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      One autonomous taxi, please

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      If you don’t get seasick, an autonomous boat might be the right mode of transportation for you. 

      Scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Senseable City Laboratory, together with Amsterdam Institute for Advanced Metropolitan Solutions (AMS Institute) in the Netherlands, have now created the final project in their self-navigating trilogy: a full-scale, fully autonomous robotic boat that’s ready to be deployed along the canals of Amsterdam. 

      “Roboat” has come a long way since the team first started prototyping small vessels in the MIT pool in late 2015. Last year, the team released their half-scale, medium model that was 2 meters long and demonstrated promising navigational prowess. 

      This year, two full-scale Roboats were launched, proving more than just proof-of-concept: these craft can comfortably carry up to five people, collect waste, deliver goods, and provide on-demand infrastructure. 

      The boat looks futuristic — it’s a sleek combination of black and gray with two seats that face each other, with orange block letters on the sides that illustrate the makers’ namesakes. It’s a fully electrical boat with a battery that’s the size of a small chest, enabling up to 10 hours of operation and wireless charging capabilities. 

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      Autonomous Roboats set sea in the Amsterdam canals and can comfortably carry up to five people, collect waste, deliver goods, and provide on-demand infrastructure.

      “We now have higher precision and robustness in the perception, navigation, and control systems, including new functions, such as close-proximity approach mode for latching capabilities, and improved dynamic positioning, so the boat can navigate real-world waters,” says Daniela Rus, MIT professor of electrical engineering and computer science and director of CSAIL. “Roboat’s control system is adaptive to the number of people in the boat.” 

      To swiftly navigate the bustling waters of Amsterdam, Roboat needs a meticulous fusion of proper navigation, perception, and control software. 

      Using GPS, the boat autonomously decides on a safe route from A to B, while continuously scanning the environment to  avoid collisions with objects, such as bridges, pillars, and other boats.

      To autonomously determine a free path and avoid crashing into objects, Roboat uses lidar and a number of cameras to enable a 360-degree view. This bundle of sensors is referred to as the “perception kit” and lets Roboat understand its surroundings. When the perception picks up an unseen object, like a canoe, for example, the algorithm flags the item as “unknown.” When the team later looks at the collected data from the day, the object is manually selected and can be tagged as “canoe.” 

      The control algorithms — similar to ones used for self-driving cars — function a little like a coxswain giving orders to rowers, by translating a given path into instructions toward the “thrusters,” which are the propellers that help the boat move.  

      If you think the boat feels slightly futuristic, its latching mechanism is one of its most impressive feats: small cameras on the boat guide it to the docking station, or other boats, when they detect specific QR codes. “The system allows Roboat to connect to other boats, and to the docking station, to form temporary bridges to alleviate traffic, as well as floating stages and squares, which wasn’t possible with the last iteration,” says Carlo Ratti, professor of the practice in the MIT Department of Urban Studies and Planning (DUSP) and director of the Senseable City Lab. 

      Roboat, by design, is also versatile. The team created a universal “hull” design — that’s the part of the boat that rides both in and on top of the water. While regular boats have unique hulls, designed for specific purposes, Roboat has a universal hull design where the base is the same, but the top decks can be switched out depending on the use case.

      “As Roboat can perform its tasks 24/7, and without a skipper on board, it adds great value for a city. However, for safety reasons it is questionable if reaching level A autonomy is desirable,” says Fabio Duarte, a principal research scientist in DUSP and lead scientist on the project. “Just like a bridge keeper, an onshore operator will monitor Roboat remotely from a control center. One operator can monitor over 50 Roboat units, ensuring smooth operations.”

      The next step for Roboat is to pilot the technology in the public domain. “The historic center of Amsterdam is the perfect place to start, with its capillary network of canals suffering from contemporary challenges, such as mobility and logistics,” says Stephan van Dijk, director of innovation at AMS Institute. 

      Previous iterations of Roboat have been presented at the IEEE International Conference on Robotics and Automation. The boats will be unveiled on Oct. 28 in the waters of Amsterdam. 

      Ratti, Rus, Duarte, and Dijk worked on the project alongside Andrew Whittle, MIT’s Edmund K Turner Professor in civil and environmental engineering; Dennis Frenchman, professor at MIT’s Department of Urban Studies and Planning; and Ynse Deinema of AMS Institute. The full team can be found at Roboat’s website. The project is a joint collaboration with AMS Institute. The City of Amsterdam is a project partner. More

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      Deep learning helps predict traffic crashes before they happen

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      Today’s world is one big maze, connected by layers of concrete and asphalt that afford us the luxury of navigation by vehicle. For many of our road-related advancements — GPS lets us fire fewer neurons thanks to map apps, cameras alert us to potentially costly scrapes and scratches, and electric autonomous cars have lower fuel costs — our safety measures haven’t quite caught up. We still rely on a steady diet of traffic signals, trust, and the steel surrounding us to safely get from point A to point B. 

      To get ahead of the uncertainty inherent to crashes, scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Qatar Center for Artificial Intelligence developed a deep learning model that predicts very high-resolution crash risk maps. Fed on a combination of historical crash data, road maps, satellite imagery, and GPS traces, the risk maps describe the expected number of crashes over a period of time in the future, to identify high-risk areas and predict future crashes. 

      Typically, these types of risk maps are captured at much lower resolutions that hover around hundreds of meters, which means glossing over crucial details since the roads become blurred together. These maps, though, are 5×5 meter grid cells, and the higher resolution brings newfound clarity: The scientists found that a highway road, for example, has a higher risk than nearby residential roads, and ramps merging and exiting the highway have an even higher risk than other roads. 

      “By capturing the underlying risk distribution that determines the probability of future crashes at all places, and without any historical data, we can find safer routes, enable auto insurance companies to provide customized insurance plans based on driving trajectories of customers, help city planners design safer roads, and even predict future crashes,” says MIT CSAIL PhD student Songtao He, a lead author on a new paper about the research. 

      Even though car crashes are sparse, they cost about 3 percent of the world’s GDP and are the leading cause of death in children and young adults. This sparsity makes inferring maps at such a high resolution a tricky task. Crashes at this level are thinly scattered — the average annual odds of a crash in a 5×5 grid cell is about one-in-1,000 — and they rarely happen at the same location twice. Previous attempts to predict crash risk have been largely “historical,” as an area would only be considered high-risk if there was a previous nearby crash. 

      The team’s approach casts a wider net to capture critical data. It identifies high-risk locations using GPS trajectory patterns, which give information about density, speed, and direction of traffic, and satellite imagery that describes road structures, such as the number of lanes, whether there’s a shoulder, or if there’s a large number of pedestrians. Then, even if a high-risk area has no recorded crashes, it can still be identified as high-risk, based on its traffic patterns and topology alone. 

      To evaluate the model, the scientists used crashes and data from 2017 and 2018, and tested its performance at predicting crashes in 2019 and 2020. Many locations were identified as high-risk, even though they had no recorded crashes, and also experienced crashes during the follow-up years.

      “Our model can generalize from one city to another by combining multiple clues from seemingly unrelated data sources. This is a step toward general AI, because our model can predict crash maps in uncharted territories,” says Amin Sadeghi, a lead scientist at Qatar Computing Research Institute (QCRI) and an author on the paper. “The model can be used to infer a useful crash map even in the absence of historical crash data, which could translate to positive use for city planning and policymaking by comparing imaginary scenarios.” 

      The dataset covered 7,500 square kilometers from Los Angeles, New York City, Chicago and Boston. Among the four cities, L.A. was the most unsafe, since it had the highest crash density, followed by New York City, Chicago, and Boston. 

      “If people can use the risk map to identify potentially high-risk road segments, they can take action in advance to reduce the risk of trips they take. Apps like Waze and Apple Maps have incident feature tools, but we’re trying to get ahead of the crashes — before they happen,” says He. 

      He and Sadeghi wrote the paper alongside Sanjay Chawla, research director at QCRI, and MIT professors of electrical engineering and computer science Mohammad Alizadeh, ​​Hari Balakrishnan, and Sam Madden. They will present the paper at the 2021 International Conference on Computer Vision. More

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      Finding common ground in Malden

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      When disparate groups convene around a common goal, exciting things can happen.

      That is the inspiring story unfolding in Malden, Massachusetts, a city of about 60,000 — nearly half people of color — where a new type of community coalition continues to gain momentum on its plan to build a climate-resilient waterfront park along its river. The Malden River Works (MRW) project, recipient of the inaugural Leventhal City Prize, is seeking to connect to a contiguous greenway network where neighboring cities already have visitors coming to their parks and enjoying recreational boating. More important, the MRW is changing the model for how cities address civic growth, community engagement, equitable climate resilience, and environmental justice.                                                                                        

      The MRW’s steering committee consists of eight resident leaders of color, a resident environmental advocate, and three city representatives. One of the committee’s primary responsibilities is providing direction to the MRW’s project team, which includes urban designers, watershed and climate resilience planners, and a community outreach specialist. MIT’s Kathleen Vandiver, director of the Community Outreach Education and Engagement Core at MIT’s Center for Environmental Health Sciences (CEHS), and Marie Law Adams MArch ’06, a lecturer in the School of Architecture and Planning’s Department of Urban Studies and Planning (DUSP), serve on the project team.

      “This governance structure is somewhat unusual,” says Adams. “More typical is having city government as the primary decision-maker. It is important that one of the first things our team did was build a steering committee that is the decision maker on this project.”

      Evan Spetrini ’18 is the senior planner and policy manager for the Malden Redevelopment Authority and sits on both the steering committee and project team. He says placing the decision-making power with the steering committee and building it to be representative of marginalized communities was intentional. 

      “Changing that paradigm of power and decision-making in planning processes was the way we approached social resilience,” says Spetrini. “We have always intended this project to be a model for future planning projects in Malden.”

      This model ushers in a new history chapter for a city founded in 1640.

      Located about six miles north of Boston, Malden was home to mills and factories that used the Malden River for power, and a site for industrial waste over the last two centuries. Decades after the city’s industrial decline, there is little to no public access to the river. Many residents were not even aware there was a river in their city. Before the project was under way, Vandiver initiated a collaborative effort to evaluate the quality of the river’s water. Working with the Mystic River Watershed Association, Gradient Corporation, and CEHS, water samples were tested and a risk analysis conducted.

      “Having the study done made it clear the public could safely enjoy boating on the water,” says Vandiver. “It was a breakthrough that allowed people to see the river as an amenity.”

      A team effort

      Marcia Manong had never seen the river, but the Malden resident was persuaded to join the steering committee with the promise the project would be inclusive and of value to the community. Manong has been involved with civic engagement most of her life in the United States and for 20 years in South Africa.

      “It wasn’t going to be a marginalized, token-ized engagement,” says Manong. “It was clear to me that they were looking for people that would actually be sitting at the table.”

      Manong agreed to recruit additional people of color to join the team. From the beginning, she says, language was a huge barrier, given that nearly half of Malden’s residents do not speak English at home. Finding the translation efforts at their public events to be inadequate, the steering committee directed more funds to be made available for translation in several languages when public meetings began being held over Zoom this past year.

      “It’s unusual for most cities to spend this money, but our population is so diverse that we require it,” says Manong. “We have to do it. If the steering committee wasn’t raising this issue with the rest of the team, perhaps this would be overlooked.”

      Another alteration the steering committee has made is how the project engages with the community. While public attendance at meetings had been successful before the pandemic, Manong says they are “constantly working” to reach new people. One method has been to request invitations to attend the virtual meetings of other organizations to keep them apprised of the project.

      “We’ve said that people feel most comfortable when they’re in their own surroundings, so why not go where the people are instead of trying to get them to where we are,” says Manong.

      Buoyed by the $100,000 grant from MIT’s Norman B. Leventhal Center for Advanced Urbanism (LCAU) in 2019, the project team worked with Malden’s Department of Public Works, which is located along the river, to redesign its site and buildings and to study how to create a flood-resistant public open space as well as an elevated greenway path, connecting with other neighboring cities’ paths. The park’s plans also call for 75 new trees to reduce urban heat island effect, open lawn for gathering, and a dock for boating on the river.

      “The storm water infrastructure in these cities is old and isn’t going to be able to keep up with increased precipitation,” says Adams. “We’re looking for ways to store as much water as possible on the DPW site so we can hold it and release it more gradually into the river to avoid flooding.”

      The project along the 2.3-mile-long river continues to receive attention. Recently, the city of Malden was awarded a 2021 Accelerating Climate Resilience Grant of more than $50,000 from the state’s Metropolitan Area Planning Council and the Barr Foundation to support the project. Last fall, the project was awarded a $150,015 Municipal Vulnerability Preparedness Action Grant. Both awards are being directed to fund engineering work to refine the project’s design.

      “We — and in general, the planning profession — are striving to create more community empowerment in decision-making as to what happens to their community,” says Spetrini. “Putting the power in the community ensures that it’s actually responding to the needs of the community.”

      Contagious enthusiasm

      Manong says she’s happy she got involved with the project and believes the new governance structure is making a difference.

      “This project is definitely engaging with communities of color in a manner that is transformative and that is looking to build a long-lasting power dynamic built on trust,” she says. “It’s a new energized civic engagement and we’re making that happen. It’s very exciting.”

      Spetrini finds the challenge of creating an open space that’s publicly accessible and alongside an active work site professionally compelling.

      “There is a way to preserve the industrial employment base while also giving the public greater access to this natural resource,” he says. “It has real implications for other communities to follow this type of model.”

      Despite the pandemic this past year, enthusiasm for the project is palpable. For Spetrini, a Malden resident, it’s building “the first significant piece of what has been envisioned as the Malden River Greenway.” Adams sees the total project as a way to build social resilience as well as garnering community interest in climate resilience. For Vandiver, it’s the implications for improved community access.

      “From a health standpoint, everybody has learned from Covid-19 that the health aspects of walking in nature are really restorative,” says Vandiver. “Creating greater green space gives more attention to health issues. These are seemingly small side benefits, but they’re huge for mental health benefits.”

      Leventhal City Prize’s next cycle

      The Leventhal City Prize was established by the LCAU to catalyze innovative, interdisciplinary urban design, and planning approaches worldwide to improve both the environment and the quality of life for residents. Support for the LCAU was provided by the Muriel and Norman B. Leventhal Family Foundation and the Sherry and Alan Leventhal Family Foundation.

      “We’re thrilled with inaugural recipients of the award and the extensive work they’ve undertaken that is being held up as an exemplary model for others to learn from,” says Sarah Williams, LCAU director and a professor in DUSP. “Their work reflects the prize’s intent. We look forward to catalyzing these types of collaborative partnership in the next prize cycle.”

      Submissions for the next cycle of the Leventhal City Prize will open in early 2022.    More

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      Study finds lockdowns effective at reducing travel in Sierra Leone

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      Throughout the Covid-19 pandemic, governments have used data on people’s movements to inform strategies for containing the spread of the virus. In Europe and the United States, for example, contact-tracing apps have used Bluetooth signals in smartphones to alert people when they’ve spent time near app users who have tested positive for Covid-19. 

      But how can governments make evidence-based decisions in countries where such fine-grained data isn’t available? In recent findings, MIT researchers, in collaboration with Sierra Leone’s government, use cell tower records in Sierra Leone to show that people were traveling less during lockdowns. “When the government implemented novel three-day lockdowns, there was a dual aim to reduce virus spread and also limit social impacts, like increased hunger or food insecurity,” says Professor Lily L. Tsai, MIT Governance Lab’s (MIT GOV/LAB) director and founder. “We wanted to know if shorter lockdowns would be successful.”   

      The research was conducted by MIT GOV/LAB and MIT’s Civic Data Design Lab (CDDL), in partnership with Sierra Leone’s Directorate for Science, Innovation and Technology (DSTI) and Africell, a wireless service provider. The findings will be published as a chapter in the book “Urban Informatics and Future Cities,” a selection of research submitted to the 2021 Computational Urban Planning and Urban Management conference. 

      A proxy for mobility: cell tower records

      Any time someone’s cellphone sends or receives a text, or makes or receives a call, the nearest cell tower is pinged. The tower collects some data (call-detail records, or CDRs), including the date and time of the event and the phone number. By tracking which towers a certain (anonymized) phone number pings, the researchers could approximately measure how much someone was moving around.  

      These measurements showed that, on average, people were traveling less during lockdowns than before lockdowns. Professor Sarah Williams, CDDL’s director, says the analysis also revealed frequently traveled routes, which “allow the government to develop region-specific lockdowns.” 

      While more fine-grained GPS data from smartphones paint a more accurate picture of movement, “there just isn’t a systematic effort in many developing countries to build the infrastructure to collect this data,” says Innocent Ndubuisi-Obi Jr., an MIT GOV/LAB research associate. “In many cases, the closest thing we can use as a proxy for mobility is CDR data.”

      Measuring the effectiveness of lockdowns

      Sierra Leone’s government imposed the three-day lockdown, which required people stay in their homes, in April 2020. A few days after the lockdown ended, a two-week inter-district travel ban began. “Analysis of aggregated CDRs was the quickest means to understanding mobility prior to and during lockdowns,” says Michala Mackay, DSTI’s director and chief operating officer. 

      The data MIT and DSTI received was anonymized — an essential part of ensuring the privacy of the individuals whose data was used. 

      Extracting meaning from the data, though, presented some challenges. Only about 75 percent of adults in Sierra Leone own cellphones, and people sometimes share phones. So the towers pinged by a specific phone might actually represent the movement of several people, and not everyone’s movement will be captured by cell towers. 

      Furthermore, some districts in Sierra Leone have significantly fewer towers than others. When the data were collected, Falaba, a rural district in the northeast, had only five towers, while over 100 towers were clustered in and around Freetown, the capital. In areas with very few towers, it’s harder to detect changes in how much people are traveling. 

      Since each district had a unique tower distribution, the researchers looked at each district separately, establishing a baseline for average distance traveled in each district before the lockdowns, then measuring how movement compared to this average during lockdowns. They found that travel to other districts declined in every district, by as much as 72 percent and by as little as 16 percent. Travel within districts also dropped in all but one district. 

      This map shows change in average distance traveled per trip to other districts in Sierra Leone in 2020.

      Image courtesy of the MIT GOV/LAB and CDDL.

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      Lockdowns have greater costs in poorer areas

      While movement did decline in all districts, the effect was less dramatic in poorer, more sparsely populated areas. This finding was to be expected; other studies have shown that poorer people often can’t afford to comply with lockdowns, since they can’t take time off work or need to travel to get food. Evidence showing how lockdowns are less effective in poorer areas highlights the importance of distributing resources to poorer areas during crises, which could both provide support during a particularly challenging time and make it less costly for people to comply with social distancing measures. 

      “In low-income communities that demonstrated moderate or low compliance, one of the most common reasons why people left their homes was to search for water,” says Mackay. “A policy takeaway was that lockdowns should only be implemented in extreme cases and for no longer than three days at a time.”

      Throughout the project, the researchers collaborated intimately with DSTI. “This meant government officials learned along with the MIT researchers and added crucial local knowledge,” says Williams. “We hope this model can be replicated elsewhere — especially during crises.” 

      The researchers will be developing an MITx course teaching government officials and MIT students how to collaboratively use CDR data during crises, with a focus on how to do the analysis in a way that protects people’s privacy.

      Ndubuisi-Obi Jr. also has led a training on CDR analysis for Sierra Leonean government officials and has written a guide on how policymakers can use CDRs safely and effectively. “Some of these data sets will help us answer really important policy questions, and we have to balance that with the privacy risks,” he says. More