scholarly journals Mobility Trends and their effect on Traffic Safety During the Covid-19 Pandemic: Case Study Republic of Croatia

2021 ◽  
Vol 67 (4) ◽  
pp. 17-20
Author(s):  
Ana Globočnik Žunac ◽  
Predrag Brlek ◽  
Ivan Cvitković ◽  
Goran Kaniški
Keyword(s):  
Traffic Safety ◽  
Travel Behavior ◽  
Human Mobility ◽  
Transport Systems ◽  
Data Set ◽  
Mobile Location ◽  
Location Data ◽  
Wide Availability ◽  
Accident Data ◽  
The Impact

Safety analysis focuses on how traffic safety can change while mobility analysis is used to determine how people change travel behavior. The integration of mobility, safety and behavioral data related to COVID-19 can provide valuable insights to decision makers. Wide availability of mobile sensors has given us the opportunity to be able to assess changes in the performance and mobility of transport systems in, almost real time. The researchers also measured the impact of COVID-19 on human mobility using public mobile location data available from many companies such as Google and Apple, which is very useful for changing human mobility. The platforms produce aggregated metrics of daily mobility, including the purpose of travel, the mode of travel, and imputations of social demographics. Based on a comprehensive data set of people who participated in the collected accident data and mobile device data, we record the impact of COVID-19 on traffic safety. The paper systematically and statistically approaches the assessment of road safety in Croatia during the COVID-19 pandemic.

scholarly journals Mobility Trends and their effect on Traffic Safety During the Covid-19 Pandemic: Case Study Republic of Croatia

2021 ◽  
Vol 67 (4) ◽  
pp. 17-20
Author(s):  
Ana Globočnik Žunac ◽  
Predrag Brlek ◽  
Ivan Cvitković ◽  
Goran Kaniški
Keyword(s):  
Traffic Safety ◽  
Travel Behavior ◽  
Human Mobility ◽  
Transport Systems ◽  
Data Set ◽  
Mobile Location ◽  
Location Data ◽  
Wide Availability ◽  
Accident Data ◽  
The Impact

Safety analysis focuses on how traffic safety can change while mobility analysis is used to determine how people change travel behavior. The integration of mobility, safety and behavioral data related to COVID-19 can provide valuable insights to decision makers. Wide availability of mobile sensors has given us the opportunity to be able to assess changes in the performance and mobility of transport systems in, almost real time. The researchers also measured the impact of COVID-19 on human mobility using public mobile location data available from many companies such as Google and Apple, which is very useful for changing human mobility. The platforms produce aggregated metrics of daily mobility, including the purpose of travel, the mode of travel, and imputations of social demographics. Based on a comprehensive data set of people who participated in the collected accident data and mobile device data, we record the impact of COVID-19 on traffic safety. The paper systematically and statistically approaches the assessment of road safety in Croatia during the COVID-19 pandemic.

scholarly journals Assessing inequality, irregularity, and severity regarding road traffic safety during COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lei Lin ◽  
Feng Shi ◽  
Weizi Li
Keyword(s):  
New York ◽  
Los Angeles ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Human Mobility ◽  
Critical Conditions ◽  
Road Traffic Safety ◽  
Accident Data ◽  
The Impact

AbstractCOVID-19 has affected every sector of our society, among which human mobility is taking a dramatic change due to quarantine and social distancing. We investigate the impact of the pandemic and subsequent mobility changes on road traffic safety. Using traffic accident data from the city of Los Angeles and New York City, we find that the impact is not merely a blunt reduction in traffic and accidents; rather, (1) the proportion of accidents unexpectedly increases for “Hispanic” and “Male” groups; (2) the “hot spots” of accidents have shifted in both time and space and are likely moved from higher-income areas (e.g., Hollywood and Lower Manhattan) to lower-income areas (e.g., southern LA and southern Brooklyn); (3) the severity level of accidents decreases with the number of accidents regardless of transportation modes. Understanding those variations of traffic accidents not only sheds a light on the heterogeneous impact of COVID-19 across demographic and geographic factors, but also helps policymakers and planners design more effective safety policies and interventions during critical conditions such as the pandemic.

Riding the rails of removal: The impact of railways on border controls and expulsion practices

2019 ◽  
Vol 40 (2) ◽  
pp. 189-210
Author(s):  
Torsten Feys
Keyword(s):  
Nineteenth Century ◽  
Human Mobility ◽  
Transport Infrastructure ◽  
Transport Systems ◽  
Border Control ◽  
Migration Policies ◽  
Railway Networks ◽  
Central Pillar ◽  
Border Controls ◽  
The Impact

Nineteenth-century Belgian authorities liked to consider themselves as liberal towards migrants, but the 340,000 expulsions carried out between 1835 and 1913 paint a different picture. This article assesses how the development of Belgian railway networks influenced controls of entry and expulsion practices through seven borderland hubs with international rail connections. It first details how control stations followed changes in transport infrastructure and that some form of border control on human mobility was upheld throughout the nineteenth century. Second, it explains how railways drastically changed expulsions allowing the Sûreté Publique (i.e. the Belgian Foreigners Police) to establish a well-oiled deportation apparatus which became a central pillar of migration policies. Using Walters' concept of “viapolitics”, it details how transport systems and infrastructure shaped the state's ability to govern migrants.

scholarly journals Lockdown related travel behavior undermines the containment of SARS-CoV-2

2020 ◽  
Author(s):  
Nishant Kishore ◽  
Rebecca Kahn ◽  
Pamela P. Martinez ◽  
Pablo M. De Salazar ◽  
Ayesha S. Mahmud ◽  
...  
Keyword(s):  
Rural Areas ◽  
Travel Behavior ◽  
Human Mobility ◽  
Unintended Consequences ◽  
Disease Spread ◽  
Mobility Patterns ◽  
Long Distance ◽  
Mobility Data ◽  
Travel Restrictions ◽  
The Impact

ABSTRACTIn response to the SARS-CoV-2 pandemic, unprecedented policies of travel restrictions and stay-at-home orders were enacted around the world. Ultimately, the public’s response to announcements of lockdowns - defined here as restrictions on both local movement or long distance travel - will determine how effective these kinds of interventions are. Here, we measure the impact of the announcement and implementation of lockdowns on human mobility patterns by analyzing aggregated mobility data from mobile phones. We find that following the announcement of lockdowns, both local and long distance movement increased. To examine how these behavioral responses to lockdown policies may contribute to epidemic spread, we developed a simple agent-based spatial model. We find that travel surges following announcements of lockdowns can increase seeding of the epidemic in rural areas, undermining the goal of the lockdown of preventing disease spread. Appropriate messaging surrounding the announcement of lockdowns and measures to decrease unnecessary travel are important for preventing these unintended consequences of lockdowns.

scholarly journals Traffic accident analysis based on C4.5 algorithm in WEKA

2019 ◽  
Vol 272 ◽  
pp. 01035 ◽  
Author(s):  
Jiajia Li ◽  
Jie He ◽  
Ziyang Liu ◽  
Hao Zhang ◽  
Chen Zhang
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Safety Management ◽  
Depth Information ◽  
Highway Traffic ◽  
Safety Issues ◽  
C4.5 Algorithm ◽  
Accident Data ◽  
The Impact

At present, China is in a period of steady development of highways. At the same time, traffic safety issues are becoming increasingly serious. Data mining technology is an effective method for analysing traffic accidents. In-depth information mining of traffic accident data is conducive to accident prevention and traffic safety management. Based on the data of Wenli highway traffic accidents from 2006 to 2013, this study selected factors including time factor, linear factor and driver characteristics as research indicators, and established the decision tree using C4.5 algorithm in WEKA to explore the impact of various factors on the accident. According to the degree of contribution of each variable to the classification effect of the model, various modes affecting the type of the accident are obtained and the overall prediction accuracy is about 80%.

Reshaping the Region

2015 ◽  
Vol 2537 (1) ◽  
pp. 33-41
Author(s):  
Stephanie Pollack ◽  
Anna Gartsman ◽  
Timothy Reardon ◽  
Meghna Hari
Keyword(s):  
Land Use ◽  
Public Transportation ◽  
Travel Behavior ◽  
Massachusetts Bay ◽  
Data Set ◽  
Transit System ◽  
Transit Systems ◽  
Commuter Rail ◽  
In Transit ◽  
The Impact

The American Public Transportation Association's use of a “land use multiplier” as part of its methodology for calculating greenhouse gas reduction from transit has increased interest in methodologies that quantify the impact of transit systems on land use and vehicle miles traveled. Such transit leverage, however, is frequently evaluated for urbanized areas, although transit systems serve only a small proportion of those areas. If transit leverage is stronger in areas closer to transit stations, studies based on larger geographies may underestimate land use and travel behavior effects in transit-served areas. A geographic information system–based data set was developed to understand better the leverage effects associated with the mature and extensive Massachusetts Bay Transportation Authority transit system in areas proximate to its stations throughout Metropolitan Boston. The region was divided into the subregion that was transit-proximate (within a half mile of a rapid transit station or key bus route), the portion that was commuter rail–proximate, and the remaining 93.3% of the region that was not proximate to high-frequency transit. Households in the transit-proximate subregion were significantly more likely to commute by transit (and walking or biking), less likely to own a car, and drove fewer miles than households in the non-transit-served areas of the region. Commuter rail–proximate areas, although denser than the region as a whole, exhibited more driving and car ownership than regional averages. Given these spatial and modal variations, future efforts to understand transit leverage should separately evaluate land use and travel effects by mode and proximity to transit stations.

scholarly journals The effect of human mobility and control measures on traffic safety during COVID-19 pandemic

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0243263
Author(s):  
Jie Zhang ◽  
Baoheng Feng ◽  
Yina Wu ◽  
Pengpeng Xu ◽  
Ruimin Ke ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Traffic Safety ◽  
York City ◽  
Travel Behavior ◽  
Negative Binomial ◽  
Negative Relationship ◽  
Control Measures ◽  
Control Policies ◽  
The Impact

As mobile device location data become increasingly available, new analyses are revealing the significant changes of mobility pattern when an unplanned event happened. With different control policies from local and state government, the COVID-19 outbreak has dramatically changed mobility behavior in affected cities. This study has been investigating the impact of COVID-19 on the number of people involved in crashes accounting for the intensity of different control measures using Negative Binomial (NB) method. Based on a comprehensive dataset of people involved in crashes aggregated in New York City during January 1, 2020 to May 24, 2020, people involved in crashes with respect to travel behavior, traffic characteristics and socio-demographic characteristics are found. The results show that the average person miles traveled on the main traffic mode per person per day, percentage of work trip have positive effect on person involved in crashes. On the contrary, unemployment rate and inflation rate have negative effects on person involved in crashes. Interestingly, different level of control policies during COVID-19 outbreak are closely associated with safety awareness, driving and travel behavior, and thus has an indirect influence on the frequency of crashes. Comparing to other three control policies including emergence declare, limits on mass gatherings, and ban on all nonessential gathering, the negative relationship between stay-at-home policy implemented in New York City from March 20, 2020 and the number of people involved crashes is found in our study.

Consumer safety complaints and organizational learning: evidence from the automotive industry

2018 ◽  
Vol 35 (10) ◽  
pp. 2094-2118 ◽  
Author(s):  
Sourish Sarkar ◽  
Balaji Rajagopalan
Keyword(s):  
Organizational Learning ◽  
Traffic Safety ◽  
Value Of Information ◽  
Highway Traffic ◽  
Radical Product ◽  
Data Set ◽  
National Highway Traffic Safety ◽  
Content Type ◽  
Consumer Safety ◽  
The Impact

Purpose The purpose of this paper is to investigate the value of information in consumer safety complaints for organizational learning. Design/methodology/approach Empirical analysis of this study uses a novel secondary data set, which is formed by combining complaints data filed with the National Highway Traffic Safety Administration (NHTSA) for potential safety defects, and design change information from 2003 to 2011 model-year vehicles in the USA. Findings First, the paper demonstrates the value of information embedded in complaints. Second, in the case of radical product redesigns, owing to the lack of direct applicability of consumer feedback based learning, the impact of learning on product safety is found to be muted, third, the results suggest that the safety complaint rates vary by vehicle classes/categories and, fourth, the findings differ from prior research conclusions on vehicle quality. Prior research finds the debuting car models have the lowest repair rates among all car models produced in a given year, but the current study finds the debuting models to have the highest rates of safety complaints. Originality/value Quality management literature rarely examines the safety complaints data (which, unlike other consumer feedbacks, focuses exclusively on the safety hazards due to flaws that result in accidents). This paper fills the gap in literature by linking safety complaints with future product quality and organizational learning.

Using Location Data From Mobile Phones to Study Participation in Mass Protests

2020 ◽  
pp. 004912412091492
Author(s):  
Assaf Rotman ◽  
Michael Shalev
Keyword(s):  
Temporal Resolution ◽  
Mobile Phones ◽  
Mass Mobilization ◽  
Study Participation ◽  
Data Set ◽  
Mobile Location ◽  
Location Data ◽  
Wide Range ◽  
Potential Applications ◽  
Privacy Issues

Automatically collected behavioral data on the location of users of mobile phones offer an unprecedented opportunity to measure mobilization in mass protests, while simultaneously expanding the range of researchable questions. Location data not only improve estimation of the number and composition of participants in large demonstrations. Thanks to high spatial and temporal resolution they also reveal when, where, and with whom different sociopolitical sectors join a protest campaign. This article compares the features and advantages of this type of data with other methods of measuring who participates in street protests. The steps in preparing a usable data set are explained with reference to a six-week campaign of mass mobilization in Israel in 2011. Findings based on the Israeli data set illustrate a wide range of potential applications, pertaining to both the determinants and consequences of protest participation. Limitations of mobile location data and the privacy issues it raises are also discussed.

Traffic Safety Evaluation of Uncontrolled Intersections using Surrogate Safety Measures under Mixed Traffic Conditions

2015 ◽  
Vol 2512 (1) ◽  
pp. 81-89 ◽  
Author(s):  
P. Vedagiri ◽  
Deepak V. Killi
Keyword(s):  
Traffic Safety ◽  
Safety Evaluation ◽  
Mixed Traffic ◽  
Safety Measures ◽  
Traffic Conditions ◽  
Management Measures ◽  
Large Populations ◽  
Accident Data ◽  
Surrogate Safety Measures ◽  
The Impact

In the developing world, with increases in population, the number of vehicles is increasing tremendously. Traffic safety on roads has become a major concern even with advancements in technology and infrastructure. Traffic safety assessments and accident prediction based on accident data is a reactive approach. There are known drawbacks related to the reliability of accident data, especially in developing countries with large populations, such as India. It is, however, unethical to wait for accidents to occur before drawing statistically accurate conclusions regarding safety impacts. To overcome this impediment, one needs to develop accurate models that rely on surrogate safety measures (SSMs) for effective safety evaluations. The main advantage associated with the use of these models is that they can model crashes more frequently than in the real world and thereby imply an efficient and more statistically reliable proximal measure of traffic safety. The objective of this study is to examine the impact of management measures on traffic safety at a three-arm uncontrolled intersection with the use of microsimulation modeling under mixed traffic conditions. This examination was done by developing a unique methodology of measuring one SSM, postencroachment time (PET). This paper describes improvement in the accuracy of crash predictions by proposing a methodology to calculate PET.

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