previously disregarded factors that influence the adoption of AVs and dynamic ridepooling and offers insights on how potential users’ sharing anxiety can be mitigated.

“Is Sharing Really Caring?”: The Role of Environmental Concern and Trust Reflecting Usage Intention of “Station-Based” and “Free-Floating”—Carsharing Business Models

Global use of carsharing has increased. The dominant model is station-based carsharing, but free-floating providers are continuously increasing their businesses volumes. Carsharing customers have been described as environmentally conscious with a high preference for mobility providers who show responsibility and trustworthiness. This generalization of usage determinants appears to be questionable given the background of current market developments. Existing research in the area is lacking a context-sensitive view of the antecedents of potential carsharing usage. Do environmental concerns and trust have similar effects on usage intention of carsharing, when free-floating providers implement business models that are more flexible, digital, and sophisticated? Using a standardized online survey, this study paper applied a framework adapted from the Theory of Planned Behavior (ToPB) that included the constructs of trust and environmental concern. The focus was on Share Now and Stadtmobil, which are the largest free-floating and station-based providers, respectively, in Germany. Using structural equation modeling, the study explored potential perception differences between both business models among German consumers. Although not significant, results indicate slightly higher total effects of environmental concern and initial trust on the usage intention of station-based compared to free-floating carsharing. Depending on the type of carsharing, different priorities should be set in the respective business model.

Teleoperation of Highly Automated Vehicles in Public Transport: User-Centered Design of a Human-Machine Interface for Remote-Operation and Its Expert Usability Evaluation

Paving the way to future mobility, teleoperation of vehicles promises a reachable solution to effectively use the benefits of automated driving as long as fully automated vehicles (SAE 5) are not entirely feasible. Safety and reliability are assured by a human operator who remotely observes the vehicle and takes over control in cases of disturbances that exceed the vehicle automation’s skills. In order to integrate the vehicle’s automation and human remote-operation, we developed a novel user-centered human-machine interface (HMI) for teleoperation. It is tailored to the remote-operation of a highly automated shuttle (SAE 4) by a public transport control center and based on a systematic analysis of scenarios, of which detailed requirements were derived. Subsequently, a paper-pencil prototype was generated and refined until a click-dummy emerged. This click-dummy was evaluated by twelve control center professionals. The experts were presented the prototype in regular mode and were then asked to solve three scenarios with disturbances in the system. Using structured interview and questionnaire methodology, the prototype was evaluated regarding its usability, situation awareness, acceptance, and perceived workload. Results support our HMI design for teleoperation of a highly automated shuttle, especially regarding usability, acceptance, and workload. Participant ratings and comments indicated particularly high satisfaction with the interaction design to resolve disturbances and the presentation of camera images. Participants’ feedbacks provide valuable information for a refined HMI design as well as for further research.

Autonomous Vehicle Use and Urban Space Transformation: A Scenario Building and Analysing Method

The use of autonomous vehicles (AVs) has the potential to transform users’ behaviour and urban space management. Quantitative and qualitative analyses of impacts require a scenario building method. We considered the fleet size, modal share, car ownership, parking preferences, and urban space repurposing during the elaboration of a novel method. Existing scenarios and results of a questionnaire survey have been used as sources. The method was applied to build scenarios in a case study in Budapest, Hungary. The results were used to calculate the impacts on urban space management, including environmental savings. The key findings are: scenarios with significant shared AV use show that parking demand may be minimised (almost 83%) and urban space repurposing has the highest potential; furthermore, AV use and sharing acceptability may decrease the fleet size and alter the type of shared mode to multiple occupancies. The developed scenario building method serves as a base for future studies. The produced scenarios allow the researchers to focus on the analysis of the impacts caused.

How Will the Technological Shift in Transportation Impact Cities? A Review of Quantitative Studies on the Impacts of New Transportation Technologies

Recent developments in vehicle automation, connectivity, electro-mobility and ridesharing are expected to transform urban mobility patterns and reshape cities. There is enormous uncertainty about how these technological developments, collectively referred to as the ‘technological shift in transportation’, may impact cities. This paper examines whether the technological shift in transportation will lead cities on a path to sustainability in five aspects—traffic flow, space use, energy consumption, transit and active mobility and economic affordability—through a review of 34 quantitative studies. We find that these studies backed by analytical and simulation models can provide more precise answers, and their results tend to contradict each other based on starting conditions, modelling methods and other driving factors. These driving factors fall within four categories: technological integration, policy, operations and urban planning. The interaction of these driving forces will determine if the technological shift improves transportation sustainability or is detrimental for the city in the long term.

Integration of automated vehicles in mixed traffic: Evaluating changes in performance of following human-driven vehicles

The introduction of Automated Vehicles (AVs) into the transportation network is expected to improve system performance, but the impacts of AVs in mixed traffic streams have not been clearly studied. As AV's market penetration increases, the interactions between conventional vehicles and AVs are inevitable but by no means clear. This study aims to create new knowledge by quantifying the behavioral changes caused when conventional human-driven vehicles follow AVs and investigating the impact of these changes (if any) on safety and the environment. This study analyzes data obtained from a field experiment by Texas A&M University to evaluate the effects of AVs on the behavior of a following human-driver. The dataset is comprised of nine drivers that attempted to follow 5 speed-profiles, with two scenarios per profile. In scenario one, a human-driven vehicle follows an AV that implements a human driver speed profile (base). In scenario two, the human-driven vehicle follows an AV that executes an AV speed profile. In order to evaluate safety, these scenarios are compared using time-to-collision (TTC) and several other driving volatility measures. Likewise, fuel consumption and emissions are used to investigate environmental impacts. Overall, the results show that AVs in mixed traffic streams can induce behavioral changes in conventional vehicle drivers, with some beneficial effects on safety and the environment. On average, a driver that follows an AV exhibits lower driving volatility in terms of speed and acceleration, which represents more stable traffic flow behavior and lower crash risk. The analysis showed a remarkable improvement in TTC as a result of the notably better speed adjustments of the following vehicle (i.e., lower differences in speeds between the lead and following vehicles) in the second scenario. Furthermore, human-driven vehicles were found to consume less fuel and produce fewer emissions on average when following an AV.

Public acceptance and perception of autonomous vehicles: a comprehensive review

Autonomous vehicles (AVs) or self-driving cars have the potential to provide many benefits such as improving mobility and reducing the energy and emissions consumed, travel time, and vehicle ownership. Thus, in the last few years, both research and industry have put significant efforts to develop AVs. However, laws and regulations are not ready yet for this switch and the legal sector is unable to take the lead but follow the development of AVs. Besides, the social acceptance is considered as a main key factor for the success of any new technology. Despite the enthusiastic speculation of AVs, little is known about the public acceptance and perception of the AVs technology or the factors that influence the public acceptance. This paper reviews the previous studies that focuses on testing the public acceptance and perception of AVs and sketches out the main trends in this area to provide some directions and recommendations for the future. This paper focuses on the influence of safety, ethics, liability, regulations, and the recent pandemic on the public acceptance of AVs.

Evaluation Methods for the Impacts of Shared Mobility: Classification and Critical Review

In recent years, shared mobility services have had a growing presence in cities all over the world. Developing methodologies to measure and evaluate the impacts of shared mobility has therefore become of critical importance for city authorities. This paper conducts a thorough review of the different types of methods that can be used for this evaluation and suggests a classification of them. The pros and cons of each method are also discussed. The added value of the paper is twofold; first, we provide a systematic recording of the state of the art and the state of the practice regarding the evaluation of the impacts of shared mobility, from the perspective of city authorities, reflecting on their role, needs, and expectations. Second, by identifying the existing gaps in the literature, we highlight the specific needs for research and practice in this field that can help society figure out the role of urban shared mobility.

Users’ Acceptance of Connected and Automated Shuttles for Tourism Purposes: A Survey Study

In recent years, autonomous vehicles have received increasing attention and many studies in the literature have discussed the potentialities and the opportunities they could offer. Despite the potential benefits, mainly related to the expected reduction in accidents and congestion phenomena as well as the potentially improved social inclusion of people with driving difficulties (e.g., people with physical disabilities or elderly people), many aspects remain to be addressed, mainly for understanding users’ acceptance in the case of collective transport vehicles. This study proposes an analysis based on a survey aimed at exploring user’s preferences with respect to the use of autonomous shuttles (ASs) for tourism purposes. The main correlations between the variables considered and the preferences of potential users have been discussed. Interviewees expressed high confidence in AS technology, although the analyses performed about willingness to pay show that users give more relevance to the provided transport services than the AS technology.

The Role of Human Operators in Safety Perception of AV Deployment—Insights from a Large European Survey

Autonomous vehicles are anticipated to play an important role on future mobility offering encouraging solutions to today’s transport problems. However, concerns of the public, which can affect the AVs’ uptake, are yet to be addressed. This study presents relevant findings of an online survey in eight European countries. First, 1639 responses were collected in Spring 2020 on people’s commute, preferred transport mode, willingness to use AVs and demographic details. Data was analyzed for the entire dataset and for vulnerable road users in particular. Results re-confirm the long-lasting discourse on the importance of safety on the acceptance of AVs. Spearman correlations show that age, gender, education level and number of household members have an impact on how people may be using or allowing their children to use the technology, e.g., with or without the presence of a human supervisor in the vehicle. Results on vulnerable road users show the same trend. The elderly would travel in AVs with the presence of a human supervisor. People with disabilities have the same proclivity, however their reactions were more conservative. Next to safety, reliability, affordability, cost, driving pleasure and household size may also impact the uptake of AVs and shall be considered when designing relevant policies.

Addressing the "minimum parking" problem for on-demand mobility

Parking infrastructure is pervasive and occupies large swaths of land in cities. However, on-demand (OD) mobility has started reducing parking needs in urban areas around the world. This trend is expected to grow significantly with the advent of autonomous driving, which might render on-demand mobility predominant. Recent studies have started looking at expected parking reductions with on-demand mobility, but a systematic framework is still lacking. In this paper, we apply a data-driven methodology based on shareability networks to address what we call the "minimum parking" problem: what is the minimum parking infrastructure needed in a city for given on-demand mobility needs? While solving the problem, we also identify a critical tradeoff between two public policy goals: less parking means increased vehicle travel from deadheading between trips. By applying our methodology to the city of Singapore we discover that parking infrastructure reduction of up to 86% is possible, but at the expense of a 24% increase in traffic measured as vehicle kilometers travelled (VKT). However, a more modest 57% reduction in parking is achievable with only a 1.3% increase in VKT. We find that the tradeoff between parking and traffic obeys an inverse exponential law which is invariant with the size of the vehicle fleet. Finally, we analyze parking requirements due to passenger pick-ups and show that increasing convenience produces a substantial increase in parking for passenger pickup/dropoff. The above findings can inform policy-makers, mobility operators, and society at large on the tradeoffs required in the transition towards pervasive on-demand mobility.

An Agent-Based Simulation Approach for Evaluating the Performance of On-Demand Bus Services

On-demand multi-passenger shared transport options are increasingly being promoted as an influential strategy to reduce traffic congestion and emissions and improve the convenience and travel experience for passengers. These services, often referred to as on-demand public transport, are aimed at meeting personal travel demands through the use of shared vehicles that run on flexible routes using advanced tools for dynamic scheduling. This paper presents an agent-based traffic simulation model that was developed to evaluate the performance of on-demand public transport and compare it with existing scheduled bus services using a case study of the inner city of Melbourne in Australia. The key performance measures used in the comparative evaluation included quality of service and passenger experience in terms of waiting times, the efficiency of service and operations in terms of hourly vehicle utilization, and system efficiency in terms of trip completion rates, passenger kilometers travelled and total passenger trip times. The results showed significant benefits for passengers who use on-demand bus services compared to scheduled bus services. The on-demand bus service was found to reduce average total passenger waiting times by 89% during the Morning Peak; by 78% during the Mid-Day period; by 81% during the Afternoon Peak; and by more than 95% during other periods of the day. From an operator’s perspective, the on-demand services were found to achieve around 70% vehicle utilization rates during peak hours compared to a utilization rate not exceeding 16% for the scheduled bus services. Even during off-peak periods, the occupancies for on-demand services were almost twice the vehicle occupancies for scheduled bus services. In terms of system efficiency, the on-demand services achieved a trip completion rate of 85% compared to a trip completion rate of 67% for the scheduled bus services. The total passenger-kilometers travelled was similar for both scheduled and on-demand bus services, which refutes claims that on-demand bus services induce more kilometers of travel. The trip completion times were around 55% shorter for on-demand bus services compared to scheduled services, which represents a significant saving in travel time for users. Finally, the paper presents average emissions per completed trip for both types of services and shows a significant reduction in emissions for on-demand services compared to conventional bus services. These include, on average, a 48% reduction in CO2 emissions per trip; 82% reduction in NO emissions per trip; and 41% reduction in p.m.10 emissions per trip. These findings clearly demonstrate the superior benefits of on-demand bus services compared to scheduled bus services.

Subjectivities behind the wheel: transformations in work relations of drivers in Brazil

Purpose

This study aims to analyze the processes of introducing apps (Easy Taxi and Uber) in the work routine of taxi and private drivers, exploring their work relations and identifying new forms of relationship between them and their passengers. The authors expose the complexity in which such processes occur in a dialogical way, aligning poststructuralist notions of actor–network theory with theorizations on subjectivity production.

Design/methodology/approach

The authors conducted semi-structured interviews with 16 drivers of Easy Taxi and Uber apps in three Brazilian capitals.

Findings

Apps came to play a central role in the work practice of the drivers interviewed. The authors suggest that they offer more security, convenience, accessibility and agility, going beyond dependent forms of working and living, in overlapping networks and connections, enacting entities that guide workers and users to an increasingly programmed way of life.

Practical implications

New forms of thinking managerial relations with taxi and private drivers work and their work relations with other drivers and passengers.

Social implications

This kind of technology not only generates new social relations but also activates mechanisms of subjectivation that reverberate new forms of relating, working and living in contemporaneity.

Originality/value

Approaches on subjectivity regarding the adoption of technology in the practice of work in the contemporaneity, with the emergence of new working relations mediated by e-hailing technology.

The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

Excessive dependence on autonomous vehicles (AVs) may exacerbate traffic congestion and increase exhaust emissions in the future. The diffusion of AVs may be significantly affected by the public’s acceptance. A few factors that may affect people’s acceptance of AVs have been researched in the existing studies, one-third of which cited behavioral theories, while the rest did not. A total of seven factors with behavior theories are screened out that significantly affect the acceptance intention, including perceived ease of use, attitude, social norm, trust, perceived usefulness, perceived risk, and compatibility. Six factors without behavior theories are summed up that affect AV acceptance, namely safety, performance-to-price value, mobility, value of travel time, symbolic value, and environmentally friendly. We found that people in Europe and Asia have substantial differences in attitudes toward AVs and that safety is one of the most concerned factors of AVs by scholars and respondents. Public acceptance of the different types of AVs and consumers’ dynamic preferences for AVs are highlighted in the review too. The quality of literature is systematically assessed based on previously established instruments and tailored for the current review. The results of the assessment show potential opportunities for future research, such as the citation of behavior theories and access to longitudinal data. Additionally, the experimental methods and the utilization of mathematical and theoretical methods could be optimized.

A Review of the Transformation of Road Transport Systems: Are We Ready for the Next Step in Artificially Intelligent Sustainable Transport?

Mobility is experiencing a revolution, as advanced communications, computers with big data capacities, efficient networks of sensors, and signals, are developing value-added applications such as intelligent spaces and autonomous vehicles. Another new technology that is both promising and might even be pervasive for faster, safer and more environmentally-friendly public transport (PT) is the development of autonomous vehicles (AVs). This study aims to understand the state of the current research on the artificially intelligent transportation system (ITS) and AVs through a critical evaluation of peer-reviewed literature. This study’s findings revealed that the majority of existing research (around 82% of studies) focused on AVs. Results show that AVs can potentially reduce more than 80% of pollutant emissions per mile if powered by alternate energy resources (e.g., natural gas, biofuel, electricity, hydrogen cells, etc.). Not only can private vehicle ownership be cut down by bringing in ridesharing but the average vehicle miles travelled (VMT) should also be reduced through improved PT. The main benefits of AV adoption were reported in the literature to be travel time, traffic congestion, cost and environmental factors. Findings revealed barriers such as technological uncertainties, lack of regulation, unawareness among stakeholders and privacy and security concerns, along with the fact that lack of simulation and empirical modelling data from pilot studies limit the application. AV–PT was also found to be the most sustainable strategy in dense urban areas to shift the heavy trip load from private vehicles.

An Inter- and Transdisciplinary Approach to Developing and Testing a New Sustainable Mobility System

Sustainability research is frequently tasked with the development of concrete solutions that can be directly applied to socio-environmental problems as such this paper presents and discusses an inter- and transdisciplinary approach to developing and testing a mobility-on-demand-system in a “real world laboratory” set up in Schorndorf, Germany. This paper addresses the following questions: (1) How can stakeholders be involved in the research and development process and become co-designers? (2) What are the suitable ways of supporting and facilitating interdisciplinary exchange and joint work at different places? The main contribution of this paper is the description of a methodological approach. It thereby reflects on the process of inter- and transdisciplinary work in the development phase and pilot operation. In addition, a joint working document, a so called “Specification Book”, is utilized to facilitate teamwork and enable the exchange of scientific knowledge within the team. The experiences in the project are also reflected upon and specific recommendations are determined. The paper further reflects on the possibilities and challenges of the methodology and provides recommendations for its application. The originality of the paper lies in its description and reflection of a method that goes beyond the participation of users in the design phase of the project.

Pumping the Brakes on Robot Cars: Current Urban Traveler Willingness to Consider Driverless Vehicles

A growing literature suggests that widespread travel conducted through driverless connected and automated vehicles (CAVs) accessed as a service, in contrast to those personally owned, could have significant impacts on the sustainability of urban transportation. However, it is unclear how the general public currently considers willingness to travel in driverless vehicles, and if they would be more comfortable doing so in one personally owned or one accessed as a service. To address this, we collected travel survey data by intercepting respondents on discretionary or social trips to four popular destinations in a medium-size U.S. city in the spring of 2017. After collecting data on how the respondent reached the survey site and the trip’s origin and destination, survey administrators then asked if respondents would have been willing to make their current trip in either a personally-owned driverless vehicle or through a driverless vehicle service. Over one-third expressed willingness to use both forms, while 31% were unwilling to use either. For those that considered only one, slightly more favored the personally-owned model. Consideration of an existing mobility service was consistently a positive and significant predictor of those that expressed willingness to travel in a driverless vehicle, while traveling downtown negatively and significantly influenced consideration of at least one form of driverless vehicle. These findings highlight the diverse public views about the prospect of integration of CAVs in transportation systems and raise questions about the assumption that travelers to central city locations would be early adopters of automated vehicle mobility services.

Toward Sustainable Environmental Quality: Priority Research Questions for North America

Anticipating, identifying, and prioritizing strategic needs represent essential activities by research organizations. Decided benefits emerge when these pursuits engage globally important environment and health goals, including the United Nations Sustainable Development Goals. To this end, horizon scanning efforts can facilitate identification of specific research needs to address grand challenges. We report and discuss 40 priority research questions following engagement of scientists and engineers in North America. These timely questions identify the importance of stimulating innovation and developing new methods, tools, and concepts in environmental chemistry and toxicology to improve assessment and management of chemical contaminants and other diverse environmental stressors. Grand challenges to achieving sustainable management of the environment are becoming increasingly complex and structured by global megatrends, which collectively challenge existing sustainable environmental quality efforts. Transdisciplinary, systems-based approaches will be required to define and avoid adverse biological effects across temporal and spatial gradients. Similarly, coordinated research activities among organizations within and among countries are necessary to address the priority research needs reported here. Acquiring answers to these 40 research questions will not be trivial, but doing so promises to advance sustainable environmental quality in the 21st century. Environ Toxicol Chem 2019;38:1606-1624. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Autonomous Road Vehicles: Challenges for Urban Planning in European Cities

Autonomous vehicles will significantly affect mobility conditions in the future. The changes in mobility conditions are expected to have an impact on urban development and, more specifically, on location choices, land use organisation and infrastructure design. Nowadays, there is not enough data for a real-life assessment of this impact. Experts estimate that autonomous vehicles will be available for uptake in the next decade. Therefore, urban planners should consider the possible impacts from autonomous vehicles on cities and the future challenges for urban planning. In this context, the present paper focuses on the challenges from the implementation of autonomous road vehicles for passenger transport in European cities. The analysis is based on a systematic review of research and policy. The main outcome of the analysis is a set of challenges for urban planning regarding the features of urban development, the local and European policy priorities, the current lack of data for planning and the potential for autonomous vehicles to be used by planners as data sources. The paper concludes that tackling these challenges is essential for the full exploitation of the autonomous vehicles’ potential to promote sustainable urban development.

Urban Sustainability and Livability: An Analysis of Doha’s Urban-form and Possible Mitigation Strategies

This study examines the concept of sustainability and livability at the neighborhood level in a low-density city such as Doha. In its current form, Metropolitan Doha, Qatar’s capital and where 80% of the population resides, is neither sustainable nor ranked highly in many city livability indices of international cities, although Qatar aims to become a truly sustainable state as envisioned in its Qatar National Vision (QNV) 2030 and endorsed in its National Development Strategies 2012 and 2018. Doha remains a fractured city; its rapid growth has led to unrestrained, extensive urban sprawl with high dependency on private transportation mainly by large SUVs, continually instigated by the absence of public transportation. Doha is also a relatively low-density city where the main driver of its urban sprawl is the inhabitants’ deep-set desire for privacy, and hence, home ownership of single-family detached villas, which have become the predominant residential building-block of neighborhoods with little to no provisions of in-neighborhood community services and amenities such as basic shopping, health, education, and recreation. Consequently, this urban form has resulted in long and frequent commutes for individuals and families, increasing the number of vehicles in traffic almost every hour of every day, traffic congestion, high transportation-related CO2 emissions, additional expenses, and loss of quality family time, among several other environmental, social, and economic sustainability impacts. The findings of this study, which are based on a behavioral survey, illustrate the residents’ views on neighborhood improvement and changes in the transportation modes, as well as their willingness to change their habits for the benefit of common and future generations.

Energy and emissions implications of automated vehicles in the U.S. energy system

Vehicle automation has the potential to drastically transform transportation, with important implications for energy and the environment. There is considerable uncertainty regarding the impact of automation on travel demand and vehicle efficiency. We utilize the MARKet ALlocation (MARKAL) energy system model to examine four previously published scenarios that consider different effects of automation on efficiency and demand. We do not replicate detailed estimation of individual mechanisms but apply key outcomes from prior studies within a broader energy system framework. Our analysis adds insights on fuel switching, upstream impacts, and air emissions. MARKAL dynamically captures interactions between transportation and non-transportation sectors, which is important given that the revolutionary shifts from automation may invalidate static assumptions. Model results suggest that increasing travel demands from automation may boost fuel use and petroleum-based fuel prices, potentially increasing the market penetration of alternative-fuel vehicles. In contrast, dramatic efficiency improvements from automation could drive fuel prices lower, greatly reducing the competitiveness of alternative-fueled vehicles. Furthermore, these shifts could yield positive or negative environmental impacts. Some automation scenarios even resulted in counterintuitive results. For example, if high levels of efficiency improvement drive out alternative-fuel vehicles, such as battery electric and hybrids, a net worsening of air quality relative to the other scenarios could result. We also found system-level dynamics to be key. For example, reductions in liquid fuel prices led to increased consumption, and the resulting increase in air pollutant emissions offset a portion of the potential air quality benefits of automation.

Smart Technology Impact on Neighborhood Form for a Sustainable Doha

This study focuses on the significance of neighborhoods in a city as the smallest self-sufficient urban units akin to nuclear families in the larger society. Thus, improvements to the neighborhood form can improve livability, maximize walkability, and better the overall life quality of city inhabitants, which, in turn, advance a city’s overall environmental and social sustainability profile. The physical form (arrangement) and density of neighborhoods are primarily shaped by land ownership regulations, transportation, and communication means. The development of smart technology, especially in the fields of transportation and communication, has led to the reconsideration of some of sustainable urban form concepts such as neighborhoods. Low-density cities like Doha, Qatar can become both sustainable and livable, creating the basis for a sustainable city. First, this paper presents a critical review of Doha’s neighborhoods and advanced transport and communication technologies, in addition to the integration of these technologies with the physical form of neighborhoods. Then, the paper discusses the influences of such technologies on the future sustainability of the city of Doha and its neighborhoods. This investigation is based on a Delphi study to address the characteristics of a neighborhood and to identify two paradigms of ‘good’ design practice.

A Review on Energy, Environmental, and Sustainability Implications of Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are poised to reshape transportation and mobility by replacing humans as the driver and service provider. While the primary stated motivation for vehicle automation is to improve safety and convenience of road mobility, this transformation also provides a valuable opportunity to improve vehicle energy efficiency and reduce emissions in the transportation sector. Progress in vehicle efficiency and functionality, however, does not necessarily translate to net positive environmental outcomes. Here, we examine the interactions between CAV technology and the environment at four levels of increasing complexity: vehicle, transportation system, urban system, and society. We find that environmental impacts come from CAV-facilitated transformations at all four levels, rather than from CAV technology directly. We anticipate net positive environmental impacts at the vehicle, transportation system, and urban system levels, but expect greater vehicle utilization and shifts in travel patterns at the society level to offset some of these benefits. Focusing on the vehicle-level improvements associated with CAV technology is likely to yield excessively optimistic estimates of environmental benefits. Future research and policy efforts should strive to clarify the extent and possible synergetic effects from a systems level to envisage and address concerns regarding the short- and long-term sustainable adoption of CAV technology.

Cost, Energy, and Environmental Impact of Automated Electric Taxi Fleets in Manhattan

Shared automated electric vehicles (SAEVs) hold great promise for improving transportation access in urban centers while drastically reducing transportation-related energy consumption and air pollution. Using taxi-trip data from New York City, we develop an agent-based model to predict the battery range and charging infrastructure requirements of a fleet of SAEVs operating on Manhattan Island. We also develop a model to estimate the cost and environmental impact of providing service and perform extensive sensitivity analysis to test the robustness of our predictions. We estimate that costs will be lowest with a battery range of 50-90 mi, with either 66 chargers per square mile, rated at 11 kW or 44 chargers per square mile, rated at 22 kW. We estimate that the cost of service provided by such an SAEV fleet will be $0.29-$0.61 per revenue mile, an order of magnitude lower than the cost of service of present-day Manhattan taxis and $0.05-$0.08/mi lower than that of an automated fleet composed of any currently available hybrid or internal combustion engine vehicle (ICEV). We estimate that such an SAEV fleet drawing power from the current NYC power grid would reduce GHG emissions by 73% and energy consumption by 58% compared to an automated fleet of ICEVs.