Autonomous Vehicles and Cities

Governing Autonomous Vehicles

The advent of autonomous-vehicle (AV) technology promises to upend urban mobility and transportation policy. Yet this technology, as well as its possible social and environmental consequences, are far from certain. At JTL, we examine how people, policy, and cityscapes will interact with this new technology by examining the formation processes of people’s preferences for autonomous vehicles; evaluating how to embed shared AV services within the public transportation system, through the integration of information, price, operations, and institutions; envisioning how municipal governments can devise AV policies to produce more equitable, sustainable, efficient, and livable cities; examining potential secondary impacts of AVs on urban systems, including land use and the environment as well as policies to mitigate negative impacts; and acknowledging the uncertainties inherent in planning for autonomous vehicles and applying research methodologies appropriate to such uncertainty.

AV technology could revolutionize urban mobility—making travel cheaper and more accessible, and spurring the development of more vibrant, safer communities. These outcomes, however, are hardly guaranteed. Rather, they will require thoughtful regulatory policy to stimulate development in such a positive direction. We provide policymakers in Canada, the United States, Singapore, and other partner organizations with the tools they need to design and implement just such effective, considered legislation.

Approach

Based in the Massachusetts Institute of Technology (MIT) we approach autonomous vehicle development through an urbanist perspective and have five guiding principles:

  • AV development should accommodate the different needs, preferences, and abilities of a community’s diverse population. 
  • AV service should be available and accessible to all citizens, regardless of their income; where they live, work, and play; or the technology they own.
  • AVs should contribute to a reduction in transportation-sector greenhouse gas emissions. 
  • AV rollout should help eliminate fatal and serious traffic collisions. 
  • AV should be to make walking, biking, public transit, and sharing a ride more attractive. 

Our Policy Foundation

We have identified nine general policies to address the challenges of modern transportation systems, which are enhanced by the capabilities of autonomous technology. While these broad ideas must be refined for each local context, they form the backbone of our work.  

I. Altering the Cityscape

Limit parking provision: As the AV fleet grows, cities can reduce on-street and garage parking, decouple development projects from parking provision, and incentivize redevelopment of existing lots—to encourage commuters to choose alternative modes of travel.

Rethink the use of streetspace: By reducing road space for automobiles proportional to the decline in registered vehicles, cities can open up land for larger sidewalks and plazas, as well as dedicated transit and bike lanes—to make it more attractive to choose active and public transit. 

II. Ensuring Adequate Service

Centralize data collection and distribution: To strengthen and develop a holistic mobility system, cities can use existing technology (such as online trip planning applications and fare collection systems) to make multi-modal travel easier. 

Require minimum levels of service provision: By setting minimum levels of service provision, cities can ensure all citizens can get around within a reasonable amount of time, regardless of where they are going or coming from. 

Integrate for-hire autonomous vehicles and public transit: Enabling travellers to seamlessly transfer between public transit and for-hire services depending on travel time of day and location makes it more appealing to choose more efficient forms of transport. 

III. Harnessing Pricing

Enact distance-based road pricing: Charging users based on when and where they travel would encourage higher vehicle occupancy, particularly at peak times, and would discourage the circulation of empty autonomous vehicles on public streets.

Offer income-based subsidies: Travel is essential to citizen wellbeing, and cities can financially support those of lesser means to meet their travel needs. This assistance should not be a subsidy for AV services specifically, but for using a multi-modal network when getting around. 

IV. Limiting Externalities

Require zero-emission vehicles: Vehicles are to a great degree responsible for localized poor air quality, so limiting pollutants at the tail pipe cuts the environmental and health burdens imposed by a fossil fuel-based transportation system.

Limit empty-vehicle travel: Autonomous vehicles will have the ability to move by themselves, without passengers. In congested areas, this could add to traffic and slow travel times for people inside other vehicles. Cities can mitigate this impact by limiting empty-vehicle travel.   

AV Policy 

  • Aptitudes for Regulating Autonomous Vehicles: A Survey of Municipal Officials

    Transportation Research Board 99th Annual Meeting
    Washington, D.C.
    ,
    (
    2020
    )

    Local governments play an important role in urban transportation through street management, zoning, right-of-way apportionment, and shared jurisdiction over ride-hailing, transit, and road pricing. While cities can harness these powers to steer the development of new transportation technologies, there is little research about what local officials think about making autonomous vehicle (AV)-related policy changes. We compile key AV-related transportation policies and conduct a large survey of municipal officials throughout the United States. In addition to exploring officials´ personal support for each policy, we examine other aspects of municipal decision-making, including the bureaucratic capacity, legal capacity, and political support for each policy. We find broad personal support among officials for regulations in the areas of land use, right-of-way, and equity, such as for increasing pedestrian street space, expanding access for low-income and disabled people, and reducing sprawl. However, officials emphasized uncertainty with regards to bureaucratic or legal capacity for city intervention outside of land use, right-of-way, and equity; and only a minority expected political support for any policy. Requiring shared vehicles and banning single occupancy vehicles evinced the lowest support of any policy across all spectrums, raising concerns about ongoing efforts to encourage a transportation system with fewer single-occupancy vehicles We identify population size and local-resident political ideology to be most strongly associated with personal and political support for most policies (officials from cities with more liberal residents are much more likely to support AV-related regulations), but local population growth is the most significant characteristic in influencing capacity to undertake policies.

  • Policies for autonomy: How American cities envision regulating automated vehicles

    Urban Science
    (
    2020
    )

    Local governments play an important role in structuring urban transportation through street design, zoning, and shared jurisdiction over ride-hailing, transit, and road pricing. While cities can harness these powers to steer planning outcomes, there is little research about what local officials think about regulatory changes related to autonomous vehicles (AV). We compile key AV-related policies recommended by scholars but rarely implemented, and conduct a survey of municipal officials throughout the United States, exploring their personal support and perceptions of bureaucratic capacity, legal limits, and political backing for each policy. This paper finds broad personal support for regulations related to right-of-way, equity, and land use, such as for increasing pedestrian space, expanding access for low-income people, and reducing sprawl. However, officials emphasized uncertain bureaucratic and legal capacity for city intervention outside of these areas, reaffirming limited local power in the federal system. Only a minority expected political support for any policy. Greater population size and more liberal resident political ideologies are strongly associated with personal and political support for many policies. Local population growth is correlated with greater capacity to undertake policies. This work contributes to the growing literature on transportation governance in the context of technological uncertainty.

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    Are cities prepared for autonomous vehicles? Planning for technological change by U.S. local governments

    Journal of the American Planning Association
    (
    2019
    )

     

    Problem, Research Strategy, and Findings: Local government policies could impact how autonomous vehicle (AV) technology is deployed. This paper examines how municipalities are planning for AVs, identifies local characteristics that are associated with preparation, and describes what impacts bureaucrats expect from the vehicles. We review existing plans of the United States’ 25 largest cities and survey transportation and planning officials from 120 cities, representative of all municipalities with populations larger than 100,000. First, we find that few local governments have commenced planning for AVs. Second, cities with larger populations and higher population growth are more likely to be prepared. Third, while local officials are optimistic about the technology and its potential to increase safety while reducing congestion, costs, and pollution, more than a third of respondents worried about AVs increasing vehicle-miles traveled and sprawl while reducing transit ridership and local revenues. Those concerns are associated with greater willingness to implement AV regulations, but there is variation among responses depending on political ideology, per-capita government expenditures, and population density.

    Takeaway for Practice: Municipal governments’ future approaches to AV preparation will likely depend on characteristics of city residents and local resources. Planners can maximize policy advancement if they work with officials in other cities to develop best practices and articulate strategies that overlap with existing priorities, such as reducing pollution and single-occupancy commuting. 

    Cited as: "Yonah Freemark, Anne Hudson & Jinhua Zhao (2019) Are Cities Prepared for Autonomous Vehicles?,Journal of the American Planning Association, DOI: 10.1080/01944363.2019.1603760"

     

  • Is There a Way? Is There a Will? Legal, bureaucratic and political aspects of Automated Vehicles Regulation in Toronto, Canada

    Transportation Research Board 98th Annual Meeting
    Washington, D.C.
    ,
    (
    2019
    )

    Current research suggests there is a huge uncertainty as to whether automated vehicle development will improve or exacerbate congestion, sprawl, and inequitable access to travel. Likely, the outcome will be determined by the policies governments adopt to guide development. As such, the goal of this paper is to examine the legal capacity, bureaucratic willingness and capacity, and political willingness and capacity of regulating automated vehicle regulatory development in Toronto, Canada.

    Firstly, the government needs legal capacity to regulate in a given area. The remaining four elements all relate to human resources. Interviews show Toronto’s bureaucrats believe they have a responsibility and ability to craft effective and ambitious regulations that advance the city’s goals. These willing civil servants need the time and the expertise to design good policy, and the Toronto government has an AV working group that provides a forum for such a discussion. To see regulations enacted effectively, however, the mayor and council must not only support rules eventually proposed by the working group; they may also need to approach the provincial government to convince them to craft their own complementary AV legislation.

    Should policymakers want to see bold and effective regulation enacted at the local level to address the harms that might arise from AV development and guide private- sector business operations to foster equitable and sustainable planning outcomes, they must look at whether their colleagues and the politicians under whom they serve have the willingness, and ability, to propose such rules.

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    An Urban Agenda for Autonomous Vehicles: Embedding Planning Principles into Technological Deployment

    Transportation Research Board 97th Annual Meeting
    Washington, D.C.
    ,
    (
    2018
    )

    The deployment of autonomous vehicles (AVs) has spawned a considerable literature on the role of national and state-level governments in regulating components of AV manufacturing, emissions, safety, licensing, and data sharing. These provide insight into how AVs can be integrated into the current transportation system. Yet the potential for local governments to shape their futures through AV policies is underexplored. This paper argues that it is both necessary and feasible for local government to adjust local mobility policies for AVs towards the goal of achieving key planning principles by disrupting the current transportation system. Local governments must leverage the ephemeral moment in advance of full-scale AV rollout to achieve the principles of equitable, environmentally sustainable, efficient, and livable cities. It is necessary to establish a new regulatory relationship with automobiles and design mobility policies to cultivate AV benefits, while responding to their potentially deleterious impacts. Local governments are capable of doing so through their already-existing regulatory mechanisms managing much of the transportation infrastructure, public transit, taxi, parking, land uses, and public data. Based on such local government power, we identify eight policy instruments that are feasible: centralized data collection and distribution; distance- and congestion-based road pricing; integration of AV and transit networks; income-based subsidies; minimum levels of service provision; zero-emission vehicles; lowered parking provision; and a rethinking of the use of street space. We explore how such instruments could be implemented in the context of existing regulatory mechanisms through the diverging lenses of indicative cases of Chicago and London.

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    Is There a Way? Is There Even a Will? Exploring the legal capacity, bureaucratic willingness and capacity, and political willingness and capacity of automated vehicle regulatory development in Toronto, Canada

    Working paper
    (
    2018
    )

    Current research suggests there is a huge uncertainty as to whether automated vehicle development will engender a more equitable, efficient, and sustainable transportation network, or will exacerbate current trends of congestion, sprawl, and inequitable access to travel. Likely, the outcome will be determined by the policies governments adopt to guide development. Some of the most acute challenges of automated vehicle proliferation will be most acutely felt in areas under the purview of local governments—such as transportation congestion, land use, and impacts on public transit. As such, the goal of this thesis is to assist municipal policymakers with mitigating these impacts by answering the question: How can local governments, specifically the City of Toronto, effectively regulate automated vehicles? Interviews were conducted with experts from the public and private sectors and academia, with responses developed into five elements of effective regulation.Firstly, the government needs legal capacity to regulate in a given area. Toronto, for example, is responsible for overseeing local rideshare company activity. The remaining four elements all relate to human resources. Interviews show Toronto’s bureaucrats believe they have a responsibility and ability to craft effective and ambitious regulations that advance the city’s goals. These willing civil servants need the time and the expertise to design good policy, and the Toronto government has an AV working group that provides a forum for such a discussion. To see regulations enacted effectively, however, the mayor and council (to varying degrees, depending on whether the city operates a weak or strong mayoral system) must not only support rules eventually proposed by the working group; they may also need to approach the provincial government to convince them to craft their own complementary AV legislation. This research concludes that should policymakers want to see bold and effective regulation enacted at the local level to address the harms that might arise from AV development and guide private-sector business operations to foster equitable and sustainable planning outcomes, they will want to reflect on not only where within their jurisdiction they can legally ground new rules; they must also look at whether their colleagues and the politicians under whom they serve have the willingness, and ability, to propose such rules. While not touched on here, future research will subsequently explore the requirements to effectively implement and enforce new rules.

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    The Rules of the (Automated) Road: A Regulatory Proposal for Automated Ridehailing Operations in Toronto, Canada, and Government and Industry Feedback

    Working paper
    (
    2018
    )

    A number of organizations have proposed general principles for AV development—such that it must be equitable, sustainable, and promote better city-building—but this research attempts to move further by offering concrete rules in municipal codes automated vehicle ridehailing companies must follow in order to operate in Toronto, Ontario. As the City of Toronto oversees rideshare company operations, they are legally able to adopt regulations that reflect their general planning principles. Through consultation with government stakeholders and a review of the primary and secondary urban and transportation plans, major planning objectives regarding transportation equity and sustainability, and urban vibrancy were determined and seven regulations were proposed to reflect these goals. 

    These requirements were then presented to policy experts in six City of Toronto policy experts and three employees working in the automated vehicle industry. Op inions varied, from one private-sector stakeholder who argued ridehailing companies, left to their own devices, shall ensure equity and good urban form are respected, to those in the City of Toronto government who advocated for even stronger measures. In general, however, the public representatives supported the regulations, but encouraged an even more robust list that included requirements to ensure rider safety and redundant vehicle control. 

    Given the disagreement as to whether a future automated vehicle ridehailing business model would be sufficient to accomplish the objectives laid out in the City of Toronto’s plans, future research should consider what data is needed to determine whether it falls short. Additionally, while the local government does have a strong ability to influence ridehailing activity, it has less control over the automated fleet more broadly. As such, it will be worth considering what requirements the provincial government can impose to ensure positive AV development. 

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    Driving AV Policy? A 300-City Survey of AV Policy Preparedness

    (
    2018
    )

    AVs could have significant consequences in terms of the level of vehicle travel on urban streets, the need for parking in neighborhoods, the ease of accessing employment, and the incidence of pollution. Addressing those issues is fundamental to achieving better planning, and cities could play an important role in orienting policies to ensure the best-possible outcomes. All around the world, cities hold the legal mechanisms to intervene in issues related to AVs, such as the design of streets, requirements related to taxi services, and fare policies. Many municipalities are, in fact, promoting the potential for testing AVs; political officials frequently argue that these tests are essential for reaffirming their respective cities’ status as technological innovation leaders. But research we have conducted demonstrates that policymaking at the local level is underdeveloped. Yet that is slowly changing. This 300-city survey is gathering feedback from officials across the United States to determine the capacity and willingness they, and their elected superiors, have to think about and act on regulating autnomous vehicles. Please stay tuned for updates! 

AV Analytics

  • Competition between Shared Autonomous Vehicles and Public Transit: A Case Study in Singapore

    Transportation Research Part C
    (
    2021
    )

    Emerging autonomous vehicles (AV) can either supplement the public transportation (PT) system or compete with it. This study examines the competitive perspective where both AV and PT operators are profit-oriented with dynamic adjustable supply strategies under five regulatory structures regarding whether the AV operator is allowed to change the fleet size and whether the PT operator is allowed to adjust headway. Four out of the five scenarios are constrained competition while the other one focuses on unconstrained competition to find the Nash Equilibrium. We evaluate the competition process as well as the system performance from the standpoints of four stakeholders—the AV operator, the PT operator, passengers, and the transport authority. We also examine the impact of PT subsidies on the competition results including both demand-based and supply-based subsidies. A heuristic algorithm is proposed to update supply strategies for AV and PT based on the operators’ historical actions and profits. An agent-based simulation model is implemented in the first-mile scenario in Tampines, Singapore. We find that the competition can result in higher profits and higher system efficiency for both operators compared to the status quo. After the supply updates, the PT services are spatially concentrated to shorter routes feeding directly to the subway station and temporally concentrated to peak hours. On average, the competition reduces the travel time of passengers but increases their travel costs. Nonetheless, the generalized travel cost is reduced when incorporating the value of time. With respect to the system efficiency, the bus supply adjustment increases the average vehicle load and reduces the total vehicle kilometer traveled measured by the passenger car equivalent (PCE), while the AV supply adjustment does the opposite. The results suggest that PT should be allowed to optimize its supply strategies under specific operation goals and constraints, and AV operations should be regulated to reduce their system impacts, including potentially limiting the number of licenses, operation time, and service areas, which makes AV operate in a manner more complementary to the PT system. Providing subsidies to PT results in higher PT supply, profit, and market share, lower AV supply, profit, and market share, and increased passengers generalized cost and total system PCE.

  • Impacts of subjective evaluations and inertia from use of existing travel modes on adoption of autonomous mobility-on-demand

    Transportation Research Part C
    (
    2021
    )

    As autonomous vehicle (AV) technology advances, it is important to understand its potential demand and user characteristics. Literature from stated preference surveys find that attitudes and current travel behavior are as or more important than demographics in determining intention to purchase or use AVs. Yet to date no study has looked at how attitudes and use of existing modes both simultaneously affect AV adoption. In this study, we conduct a stated preference survey in Singapore to investigate how the subjective evaluation of existing travel modes (attitudes) and inertia based on previous use of existing modes affect the adoption of an autonomous mobility-on-demand service (AMOD). Using a sample size of 2,003 individuals and 11,613 choice observations, we estimate a mixed logit discrete choice model incorporating latent variables capturing subjective evaluations of existing travel modes (determined through confirmatory factor analysis), a two-part formulation of modal inertia, and other trip-specific and socio-demographic variables. Results show that subjective evaluation and use of existing modes both affect the adoption of AMOD. Specifically, people with a positive evaluation of ridehailing and those who are current ridehailing users are more likely to choose AMOD. Additionally, those who are current car drivers are more likely to choose AMOD, while users of public transit were less likely to choose AMOD. Given that ridehailing is the closest existing mode to our hypothetical AMOD service, our results might suggest that how AVs are implemented and their similarity to existing modes may be critical to the formation of attitudes and direction of inertia impacting adoption. Our research provides insights on the potential relationship between AVs and existing modes that could valuable in AV network design and service planning.

  • Latent Attitudes of Existing Travel Modes on Autonomous Vehicle Adoption

    Transportation Research Board 99th Annual Meeting
    Washington, D.C.
    ,
    (
    2020
    )

    With the quick advance of autonomous vehicle (AV) technology, understanding the potential demand of AV and its user characteristics has increasingly become a popular area of research. In consumer choice and technology adoption literature, whenever the demand of a new product is forecasted, the attitudes towards existing choices are found important in addition to new product attributes and consumer characteristics. While there is an abundance of literature from stated preference (SP) surveys identifying attitudes are just as important as demographics in forming a purchase or usage decision of AVs, past studies have seldom looked at how attitudes towards existing travel modes affect the new mode adoption. We conduct a dynamic online SP survey in Singapore on 2,003 individuals, with indicator questions about impressions on existing modes. We focus on how these attitudes affect AV adoption based on confirmatory factor analysis and discrete choice models with latent variables. The results show that having positive attitudes towards public transit casts a negative effect on AV adoption, while having positive attitudes towards ridesharing is positive on AV adoption. And, positive attitudes towards walking and driving do not have any significant effects. In addition, the model identifies that highly educated, wealthy, and/or younger people as the population to have more positive attitudes towards new technologies and more likely to adopt AVs. The research provides insights on potential relationship between AVs and existing modes, as well as the characteristics of potential audience, which may be of help in planning future AV services.

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    Risk Preference and Adoption of Autonomous Vehicles

    Transportation Research Part A
    (
    2019
    )

    While there is an increasingly large body of research on the potential demand for autonomous vehicles (AV), an understudied factor is people’s risk preference. Risk preference is important because many aspects of AVs are highly uncertain as the technology and its encompassing mobility system emerge and continue to evolve. This study analyzed how risk preferences influence the choice of AVs, and how risk preferences elicited by economic and psychometric methods differ in their impacts. We conducted a stated preference survey in Singapore with 1,303 persons and 7 choice scenarios per person. We extracted two economic risk preference parameters based on prospect theory using individualized linear regressions; and we extracted one psychometric risk preference parameter based on a set of Likert scale questions using factor analysis. After applying mixed logit models incorporating the risk preference parameters, we found that risk-seeking preference significantly increases the choice of AVs. The economic risk preference and the psychometric risk preference are statistically uncorrelated; both contribute to predicting AV usage, and the economic risk measure improves the choice model more than the psychometric one. The results show that people’s risk preference is an important factor influencing the adoption of AVs, and future studies should continue to examine the specific relationship between the multiple components of risk preferences and the multiple uncertain aspects of AVs.

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    Value of Demand Information in Autonomous Mobility-on-Demand Systems

    Transportation Research Part A
    (
    2019
    )

    Effective management of demand information is a critical factor in the successful operation of autonomous mobility-on-demand (AMoD) systems. This paper classifies, measures and evaluates the demand information for an AMoD system. First, the paper studies demand information at both individual and aggregate levels and measures two critical attributes: dynamism and granularity. We identify the trade-offs between both attributes during the data collection and information inference processes and discuss the compatibility of the AMoD dispatching algorithms with different types of information. Second, the paper assesses the value of demand information through agent-based simulation experiments with the actual road network and travel demand in a major European city, where we assume a single operator monopolizes the AMoD service in the case study area but competes with other transportation modes. The performance of the AMoD system is evaluated from the perspectives of travelers, AMoD operators, and transportation authority in terms of the overall system performance. The paper tests multiple scenarios, combining different information levels, information dynamism, and information granularity, as well as various fleet sizes. Results show that aggregate demand information leads to more served requests, shorter wait time and higher profit through effective rebalancing, especially when supply is high and demand information is spatially granular. Individual demand information from in-advance requests also improves the system performance, the degree of which depends on the spatial disparity of requests and their coupled service priority. By designing hailing policies accordingly, the operator is able to maximize the potential benefits. The paper concludes that the strategic trade-offs of demand information need to be made regarding the information level, information dynamism, and information granularity. It also offers a broader discussion on the benefits and costs of demand information for key stakeholders including the users, the operator, and the society.

  • Public Perceptions of Autonomous Vehicle Safety: An International Comparison

    Safety Science
    (
    2019
    )

    Autonomous vehicles (AV) are envisioned to reduce road fatalities by switching control of safety-critical tasks from humans to machines. Realizing safety benefits on the ground depends on technological advancement as well as the scale and rate of AV adoption, which are influenced by public perceptions. Employing multilevel structural equation modeling, this paper explores differences in perceptions of AV safety across 33,958 individuals in 51 countries. At the individual level, young males report higher perceptions of current AV safety and predict fewer years until AVs are safe enough for them to use. Since young males are more likely to undertake risky driving behavior, their positivity towards AV safety could lead to more rapid manifestations of safety benefits. Urban, fully employed individuals with higher incomes and education levels also report fewer years until AVs are safe to use. The multilevel model identifies country-level effects after controlling for individual characteristics. Developed countries with greater motorization rates and lower road death rates tend to have greater awareness of AVs but are more pessimistic about their present and future safety. Individuals in developing countries that face greater road safety challenges, particularly involving 2- and 3-wheeled vehicles, predict fewer years until AVs will be safe enough for them to use. Higher AV safety perception among the most risk-taking road users and in developing countries coincide with sociodemographic groups and geographic areas facing the greatest road safety challenges and most in need of improvement, highlighting a potential opportunity to reduce the global disparity in road safety.

  • Built Environment and Autonomous Vehicles Mode Choice: A First Mile Scenario in Singapore

    Transportation Research Board 98th Annual Meeting
    Washington, D.C.
    ,
    (
    2019
    )

    This study investigates travel mode choice with on-demand autonomous vehicle (AV). It takes Singapore as the study area and specifically focuses on understanding the impacts of built environment (BE) on first-mile scenarios. A dynamic stated preference survey is developed to automatically generate first-mile travel scenarios based on the respondent’s dwelling location and real-world traffic information. Two mixed logit models with panel data structures are adopted to explore the impacts of BE on AV mode choice. The results reveal that BE factor is independent of trip specific and sociodemographic variables. Although including BE does not significantly improve the model fitting, it adds to explain the nuances of individual’s preference on travel mode choice. We then employ the models to forecast AV mode choice of 11,545 individuals from the Household Interview Travel Survey of Singapore. It provides a good understanding of AV market share in different areas and helps in evaluating the planning for AV deployment in Singapore. The estimation shows the mode shares of AV in most of pilot areas with AV plans are quite low. Thus, revisiting the planning of pilot areas for future AV deployment may be needed to avoid a spatial mismatch of on- demand AV service.

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    Integrating Shared Autonomous Vehicle in Public Transportation System: A Supply-Side Simulation of the First-Mile Service in Singapore

    Transportation Research Part A
    (
    2018
    )

    This paper proposes and simulates an integrated autonomous vehicle (AV) and public transportation (PT) system. After discussing the attributes of and the interaction among the prospective stakeholders in the system, we identify opportunities for synergy between AVs and the PT system based on Singapore’s organizational structure and demand characteristics. Envisioning an integrated system in the context of the first-mile problem during morning peak hours, we propose to preserve high demand bus routes while repurposing low-demand bus routes and using shared AVs as an alternative. An agent-based supply-side simulation is built to assess the performance of the proposed service in fifty-two scenarios with different fleet sizes and ridesharing preferences. Under a set of assumptions on AV operation costs and dispatching algorithms, the results show that the integrated system has the potential of enhancing service quality, occupying fewer road resources, being financially sustainable, and utilizing bus services more efficiently.

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    Transit-Oriented Autonomous Vehicle Operation with Integrated Demand-Supply Interaction

    Transportation Research Part C
    (
    2018
    )

    Autonomous vehicles (AVs) represent potentially disruptive and innovative changes to public transportation (PT) systems. However, the exact interplay between AV and PT is understudied in existing research. This paper proposes a systematic approach to the design, simulation, and evaluation of integrated autonomous vehicle and public transportation (AV+PT) systems. Two features distinguish this research from the state of the art in the literature: the first is the transit-oriented AV operation with the purpose of supporting existing PT modes; the second is the explicit modeling of the interaction between demand and supply. We highlight the transit-orientation by identifying the synergistic opportunities between AV and PT, which makes AVs more acceptable to all the stakeholders and respects the social-purpose considerations such as maintaining service availability and ensuring equity. Specifically, AV is designed to serve first-mile connections to rail stations and provide efficient shared mobility in low-density suburban areas. The interaction between demand and supply is modeled using a set of system dynamics equations and solved as a fixed-point problem through an iterative simulation procedure. We develop an agent-based simulation platform of service and a discrete choice model of demand as two subproblems. Using a feedback loop between supply and demand, we capture the interaction between the decisions of the service operator and those of the travelers and model the choices of both parties. Considering uncertainties in demand prediction and stochasticity in simulation, we also evaluate the robustness of our fixed-point solution and demonstrate the convergence of the proposed method empirically. We test our approach in a major European city, simulating scenarios with various fleet sizes, vehicle capacities, fare schemes, and hailing strategies such as in-advance requests. Scenarios are evaluated from the perspectives of passengers, AV operators, PT operators, and urban mobility system. Results show the trade off between the level of service and the operational cost, providing insight for fleet sizing to reach the optimal balance. Our simulated experiments show that encouraging ride-sharing, allowing in-advance requests, and combining fare with transit help enable service integration and encourage sustainable travel. Both the transit-oriented AV operation and the demand-supply interaction are essential components for defining and assessing the roles of the AV technology in our future transportation systems, especially those with ample and robust transit networks.

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    Simulating the First Mile Service to Access Train Stations by Shared Autonomous Vehicle

    Transportation Research Board 96th Annual Meeting
    (
    2017
    )

    This paper studies the potential impacts of autonomous vehicle (AV) sharing with mobility-on demand service on the public transit system. We analyze the current travel demand in the public transit system in Singapore with a special focus on the first-/last-mile problem during morning peak hours. The first-/last-mile in this paper is defined as the gap between origin/destination and the heavy rail stations. A feasible method to integrate AV sharing in current transit system is proposed, which is to use on-demand AV sharing service as the alternative to the low-demand buses to improve the first-/last-mile connectivity in the study area. An agent-based simulation model is built to evaluate the performance of the new integrated service. The simulation models the behaviors, movements, and interactions of the agents—passengers, AVs, and traditional buses. A bus-only scenario is firstly simulated for validation purpose based on the real-world statistics. Then a series of scenarios integrating AV sharing in public transit system with various fleet size and passenger’s sharing preference are simulated. The results under the AV sharing scenario show that, by letting everyone in the system share their last-mile rides, with careful selection of the size of AV fleet, the new service is able to (1) reduce the average out-of-vehicle time for the passengers, (2) occupy less road resources than the low-demand buses, and (3) have a higher possibility to be financially viable.

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    Rebalancing Shared Mobility-on-Demand Systems: a Reinforcement Learning Approach

    IEEE ITSC Workshop on Intelligent Public Transport 2017
    (
    2017
    )

     

    Shared mobility-on-demand systems have very promising prospects in making urban transportation efficient and affordable. However, due to operational challenges among others, many mobility applications still remain niche products. This paper addresses rebalancing needs that are critical for effective fleet management in order to offset the inevitable imbalance of vehicle supply and travel demand. Specifically, we propose a reinforcement learning approach which adopts a deep Q network and adaptively moves idle vehicles to regain balance. This innovative model-free approach takes a very different perspective from the state-of-the-art network-based methods and is able to cope with large-scale shared systems in real time with partial or full data availability. We apply this approach to an agent based simulator and test it on a London case study. Results show that, the proposed method outperforms the local anticipatory method by reducing the fleet size by 14% while inducing little extra vehicle distance traveled. The performance is close to the optimal solution yet the computational speed is 2.5 times faster. Collectively, the paper concludes that the proposed rebalancing approach is effective under various demand scenarios and will benefit both travelers and operators if implemented in a shared mobility-on-demand system.  

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    Dynamic Pricing in Shared Mobility on Demand Service and its Social Impacts

    Working paper
    (
    2017
    )

     

    We consider a daily-level profit maximization of a shared mobility on-demand (MoD) service with request-level control, and possible government interventions to improve system efficiency. We use discrete choice models to describe traveler behavior, apply the assortment and price optimization framework to model the request-level dynamics, and leverage insights from dynamic programming to develop daily-level optimization problem. We solve this problem by designing parametric rollout policy and utilizing Covariance Matrix Adaptation Evolution Strategy (CMA-ES) to search for optimal parameter.

    We evaluate our algorithm with a case study in Langfang, China. We develop a simulation system for both the MoD service operations and the city transportation dynamics, and design scenarios with varying supply size, demand size, congestion level, and fare structure. In this case study, the optimal pricing strategy generates considerably more profit than basic strategies (those without assortment or dynamic pricing) and myopic strategies (dynamic pricing at each request level), but it increases the congestion level and reduces the capacity in the transportation system. We also compare two policy interventions to improve the system efficiency, i.e. congestion based taxation and demand based taxation, and find that the congestion based taxation is more effective. 

Team Members