There may be much to gain by deploying wireless infrastructure to support connected vehicles as part of a smart city strategy. However, these infrastructure costs can be considerable. Moreover, there are now multiple competing wireless technologies to choose from. This research uses a combination of packet-level simulation of wireless vehicular networks and an engineering-economic model of wireless infrastructure costs to help local, state and federal policymakers devise cost-effective strategies for wireless smart city infrastructure. It will explore whether and where communities can work effectively with commercial ISPs to deploy this infrastructure at lower cost to tax payers, even if in 2018 the U.S. Department of Transportation withdraws its proposed rules to require all new vehicles in the U.S. to be equipped with this wireless technology, as is widely expected. This research project will also explore the impact of proposed changes in spectrum policy at the U.S. Federal Communications Commission for the portion of spectrum allocated to Intelligent Transportation Systems
Emerging wireless and smart city technologies offer tremendous potential, including the ability to bring automobile drivers and passengers the benefits of improved safety, reduced congestion, and valuable new applications and services. However, for government agencies at the local, state and federal levels, these technologies also bring a dizzying series of decisions. Should we spend tax-payer dollars on new kinds of wireless infrastructure to support such systems? Should we partner with the private sector to do so, or even count on the private sector to build what we need on its own? What kind of wireless infrastructure is needed, now that there are competing technologies? For federal policymakers, how much spectrum should we make available for such systems, and in what form? Moreover, the best answer to such questions will often vary from community to community. The long-term goal of this research is to provide credible and quantitative results that shed light on the most cost-effective strategies for wireless smart city infrastructure to support connected vehicles. The goal for next year is to address major changes in the connected vehicle landscape that have emerged in just the last year or two. MOTIVATION It is possible to bring wireless communications to motor vehicles through traditional cellular systems, but sending information through a cellular system can be a slow and highly inefficient way of connecting two cars that are just a few meters apart, or connecting a car with a nearby signal light or fixed roadside sensor. One alternative is to support direct communications between vehicles (V2V) or vehicle to infrastructure (V2I) using a technology known as Dedicated Short-Range Communications (DSRC). Moreover, DSRC also supports mesh networking, which has many advantages. The superior latency of a DSRC-based approach is particularly valuable for real-time applications that improve safety on the roads. In 2016 the U.S. Department of Transportation proposed rules that would require all new vehicles sold in the U.S. to be equipped with DSRC devices, and that called upon state and local governments to spend billions of dollars deploying DSRC-based roadside infrastructure to communicate with these vehicles. The stated goal was to improve safety, and the U.S. Department of Transportation concluded that the benefits of reduced fatalities, injuries and property damage exceeded the cost. Nevertheless, this would not make it easy for state and local governments to cover the billions of dollars of infrastructure cost . In that 2016 context, which now seems like the distant past, our research to date has offered one way to reduce this burden. We have shown that in some but not all parts of the country, these same DSRC-based mesh networks are a more cost-effective way of providing Internet access and other broadband capabilities to highly mobile devices such as cars than traditional cellular networks , while still giving safety applications priority over other kinds of traffic whenever it is needed. Thus, there is an opportunity for commercial ISPs or new forms of businesses to deploy DSRC-based roadside infrastructure as a means of providing Internet access, and doing so will lower the cost of Internet for these communities. This approach was found to be cost-effective in densely populated regions, but not in rural areas. Our subsequent research considered the challenge from the perspective of state and local Departments of Transportation that have been tasked with building out DSRC-based infrastructure for safety purposes. We found that there are substantial economies of scope from combining government DSRC-based roadside infrastructure for safety and commercial DSRC-based roadside infrastructure for Internet access. Thus, government can form new kinds of partnerships with commercial ISPs that benefit both parties, and that benefit drivers who would welcome inexpensive broadband services to the car. Where benefits of sharing infrastructure are sufficient, multiple policies and business arrangements become possible: (i) government can deploy infrastructure for safety and smart city purposes, and charge commercial Internet service providers (ISPs) that use it, (ii) government can get some of the infrastructure it needs at lower cost by leasing access from commercial ISPs, or (iii) government and commercial ISPs can establish public-private partnerships to manage shared infrastructure. In a series of papers (such as [3, 4]), the PI investigated similar infrastructure sharing opportunities between wireless communications systems for public safety (e.g. firefighters, police, paramedics) and commercial cellular. His research at CMU demonstrated that many billions of dollars could be saved through different forms of infrastructure sharing. Later, while serving first as Chief Technologist in the Federal Communications Commission and then in the White House, he co-authored the plan to turn this proposal into reality. Congress passed the legislation in 2012, and put $7 billion towards nationwide rollout. In the context of vehicular networks, we have found  that this kind of cooperation between government and industry would save hundreds of millions of tax-payer dollars, or roughly a fifth of the overall safety infrastructure cost, although the benefits are unevenly distributed. In some cities, cooperation with commercial partners could cover more than 80% of government costs for safety infrastructure. In others, we estimate closer to 40%. In rural areas, savings from this approach are close to 0. Local governments could use results like these to develop a strategy that makes sense for their communities. State and federal policymakers might use these results to try to level the playing field, by helping out those municipalities likely to be hardest hit. However, the work described above relied on four major assumptions that may not be appropriate in the U.S. in the future. These are issues that we hope to address in the coming years. The first is that the U.S. Department of Transportation would mandate that all new vehicles be equipped with DSRC as the Department proposed in 2016. Since then, a new Administration has taken power with different priorities. The Department of Transportation made no move in 2017 to adopt the rules proposed the year before, and the news media has reported that the mandate will not occur . Vehicles may still be equipped with DSRC, but without a mandate, we must consider the incentives of car makers and car buyers when estimated market penetration, and the results may (or may not) be quite different. Good analysis in scenarios without a mandate is needed. Second, wireless technology is changing in a number of important ways. DSRC is no longer the only kind of roadside infrastructure that one might consider to support short-range communications with connected vehicles. Cellular operators have already been increasing reliance on microcells and femtocells in recent years, but in the past these devices have been problematic for vehicles because handoff times are far too slow for a device that is moving at 50 miles per hour. More recently, 3GPP has been advancing a set of standards known as cellular vehicle-to-everything (C-V2X) that includes V2V, V2I, and vehicle-to-base stations. The first trials of this technology have been announced for 2018. With more options, it is no longer clear which is the best. In addition, advances in more traditional cellular approaches are expected to make those systems more efficient as fifth generation (5G) cellular is rolled out, and this could reduce the comparative advantage of the new mesh networks. The emergence of these new technologies has the potential to change the types of technology that a city may choose to deploy, if it chooses to deploy at all. Moreover, it may change what the government should or must do for itself, and what it can expect from commercial cellular operators that offer broadband services using 5G technology. Our previous work also assumed that all vehicles and roadside units would have compatible technology (i.e. DSRC), and would choose to interoperate for their mutual benefit. Thus, vehicles in a region form a single mesh network. It is also possible that there will be competing systems, each with their own mesh, and possibly using different technologies that cannot interoperate. We have not yet studied the likelihood of this scenario, or its implications, which could be significant. Finally, we should consider the possibility of alternative spectrum regimes. In our results cited above, we assumed that vehicular communications would have exclusive access to the “Intelligent Transportation System” spectrum band, as was decided by the Federal Communications Commission (FCC), and is still current spectrum policy. In recent years, there has been a proceeding at the FCC that explored the possibility of allowing unlicensed devices (such as Wi-Fi) into the same band. Different spectrum sharing schemes are currently under consideration, which would have different impact on vehicular networks. In 2017, the new administration released an official Notice of Inquiry signaling its interest in repurposing what the FCC now calls “mid band” spectrum, and this could lead to further changes to the Intelligent Transportation System spectrum band. These possibilities are important for our research in two respects. First, a change in spectrum policy could make some technical approaches more or less cost-effective, and this could change the strategies that we would recommend to communities building out wireless smart city infrastructure. Second, our research could provide guidance to spectrum policymakers at the FCC by illuminating the potential implications of their decisions. While we cannot address all of these issues in a single year of research, one focus of our work next year will be on incorporating the possibility of spectrum sharing in the Intelligent Transportation Systems (ITS) band into our model. We will consider the possibility (i) that the FCC might change the amount of spectrum that vehicular networks can access, (ii) that the FCC might make some or all of the spectrum used by vehicular networks accessible to unlicensed devices, (iii) that unlicensed devices sharing this spectrum might be given secondary priority or might be allowed to share on a co-equal basis, and (iv) that unlicensed devices might share spectrum with vehicular networks using a cooperative scheme or using a coexistent scheme. We have begun this analysis , but there is more to do, even for the basic scenarios that the FCC was considering before the 2017 Notice of Inquiry. The other focus of our research next year will depend somewhat on coming events. If it becomes clear by June that the Department of Transportation will not mandate DSRC in new vehicles, as we expect based on reports to date , then we will focus on examining the costs and benefits to a community of deploying DSRC-based infrastructure in a world without a mandate. This includes estimating the fraction of vehicle owners who have incentive to purchase the technology voluntarily. If this expected policy change does not occur, however, then we will more time to spend examining emerging cellular vehicle-to-everything (C-V2X) technology, incorporating it into our engineering-economic models, and exploring the implications for communities that are considering deployment of wireless smart-city infrastructure. METHOD Our modeling approach is threefold: (i) collect extensive data from a large deployed vehicular networks in Portugal, (ii) develop a detailed packet-level network simulation using this data that shows the relationship between infrastructure deployment strategies and achievable throughput, and (iii) develop engineering-economic models that relate costs and revenues to achievable throughputs and infrastructure strategies. Infrastructure strategies vary in number of roadside units per square km, and extent of sharing between infrastructure for safety and infrastructure for Internet access. We have developed and continue to expand packet-level simulation software that uses location data from more than 900 vehicles from Portugal, to simulate a mesh network comprised by DSRC-equipped vehicles that connect to roadside units (RSU) to gain access to the Internet. We will use this simulation to estimate the rate of Internet data that can be carried through the DSRC channels not occupied by safety messages, under different conditions. To estimate economic gain as a function of throughput, we assume that mobile devices can use either cellular services or networks of connected vehicles, and that every bit carried on the vehicular network is one less bit on the cellular network. In a capacity-limited cellular network, a reduction of data from mobile devices that must be carried in the busy hour allows each cell tower to provide adequate capacity over a larger area, thereby reducing the number of costly towers that a cellular operator needs to cover a given region. We define the benefit of offload in a given scenario as the cost savings from reducing the number of cell towers. This is compared to the costs of DSRC RSUs, which quantity is assumed to be the one that maximizes the difference between benefits and costs. To examine the impact of infrastructure sharing, we estimate costs of deploying one infrastructure for safety and one for Internet, and compare that with costs obtained with different forms and levels of infrastructure sharing. We estimate the cost difference between an individual RSU used for safety, an RSU used for Internet access and an RSU suitable for both uses, with different assumptions about shared backhaul, shared power, and more. To consider the impact of spectrum policy, we have begun to redesign the packet-level simulation to support different amounts of spectrum and different types of sharing. This includes simulation of Wi-Fi hotspots and other devices that might share the band. In some scenarios, some or all of the spectrum used for intelligent transportation systems may also be used by devices that share without cooperation, meaning that they are sources of interference and congestion. In other scenarios, these devices cooperate, perhaps relaying a packet from a moving vehicle to a roadside unit, in accordance with the technical standard. In still other scenarios, unlicensed devices may operate, but only as secondary users by sensing the band and backing off when the proposed rules so dictate. These require change in the MAC-layer and network layer protocols, and this must be reflected in our simulation software. To consider the cost-effectiveness of these systems in the absence of a DSRC mandate, we will adopt a game theoretic approach, and assume that each vehicle owner will adopt DSRC when there is no mandate if and only if the savings from DSRC-based Internet access exceeds the cost of DSRC, which depends on each user’s Internet usage and time on the road, as well as how many other cars on the road already have DSRC, and how much roadside smart city infrastructure that has been deployed in a community. On the other hand, the amount of infrastructure that should be deployed depends greatly on how many vehicles are equipped with DSRC. In general, we would consider vehicles that are used heavily such as taxis, buses, and commercial trucks to be early adopters, and we would expect adoption to occur fastest in densely populated areas. We will identify equilibrium points at the community level; at equilibrium, a community would not change the amount of infrastructure deployed given the adoption rate of DSRC devices by vehicle owners, and no individual vehicle owner would not change the decision about whether to adopt DSRC given the amount of infrastructure deployed. We can then determine whether and where DSRC-based infrastructure is cost-effective at equillibrium. References  J. Wright et al., “National Connected Vehicle Field Infrastructure Footprint Analysis,” U.S. Department of Transportation Federal Highway Administration, 2014.  A. Ligo, J. M. Peha, J. Barros, "Throughput and Cost-Effectiveness of Vehicular Mesh Networks for Internet Access," Proceedings of IEEE 84th Vehicular Technology Conference (VTC), Sept. 2016.  R. Hallahan and J. M. Peha, "The Business Case of a Nationwide Wireless Network that Serves both Public Safety and Commercial Subscribers," Telecommunications Policy, vol. 35, no. 3, April 2011.  J. M. Peha, "A Public Private Approach to Public Safety Communications," Issues in Science and Technology, National Academy Press, vol. 29, no. 4, pp. 37-42, Summer 2013.  A. Ligo and J. M. Peha, "Is It Cost-Effective to Share Roadside Infrastructure for Non-Safety Use?," Proceedings of IEEE 85th Vehicular Technology Conference (VTC), June 2017.  J. Lowry, “APNewsBreak: Gov’t won’t pursue talking car mandate,” Associated Press, Nov. 1, 2017.  A. Ligo and J. M. Peha, "Spectrum Policies for Intelligent Transportation Systems," Telecommunications Policy Research Conference (TPRC), Sept. 2017.
We expect to complete a paper on how spectrum allocation and sharing policy would affect the capabilities of vehicular networks by the end of 2018. We then expect to focus on the cost-effectiveness of vehicular networks in the absence of a mandate from the U.S. Department of Transportation, and to produce informative and actionable results by the summer of 2019 about the cost-effectiveness of vehicular networks in equilibrium. Other issues described above will be addressed in subsequent years.
Not directly applicable. For this research, practical impact comes in part from outreach to policymakers rather than “deployment” per se. This includes policymakers at the Federal Communications Commission and the U.S. Department of Transportation, and state and local transportation agencies. In the past, the PI has discussed these issues with the Chairman of the FCC and other senior FCC officials, and presented results to a conference of Pennsylvania city officials. In future, we anticipate roughly one presentation to policymakers per year.
We expect to produce concrete analysis that will inform important policy decisions by providing quantitative results. With one more year of funding, we hope to provide analysis on the impact of spectrum policy that will be useful to spectrum policymakers at the Federal Communications Commission and its counterparts. This work should also show how spectrum policy should affect effective infrastructure strategies for local governments. We then expect to focus on the cost-effectiveness of vehicular networks in the absence of a mandate from the U.S. Department of Transportation. In particular, by the end of this grant, we hope to determine (i) equilibrium deployment levels in different communities, taking into account their population density and other relevant factors, (ii) an assessment of whether and where vehicular networks are more cost-effective than cellular systems as a means of providing Internet access, and (iii) whether and how communities interested in smart city applications can use this information to share infrastructure with commercial entities and thereby reduce the cost to governments of wireless infrastructure.
|email@example.com||Gong, Zhiqi||CMU ECE||Other||Student - Undergrad|
|firstname.lastname@example.org||Ligo, Alexandre||CMU EPP||Other||Student - PhD|
|email@example.com||Peha, Jon||CMU ECE/EPP||PI||Faculty - Tenured|
|Publication||Cost-Effectiveness of Sharing Roadside Infrastructure for Internet of Vehicles||Sept. 16, 2018, 10:11 a.m.|
|Publication||Throughput and Economics of DSRC-Based Internet of Vehicles||Sept. 16, 2018, 10:11 a.m.|
|Publication||Spectrum for Intelligent Transportation Systems: Allocation and Sharing||Sept. 16, 2018, 10:11 a.m.|
|Presentation||Sharing Connected Vehicle Infrastructure Between Governments and Internet Service Providers||Sept. 16, 2018, 10:11 a.m.|
|Presentation||Smart City Technologies for Local Governments||March 24, 2019, 9:47 a.m.|
|Presentation||Spectrum for Intelligent Transportation Systems: Allocation and Sharing||Sept. 16, 2018, 10:11 a.m.|
|Progress Report||173_Progress_Report_2018-09-30||Sept. 16, 2018, 10:11 a.m.|
|Publication||Connected Vehicles for Internet Access: Deployment and Spectrum Policies.||March 24, 2019, 9:31 a.m.|
|Progress Report||173_Progress_Report_2019-03-30||March 26, 2019, 7:43 a.m.|
|Presentation||Connected Vehicles for Internet Access: Implications for Governments and ISPs||July 17, 2019, 7:42 p.m.|
|Final Report||173_-_Final_Report.pdf||July 22, 2019, 5:19 a.m.|
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