Virtual Public Involvement: Lessons from the COVID-19 Pandemic


Report by the National Academies: “During the COVID-19 pandemic, transportation agencies’ most used public-engagement tools were virtual public meetings, social media, dedicated project websites or webpages, email blasts, and electronic surveys. As the pandemic subsides, virtual and hybrid models continue to provide opportunities and challenges.

The TRB National Cooperative Highway Research Program’s NCHRP Web-Only Document 349: Virtual Public Involvement: Lessons from the COVID-19 Pandemic discusses gaps that need to be addressed so that transportation agencies can better use virtual tools and techniques to facilitate two-way communication with the public…(More)”.

Improving Access and Management of Public Transit ITS Data


Report by the National Academies: “With the proliferation of automated vehicle location (AVL), automated passenger counters (APCs), and automated fare collection (AFC), transit agencies are collecting increasingly granular data on service performance, ridership, customer behavior, and financial recovery. While granular intelligent transportation systems (ITS) data can meaningfully improve transit decision-making, transit agencies face many challenges in accessing, validating, storing, and analyzing these data sets. These challenges are made more difficult in that the tools for managing and analyzing transit ITS data generally cannot, at this point, be shared across transit agencies because of variation in data collection systems and data formats. Multiple vendors provide ITS hardware and software, and data formats vary by vendor. Moreover, agencies may employ a patchwork of ITS that has been acquired and modified over time, leading to further consistency challenges.
Standardization of data structures and tools can help address these challenges. Not only can standardization streamline data transfer, validation, and database structuring, it encourages the development of analysis tools that can be used across transit agencies, as has been the case with route and schedule data, standardized in the General Transit Feed Specification (GTFS) format..(More)”.

AI-powered cameras to enforce bus lanes


Article by Chris Teale: “New York’s Metropolitan Transportation Authority will use an automated camera system to ensure bus lanes in New York City are free from illegally parked vehicles.

The MTA is partnering with Hayden AI to deploy Automated Bus Lane Enforcement camera systems to 300 buses, which will be mounted on the interior of the windshield and powered by artificial intelligence. The agency has the option to add the cameras to 200 more buses if it chooses.

Chris Carson, Hayden AI’s CEO and co-founder, said when the cameras detect an encroachment on a bus lane, they use real-time automated license plate recognition and edge computing to compile a packet of evidence that includes the time, date and location of the offense, as well as a brief video that shows the violator’s license plate. 

That information is encrypted and sent securely to the cloud, where MTA officials can access and analyze it for violations. If there is no encroachment on a bus lane, the cameras do not record anything…

An MTA spokesperson said the agency will also use data from the system to identify locations that have the highest instances of vehicles blocking bus lanes. New York City has 140 miles of bus lanes and has plans to build 150 more miles in the next four years, but congestion and lane violations from other road users slows the speed of the buses. The city already uses cameras and police patrols to attempt to enforce proper bus lane use…(More)”.

Efficient and stable data-sharing in a public transit oligopoly as a coopetitive game


Paper by Qi Liu and Joseph Y.J. Chow: “In this study, various forms of data sharing are axiomatized. A new way of studying coopetition, especially data-sharing coopetition, is proposed. The problem of the Bayesian game with signal dependence on actions is observed; and a method to handle such dependence is proposed. We focus on fixed-route transit service markets. A discrete model is first presented to analyze the data-sharing coopetition of an oligopolistic transit market when an externality effect exists. Given a fixed data sharing structure, a Bayesian game is used to capture the competition under uncertainty while a coalition formation model is used to determine the stable data-sharing decisions. A new method of composite coalition is proposed to study efficient markets. An alternative continuous model is proposed to handle large networks using simulation. We apply these models to various types of networks. Test results show that perfect information may lead to perfect selfishness. Sharing more data does not necessarily improve transit service for all groups, at least if transit operators remain non-cooperative. Service complementarity does not necessarily guarantee a grand data-sharing coalition. These results can provide insights on policy-making, like whether city authorities should enforce compulsory data-sharing along with cooperation between operators or setup a voluntary data-sharing platform…(More)”.

Parallel Worlds: Revealing the Inequity of Access to Urban Spaces in Mexico City Through Mobility Data


Paper by Emmanuel Letouzé et al: “The near-ubiquitous use of mobile devices generates mobility data that can paint pictures of urban behavior at unprecedented levels of granularity and complexity. In the current period of intense sociopolitical polarization, mobility data can help reveal which urban spaces serve to attenuate or accentuate socioeconomic divides. If urban spaces served to bridge class divides, people from different socioeconomic groups would be prone to mingle in areas further removed from their homes, creating opportunities for sharing experiences in the physical world. In an opposing scenario, people would remain among neighbors and peers, creating “local urban bubbles” that reflect and reinforce social inequities and their adverse effects on social mixity, cohesion, and trust. These questions are especially salient in cities with high levels of socioeconomic inequality, such as Mexico City.

Building on a joint research project between Data-Pop Alliance and Oxfam Mexico titled “Mundos Paralelos” [Parallel Worlds], this paper leverages privacy-preserving mobility data to unveil the unequal use and appropriation of urban spaces by the inhabitants of Mexico City. This joint research harnesses a year (2018–2019) of anonymized mobility data to perform mobility and behavioral analysis of specific groups at high spatial resolution. Its main findings suggest that Mexico City is a spatially fragmented, even segregated city: although distinct socioeconomic groups do meet in certain spaces, a pattern emerges where certain points of interest are exclusive to the high- and low-income groups analyzed in this paper. The results demonstrate that spatial inequality in Mexico City is marked by unequal access to government services and cultural sites, which translates into unequal experiences of urban life and biased access to the city. The paper concludes with a series of public policy recommendations to foster a more equitable and inclusive appropriation of public space…(More)”.

A New Model for Saving Lives on Roads Around the World


Article by Krishen Mehta & Piyush Tewari: “…In 2016, SaveLIFE Foundation (SLF), an Indian non-profit organization, introduced the Zero Fatality Corridor (ZFC) solution, which has, since its inception, delivered an unprecedented reduction in road crash fatalities on the stretches of road where it has been deployed. The ZFC solution has adapted and added to the Safe System Approach, traditionally a western concept, to make it suitable for Indian conditions and requirements.

The Safe System Approach recognizes that people are fallible and can make mistakes that may be fatal for them or their fellow road-users—irrespective of how well they are trained.

The ZFC model, in turn, is an innovation designed specifically to accommodate the realities, resources, and existing infrastructure in low- and middle-income countries, which are vastly different from their developed counterparts. For example, unlike developed nations, people in low- and middle-income countries often live closer to the highways, and use them on a daily basis on foot or through traditional and slower modes of transportation. This gives rise to high crash conflict areas.

Some of the practices that are a part of the ZFC solution include optimized placement of ambulances at high-fatality locations, the utilization of drones to identify parked vehicles to preemptively prevent rear-end collisions, and road engineering solutions unique to the realities of countries like India. The ZFC model has helped create a secure environment specific to such countries with safer roads, safer vehicles, safer speeds, safer drivers, and rapid post-crash response.

The ZFC model was first deployed in 2016 on the Mumbai-Pune Expressway (MPEW) in Maharashtra, through a collaboration between SLF, Maharashtra State Road Development Corporation (MSRDC), and automaker Mahindra & Mahindra. From 2010 to 2016, the 95-kilometer stretch witnessed 2,579 crashes and 887 fatalities, making it one of India’s deadliest roads…(More)”.

Roadside safety messages increase crashes by distracting drivers


Article by Jonathan Hall and Joshua Madsen: “Behavioural interventions involve gently suggesting that people reconsider or change specific undesirable behaviours. They are a low-cost, easy-to-implement and increasingly common tool used by policymakers to encourage socially desirable behaviours.

Examples of behavioural interventions include telling people how their electricity usage compares to their neighbours or sending text messages reminding people to pay fines.

Many of these interventions are expressly designed to “seize people’s attention” at a time when they can take the desired action. Unfortunately, seizing people’s attention can crowd out other, more important considerations, and cause even a simple intervention to backfire with costly individual and social consequences.

One such behavioural intervention struck us as odd: Several U.S. states display year-to-date fatality statistics (number of deaths) on roadside dynamic message signs (DMSs). The hope is that these sobering messages will reduce traffic crashesa leading cause of death of five- to 29-year-olds worldwide. Perhaps because of its low cost and ease of implementation, at least 28 U.S. states have displayed fatality statistics at least once since 2012. We estimate that approximately 90 million drivers have been exposed to such messages.

a road sign saying 1669 DEATHS THIS YEAR ON TEXAS ROADS
A roadside dynamic messaging sign in Texas, displaying the death toll from road crashes. (Jonathan Hall), Author provided

Startling results

As academic researchers with backgrounds in information disclosure and transportation policy, we teamed up to investigate and quantify the effects of these messages. What we found startled us.

Contrary to policymakers’ expectations (and ours), we found that displaying fatality messages increases the number of crashes…(More)”.

Citizen science and the potential for mobility policy – Introducing the Bike Barometer


Paper by Tom Storme et al: “In this paper, we report on a citizen science pilot project involving adolescents who digitize and assess their daily home-to-school routes in different school neighborhoods in Flanders (Belgium). As part of this pilot project, a web-based platform, called the “Bike Barometer” (“Fietsbarometer” in Dutch) was developed. We introduce the tool in this paper and summarize the insights gained from the pilot. From the official launch of the platform in March until the end of the pilot in June 2020, 1,256 adolescents from 31 schools digitized 5657 km of roads, of which 3,750 km were evaluated for cycling friendliness and safety. The added value and potential of citizen science in general and the platform in particular are illustrated. The results offer detailed (spatial) insights into local safety conditions for Flanders and for specific school neighborhoods. The potential for mobility policy is twofold: (i) the cycling friendliness and traffic flows in school environments can be monitored over time and (ii) the platform has the potential to create local ecosystems of adolescents and teachers (both considered citizen scientists here) and policymakers. Two key pitfalls are identified as well: the need for a critical mass of citizen scientists and a minimum level of commitment required from local policymakers. By illustrating the untapped potential of citizen science, we argue that the intersection between citizen science and local policymaking in the domain of mobility deserves much more attention….(More)”.

Can behavioral interventions be too salient? Evidence from traffic safety messages



Article by Jonathan D. Hall and Joshua M. Madsen: “Policy-makers are increasingly turning to behavioral interventions such as nudges and informational campaigns to address a variety of issues. Guidebooks say that these interventions should “seize people’s attention” at a time when they can take the desired action, but little consideration has been given to the costs of seizing one’s attention and to the possibility that these interventions may crowd out other, more important, considerations. We estimated these costs in the context of a widespread, seemingly innocuous behavioral campaign with the stated objective of reducing traffic crashes. This campaign displays the year-to-date number of statewide roadside fatalities (fatality messages) on previously installed highway dynamic message signs (DMSs) and has been implemented in 28 US states.

We estimated the impact of displaying fatality messages using data from Texas. Texas provides an ideal setting because the Texas Department of Transportation (TxDOT) decided to show fatality messages starting in August 2012 for 1 week each month: the week before TxDOT’s monthly board meeting (campaign weeks). This allows us to measure the impact of the intervention, holding fixed the road segment, year, month, day of week, and time of day. We used data on 880 DMSs and all crashes occurring in Texas between 1 January 2010 and 31 December 2017 to investigate the effects of this safety campaign. We estimated how the intervention affects crashes near DMSs as well as statewide. As placebo tests, we estimated whether the chosen weeks inherently differ using data from before TxDOT started displaying fatality messages and data from upstream of DMSs.

Contrary to policy-makers’ expectations, we found that displaying fatality messages increases the number of traffic crashes. Campaign weeks realize a 1.52% increase in crashes within 5 km of DMSs, slightly diminishing to a 1.35% increase over the 10 km after DMSs. We used instrumental variables to recover the effect of displaying a fatality message and document a significant 4.5% increase in the number of crashes over 10 km. The effect of displaying fatality messages is comparable to raising the speed limit by 3 to 5 miles per hour or reducing the number of highway troopers by 6 to 14%. We also found that the total number of statewide on-highway crashes is higher during campaign weeks. The social costs of these fatality messages are large: Back-of-the-envelope calculations suggest that this campaign causes an additional 2600 crashes and 16 fatalities per year in Texas alone, with a social cost of $377 million per year…(More)”.

Using ANPR data to create an anonymized linked open dataset on urban bustle


Paper by Brecht Van de Vyvere & Pieter Colpaert: “ANPR cameras allow the automatic detection of vehicle license plates and are increasingly used for law enforcement. However, also statistical data generated by ANPR cameras are a potential source of urban insights. In order for this data to reach its full potential for policy-making, we research how this data can be shared in digital twins, with researchers, for a diverse set of machine learning models, and even Open Data portals. This article’s key objective is to find a way to anonymize and aggregate ANPR data in a way that it still can provide useful visualizations for local decision making. We introduce an approach to aggregate the data with geotemporal binning and publish it by combining nine existing data specifications. We implemented the approach for the city of Kortrijk (Belgium) with 43 ANPR cameras, developed the ANPR Metrics tool to generate the statistical data and dashboards on top of the data, and tested whether mobility experts from the city could deduct valuable insights. We present a couple of insights that were found as a result, as a proof that anonymized ANPR data complements their currently used traffic analysis tools, providing a valuable source for data-driven policy-making…(More)”.