Behram Wali

Behram Wali
Massachusetts Institute of Technology | MIT · Senseable City Lab

Doctor of Philosophy

About

70
Publications
14,814
Reads
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823
Citations
Citations since 2016
70 Research Items
806 Citations
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2016201720182019202020212022050100150200250
Introduction
I am Postdoctoral Scholar at MIT Senseable City Lab and Lead Research Scientist at Urban Design 4 Health, Inc. (www.ud4h.com). Graduated in 2018, my ongoing research spans over diverse interconnected topics - ranging from transportation & health to safety, travel behavior, and sustainability implications of disruptive connected & automated vehicle technologies to more traditional traffic safety and mobility analysis. My methodological expertise includes big data analytics, simulation-assisted econometrics & quasi machine learning methods (walibehram@yahoo.com) More details about my research interests and activities can be found at http://bwali.weebly.com Those interested in design of smart cities would definitely find SCL’s website very valuable (senseable.mit.edu)
Additional affiliations
July 2015 - present
University of Tennessee
Position
  • Research Assistant
Description
  • Majorly associated with several projects sponsored by National Science Foundation, US-DOT, US-DOE, ORNL, and several other state DOTs. For details: https://www.linkedin.com/in/bwali
June 2014 - June 2015
National University of Sciences and Technology
Position
  • Research Assistant
Description
  • I had actively participated in projects related to traffic and work zone safety, work zone user risk perception, and analysis of key safety risk factors and their enforcement by using appropriate econometric methods
Education
July 2015 - July 2019
University of Tennessee
Field of study
  • Transportation Engineering
September 2013 - June 2015
National University of Sciences and Technology
Field of study
  • Transportation Engineering
September 2009 - July 2013

Publications

Publications (70)
Preprint
Full-text available
With the advent of seemingly unstructured big data, and through seamless integration of computation and physical components, cyber-physical systems (CPS) provide an innovative way to enhance safety and resiliency of transport infrastructure. This study focuses on real world microscopic driving behavior and its relevance to school zone safety expand...
Article
Full-text available
A novel evidence-based methodology is presented for determining place-based thresholds of objectively measured built environment features’ relationships with active travel. Using an innovative machine-learning based Generalized Additive Modeling framework, systematic heterogeneity fundamental to the development of well-justified and objective envir...
Article
Full-text available
Compact walkable environments with greenspace support physical activity and reduce the risk for depression and several obesity-related chronic diseases, including diabetes and heart disease. Recent evidence confirms that these chronic diseases increase the severity of COVID-19 infection and mortality risk. Conversely, denser transit supportive envi...
Article
Full-text available
An adequate understanding of consumer affinity towards automated vehicles (AVs) is necessary to more reliably forecast the potential impacts of AVs on transportation system. The road to fully automated driving systems pass through partially automated driving systems. This study contributes by simultaneously analyzing consumer affinity towards parti...
Article
Full-text available
Most of the existing literature concerning the links between built environment and COVID-19 outcomes is based on aggregate spatial data averaged across entire cities or counties. We present neighborhood level results linking census tract-level built environment and active/sedentary travel measures with COVID-19 hospitalization and mortality rates i...
Preprint
A variety of statistical and machine learning methods are used to model crash frequency on specific roadways with machine learning methods generally having a higher prediction accuracy. Recently, heterogeneous ensemble methods (HEM), including stacking, have emerged as more accurate and robust intelligent techniques and are often used to solve patt...
Article
Full-text available
Promoting sustainable transportation, ride-sourcing and dynamic ridesharing (DRS) services have transformative impacts on mobility, congestion, and emissions. As emerging mobility options, the demand for ride-sourcing and DRS services has rarely been simultaneously examined. This study contributes to filling this gap by jointly analyzing the demand...
Article
In September 2015, a new light rail transit (LRT) line opened in metro Portland, Oregon, USA. We used this natural experiment to conduct an interrupted time series analysis of the effects of LRT introduction on health care costs. We hypothesized that such costs would decline over time based on demonstrated health benefits of increased transit-relat...
Article
Full-text available
Evidence connecting health care expenditures with physical activity and built environment is rare. We examined how detailed urban form relates to mode specific moderate-to-vigorous physical activity (MVPA) and health care costs—controlling for transit access, residential choices/preferences, sociodemographic factors. We harness high resolution data...
Article
Full-text available
Background and objective No research to date has causally linked built environment data with health care costs derived from clinically assessed health outcomes within the framework of longitudinal intervention design. This study examined the impact of light rail transit (LRT) line intervention on health care costs after controlling for mode-specifi...
Article
Full-text available
Rapid advancements in vehicle automation and a shift towards collaborative consumption trends will disrupt future urban mobility systems. We present a joint model of consumers’ affinity towards shared automated vehicles (SAVs) with two distinct yet related configurations: automated vehicle (AV) carsharing and AV ride sourcing. Compact and walkable...
Article
Introduction: Little evidence exists in the literature regarding the discrimination power of better anatomical injury measures in differentiating clinical outcomes in motorcycle crashes. Furthermore, multiple injuries to different body parts of the rider are seldom analyzed. This study focuses on comparing anatomical injury measures such as the in...
Conference Paper
A variety of statistical and machine learning methods are used to model crash frequency on specific roadways – with machine learning methods generally having a higher prediction accuracy. Recently, heterogeneous ensemble methods (HEM), including “stacking,” have emerged as more accurate and robust intelligent techniques and are often used to solve...
Conference Paper
Non-motorists involved in rail-trespassing crashes are usually vulnerable to receiving major or fatal injuries. Previous research has used traditional quantitative crash data for understanding factors contributing to injury outcomes of non-motorists in traininvolved collisions. However, usually overlooked crash narratives can provide useful context...
Article
Full-text available
Active transportation (AT) is widely viewed as an important target for increasing participation in aerobic physical activity and improving health, while simultaneously addressing pollution and climate change through reductions in motor vehicular emissions. In recent years, progress in increasing AT has stalled in some countries and, furthermore, th...
Article
Full-text available
Accurate prediction of incident duration and response strategies are two imperative aspects of traffic incident management. Past research has applied various types of regression models for predicting incident durations and quantification of associated factors. However, an important methodological aspect is unobserved heterogeneity which may be pres...
Article
Driving errors and violations are highly relevant to the safe systems approach as human errors tend to be a predominant cause of crash occurrence. In this study, we harness highly detailed pre-crash Naturalistic Driving Study (NDS) data 1) to understand errors and violations in crash, near-crash, and baseline (no event) driving situations, and 2) t...
Article
Driving errors and violations are identified as contributing factors in most crash events. To examine the role of human factors and improve crash investigations, a systematic taxonomy of driver errors and violations (TDEV) is developed. The TDEV classifies driver errors and violations based on their occurrence during the theoretically based percept...
Article
Full-text available
Non-motorists involved in rail-trespassing crashes are usually more vulnerable to receiving major or fatal injuries. Previous research has used traditional quantitative crash data for understanding factors contributing to injury outcomes of non-motorists in train involved collisions. However, usually overlooked crash narratives can provide useful a...
Conference Paper
Driving errors and violations are identified as contributing factors in most crash events. Different types of driving errors and violations may vary across diverse roadway environments. Due to unique nature of several types of driving errors and violations, crash risk associated with each type of these driving errors and violations can be different...
Preprint
Full-text available
This report focuses on safety aspects of connected and automated vehicles (CAVs). The fundamental question to be answered is how can CAVs improve road users' safety? Using advanced data mining and thematic text analytics tools, the goal is to systematically synthesize studies related to Big Data for safety monitoring and improvement. Within this do...
Technical Report
Full-text available
Abstract: This report focuses on safety aspects of connected and automated vehicles (CAVs). The fundamental question to be answered is how can CAVs improve road users' safety? Using advanced data mining and thematic text analytics tools, the goal is to systematically synthesize studies related to Big Data for safety monitoring and improvement. With...
Article
Full-text available
As a key indicator of unsafe driving, driving volatility characterizes the variations in microscopic driving decisions. This study characterizes volatility in longitudinal and lateral driving decisions and examines the links between driving volatility in time to collision and crash-injury severity. By using a unique real-world naturalistic driving...
Preprint
Full-text available
As a key indicator of unsafe driving, driving volatility characterizes the variations in microscopic driving decisions. This study characterizes volatility in longitudinal and lateral driving decisions and examines the links between driving volatility in time to collision and crash injury severity. By using a unique real-world naturalistic driving...
Technical Report
To enhance safety, the Tennessee Department of Transportation (TDOT) is in the process of adopting the Highway Safety Manual (HSM) as a resource to facilitate decision making based on the safety performance of its roadways. The predictive models which are known as Safety Performance Functions (SPFs) are used to forecast the expected crash frequency...
Article
Full-text available
With the advent of seemingly unstructured big data, and through seamless integration of computation and physical components, cyber-physical systems (CPS) provide an innovative way to enhance safety and resiliency of transport infrastructure. This study focuses on real-world microscopic driving behavior and its relevance to school zone safety – expa...
Conference Paper
The transportation system of the future is anticipated to integrate automation, connectivity, electrification, and sharing of rides and vehicles—a concept known as ACES. Driven by the growing computational power, ubiquity of sensors, big data, and Artificial Intelligence, the public and private sectors have new opportunities to improve the quality...
Conference Paper
Adoption of Alternative Fuel Vehicles, especially by the commercial sector can reduce emissions and fossil fuel dependence. Despite the incentives to adopt AFVs, the current situation shows that about 86% of new vehicle sales for the commercial fleet are diesel and 13% are gasoline vehicles with a very small share of AFVs. A better understanding of...
Article
Automated vehicles (AVs) represent an opportunity to reduce crash frequency by eliminating driver error, as safety studies reveal human error contributes to the majority of crashes. To provide insights into the contributing factors of AV crashes, this study created a unique database from the California Department of Motor Vehicles 124 manufacturer-...
Article
Full-text available
Large-scale truck-involved crashes attract great attention due to their increasingly severe injuries. The majority of those crashes are passenger vehicle–truck collisions. This study intends to investigate the critical relationship between truck/passenger vehicle driver’s intentional or unintentional actions and the associated injury severity in pa...
Article
Full-text available
The sequence of instantaneous driving decisions and its variations, known as driving volatility, prior to involvement in safety critical events can be a leading indicator of safety. This study focuses on the component of "driving volatility matrix" related to specific normal and safety-critical events, named "event-based volatility." The research i...
Article
Full-text available
Motorcyclists are vulnerable road users at a particularly high risk of serious injury or death when involved in a crash. In order to evaluate key risk factors in motorcycle crashes, this study quantifies how different “policy-sensitive” factors correlate with injury severity, while controlling for rider and crash specific factors as well as other o...
Conference Paper
This paper develops key elements of the safe systems framework; analyzing human errors and violations and their contributions to crashes; bringing together and analyzing behavioral, infrastructure/built environment, and vehicle, and data analytic features in order to find ways to reduce crashes and prevent injuries. Driver errors and violations are...
Conference Paper
Full-text available
Driving behavior and school zone safety is a public health concern. The sequence of instantaneous driving decisions and its variations prior to involvement in safety critical events, defined as driving volatility, can be a leading indicator of safety. By harnessing unique naturalistic data on more than 41,000 normal, crash, and near-crash events fe...
Article
Full-text available
Due to enormous life and economic loss incurred by the road traffic crashes (RTCs), rigorous research efforts, especially in the developing countries are needed to investigate risk factors that significantly influence crash severity. The objective of this study is to empirically explore the impact of driver and vehicle characteristics, environmenta...
Conference Paper
To analyze key risk factors in motorcycle crashes, this study quantifies how different “policy-sensitive” factors correlate with injury severity, while controlling for rider and crash specific factors, and other observed/unobserved factors. Data on 321 motorcycle injury crashes from a comprehensive US DOT FHWA’s Motorcycle Crash Causation Study (MC...
Conference Paper
The main objective of this study is to quantify how different “policy-sensitive” factors are associated with motorcycle crash risk, while controlling for rider-specific, psycho-physiological, and other observed/unobserved factors. The analysis utilized data from a matched case-control design collected through FHWA’s Motorcycle Crash Causation Study...
Conference Paper
The sequence of instantaneous driving decisions and its variations, known as driving volatility, prior to involvement in safety critical events can be a leading indicator of safety. The research issue is to characterize volatility in instantaneous driving decisions, and how it varies across drivers involved in normal driving, crash, and/or near-cra...
Conference Paper
To address pedestrian and bicycle safety goals, new data collection techniques can be used to provide deeper understanding and insights on combating such crashes. Using the SHRP2 Naturalistic Driving Study data, we explore how driving volatility well before a crash or a near-crash happens can be used as a leading indicator of pedestrian and bicycle...
Conference Paper
Full-text available
Driving behavior and school zone safety is a public health concern. The sequence of instantaneous driving decisions and its variations prior to involvement in safety critical events, defined as driving volatility, can be a leading indicator of safety. By harnessing unique naturalistic data on more than 41,000 normal, crash, and near-crash events fe...
Article
Full-text available
Road infrastructure is used by various types of vehicles among which heavy vehicles imposes the most critical loading, causing damage in pavement structure, which ultimately leads to an increased maintenance and rehabilitation costs. During the design of road pavements, each type of vehicle is converted into equivalent standard axle load (ESAL) to...
Article
Full-text available
The key objective of this study is to investigate the interrelationship between fuel economy gaps and to quantify the differential effects of several factors on fuel economy gaps of vehicles operated by the same garage. By using a unique fuel economy database (fueleconomy.gov), users’ self-reported fuel economy estimates and government’s fuel econo...
Article
Full-text available
A key purpose of the U.S. government fuel economy ratings is to provide precise and unbiased fuel economy estimates to assist consumers in their vehicle purchase decisions. For the official fuel economy ratings to be useful, the numbers must be relatively reliable. This study focuses on quantifying the variations of on-road fuel economy relative to...
Article
Full-text available
The main objective of this study is to quantify how different policy-sensitive factors are associated with risk of motorcycle injury crashes, while controlling for rider-specific, psycho-physiological, and other observed/unobserved factors. The analysis utilizes data from a matched case-control design collected through the FHWA Motorcycle Crash Cau...
Article
Full-text available
Walkability and walking activity are of interest to planners, engineers, and health practitioners for their potential to improve safety, promote environmental and public health, and increase social equity. Connected and automated vehicles (CAVs) will reshape the built environment, mobility, and safety in ways we cannot know with certainty—but which...
Article
Full-text available
Driving behavior in general is considered a leading cause of intersection related traffic crashes. However, due to unavailability of real-world driving data, intersection safety performance evaluations are largely reactive where state-of-the-art methods are applied to analyze historical crash data. In this regard, the emerging connected vehicles te...
Article
Full-text available
Highway Work Zones (HWZs) present a major hazard for road users, construction workers and equipment, and significantly contribute to occurrence of road crashes worldwide. The present study focuses on analysing the current state of safety measures at HWZs in Pakistan. A more direct approach is adopted by comparing safety measures at randomly selecte...
Article
Full-text available
To improve transportation safety, this study applies Highway Safety Manual (HSM) procedures to roadways while accounting for unobserved heterogeneity and exploring alternative functional forms for Safety Performance Functions (SPFs). Specifically, several functional forms are considered in Poisson and Poisson-gamma modeling frameworks. Using five y...
Article
Full-text available
For practical considerations, Annual Average Daily Traffic (AADT) and segment 6 length are often used as the main correlates for predicting crash frequencies on segments. Typically, 7 a linear or simple non-linear dependence of crash frequencies on traffic exposure-related factors 8 is assumed which may not realistically represent the underlying co...
Article
Full-text available
The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same...
Article
Full-text available
Safety Performance Functions (SPFs) provide a basis for identifying locations where countermeasures can be effective. While SPFs in the Highway Safety Manual (HSM) were calibrated based on data from select states, calibration factors can be developed to localize SPFs to other states. Calibration factors typically provide a coarse adjustment—time an...
Article
Full-text available
Traditionally, evaluation of intersection safety has been largely reactive, based on historical crash frequency data. However, the emerging data from Connected and Automated Vehicles (CAVs) can complement historical data and help in proactively identify intersections which have high levels of variability in instantaneous driving behaviors prior to...
Article
Understanding the fuel economy of vehicles in actual use has important implications for fuel economy, greenhouse gas emission and consumer information policies. This study explores how fuel economy varies with intensity of daily vehicle use, cumulative mileage, and ambient temperature. Using a unique longitudinal database, we quantify variations in...
Article
Full-text available
The effectiveness of speed limit enforcement (SLE) is a critical factor in reducing the global burden of fatalities and injuries due to road crashes. A random-parameter ordered-probit model was developed to explore the relationships between the effectiveness of SLE and different explanatory variables using data from a 2013 World Health Organization...
Article
Full-text available
The contemporary traffic safety research comprises little information on quantifying the simultaneous association between drink driving and speeding among fatally injured drivers. Potential correlation between driver’s drink driving and speeding behavior poses a substantial methodological concern which needs investigation. This study therefore focu...
Article
Full-text available
Traffic incidents often known as non-recurring events impose enormous economic and social costs. Compared to short duration incidents, large-scale incidents can substantially disrupt traffic flows by blocking lanes on highways for long periods of time. A careful examination of large-scale incidents and associated factors can assist with actionable...