Khaled Shaaban

Use of Drivers' Jerk Profiles in Computer Vision-Based Traffic Safety Evaluations

A traffic conflict is usually composed of a chain of events in which at least one of the involved road users performs some sort of evasive action to avoid a collision. An evasive action usually involves powerful braking, which leads to sudden, negative change in acceleration (deceleration). The temporal dynamics (variation over time) of the acceleration of a vehicle is represented by the jerk profile. More formally, jerk is the derivative of the acceleration. In the case of an evasive action by braking, the jerk profile is characterized by strong, negative values. This study examined two issues in the quest to understand the benefits of evasive action analysis. The first issue was whether jerk profiles can be used to identify critical traffic events (conflicts). The second issue addressed the validity of the assumption that the deceleration profile is inadequate as a stand-alone measure for conflict identification. Automated video analysis was used to collect traffic data and analysis was applied on two data sets with distinct traffic patterns. The study revealed a significant difference between the jerk behavior of the groups of drivers involved in conflictive and normal traffic interactions. It also showed instances in which automated jerk evaluation was successful in finding conflicts undetected by conventional conflict indicators. The same could not be demonstrated for the road users’ deceleration behavior. These findings support earlier studies on the shortcomings of the use of deceleration data for conflict identification.

Assessment of drivers' perceptions of various police enforcement strategies and associated penalties and rewards

Road crashes are a major cause of death in many countries. Qatar has been battling to improve road safety on several fronts using different strategies, including road policing. The purpose of this study is to ascertain drivers’ perceptions towards five existing and four proposed police traffic enforcement strategies and associated penalties and rewards in Qatar using face-to-face surveys. The results show that red-light running cameras were perceived to be the most successful existing strategy. The high violation fine and the automation of the system were mentioned as the main reasons for making this strategy the most successful. Three of the existing strategies, fixed-speed enforcement cameras, police enforcement, and mobile speed cameras, were conferred almost the same success percentage, followed by the demerit point system. Regarding the proposed strategies, rewarding safe drivers was selected by the participants as the most successful proposed strategy, followed by introducing more automated enforcement methods. Community service for traffic tickets came in third, followed by defensive driving school. These results can be used to influence future enhancements of existing strategies and guide the development of future traffic strategies being introduced in the traffic system.

Investigating Driver Behavior at Minor-Street Stop-Controlled Intersections in Qatar

Stop-controlled intersections are dangerous locations in which drivers must negotiate conflicts between traffic streams. This study examined driver stopping compliance at minor-street stop-controlled intersections in Qatar. Several variables that may influence driver behavior when approaching a stop sign were considered—including age, gender, driver heritage differences, vehicle type, presence of an approaching vehicle or a pedestrian, peak and nonpeak hours, weekday versus weekend, and residential versus commercial land use. Binary and ordinal logistic regression models were developed to describe driver stopping behavior as functions of these characteristics. Results indicated an alarmingly low compliance rate with minor-street stop signs. Generally, results indicated that male drivers, young drivers, and SUV drivers are less likely to come to a complete stop at these locations. Results also revealed that drivers are more likely to ignore the stop sign when they notice a vehicle or pedestrian approaching and most likely to beat the approaching vehicle or pedestrian through the intersection and reduce intersection-related delay. These findings raise a major safety concern and indicate aggressive driving tendencies. Potential countermeasures include increasing police enforcement, initiating traffic safety campaigns (e.g., targeting the higher risk drivers identified in the results), and improving the visibility of stop signs using different measures, such as larger and additional stop signs, “Stop Ahead” advance traffic control signs, and enhanced pavement markings.

Automated Analysis and Validation of Right-Turn Merging Behavior

This article describes an automated approach for the analysis of right-turn merging behavior of vehicles. Traditional methods for collecting merging behavior data are labor intensive, suffer from reliability issues, are time consuming, and costly. Automated video merging behavior analysis is advocated as alternative data collection procedure resolving many shortcomings in the manual data collection. The main elements of the behavior analysis include merging conflicts, gap acceptance, and lane discipline. Traffic conflicts provide invaluable information that can be used to assess safety factors and to understand potential collision mechanisms. Gap acceptance is important for developing merging vehicles modeling frameworks. Lane discipline of merging vehicles is significant in showing potential aggressive and dangerous merging maneuvers and driver compliance to traffic rules. The article advocates automated computer vision as the engine to capture and analyze various merging behavior elements. The analysis is demonstrated using a case study from Doha, Qatar. A validation of the results was performed that demonstrated the soundness of the methodology and potential benefits for automated behavior data collection. The microscopic behavior data captured using the proposed automated methodology can be useful for use in road design, traffic management and safety evaluation.

Evaluating the effect of seasonal variations on walking behaviour in a hot weather country using logistic regression

ABSTRACT The city of Doha, Qatar experiences a hot and arid weather throughout the year. This study investigates the effect of season, type of day, and time of day on the walking behaviour of pedestrians in these conditions using logistic regression. The study uses data obtained from observational surveys conducted at a densely populated mixed-use neighbourhood located in the heart of the city. The results showed the walking activity is much less during hot weather. The results of the logistic regression analysis suggested that the pedestrians from other nationalities living in Qatar had much higher odds of walking compared to the Qatari nationals. Furthermore, men had almost double the odds of walking compared to females. The choice of the time of day model indicated that a pedestrian has more than twice the odds of walking in the evening time compared to the morning and afternoon times. The results can help policy makers and public agencies to develop programmes to promote the walking culture in this region.

Comparison of SimTraffic and VISSIM Microscopic Traffic Simulation Tools in Modeling Roundabouts

SimTraffic and VISSIM are two microscopic traffic simulation tools that are capable of modeling arterial roads with signalized intersections and roundabouts. This study compares the performance of the two simulation tools in modeling dual lane and triple lane roundabouts under different scenarios such as traffic volume, proportion of left turning movement, and proportion of trucks in the traffic flow. The two simulation tools did not show statistically significant difference in general. However; in the case of high traffic volumes, VISSIM showed higher average delays than those from SimTraffic compared to nearly identical results in the case of low traffic volumes.

Understanding the association between cell phone use while driving and seat belt noncompliance in Qatar using logit models

ABSTRACT Cell phone use while driving can distract the driver and can lead to serious traffic safety problems. Similarly, not using a seat belt can increase the risk of injuries and/or fatalities in the event of a crash. The objective of this study is to identify the rate of cell phone use as well as the rate of seat belt noncompliance in Qatar and to investigate the association between the two. A total of 7,982 vehicles were observed at 40 intersections. The overall rate of seat belt noncompliance was 16.4%, and the overall rate of cell phone use while driving was 10.7%. Logit models were developed to identify the factors that affect the use of cell phones and seat belts, and a significant association was found between the two. The results of the study show that people driving sport utility vehicles are less likely to wear seat belts than those using other types of vehicles and more likely to use their cell phones while driving. In addition, male drivers are more likely than female drivers to wear seat belts and less likely to use their cell phones while driving. Furthermore, young drivers are less likely to wear seat belts than older drivers and more likely to use their cell phones while driving. The results of this study can help policy makers and public agencies to understand the profiles of drivers who use cell phones while driving and who are also noncompliant with seat belt use. This information can help in identifying the proper countermeasures and the targeted population in both Qatar and similar countries in the region.

Comparison of Time-Proximity and Evasive Action Conflict Measures

Interest has grown in using traffic conflicts for studying safety from a broader perspective than relying only on collision data. Traffic conflict analysis is typically performed through the calculation of traditional conflict severity measures such as time-to-collision and postencroachment time. These measures rely on road users getting within specific temporal and spatial proximity from each other and therefore assume that proximity is the surrogate for severity. However, this assumption may not be valid in some driving environments where close interactions between road users are common and sudden evasive actions are frequently used to avoid collisions. It is suggested that evasive action–based conflict indicators can assess the analysis in some less-organized traffic environments. This study focused on the severity evaluation of pedestrian conflicts. Pedestrian evasive actions were reflected mainly in variations of spatiotemporal gait parameters (step frequency and step length). The objective was to compare the use of time proximity and evasive action–based conflict indicators in evaluating the severity of pedestrian conflicts in different traffic environments. Video data from intersections in five major cities—Shanghai, China; New Delhi, India; New York City; Doha, Qatar; and Vancouver, British Columbia, Canada—were analyzed with automated computer vision techniques to extract pedestrian-involved conflicts and calculate conflict indicators. Results show that evasive action–based indicators were more effective in identifying and measuring the severity of pedestrian conflicts than time proximity measures in traffic environments such as Shanghai and New Delhi. However, evasive action measures did not show the same potential in Vancouver and Doha, where time proximity measures were more effective.

Driver Behaviors at Level Crossings from Fixed and Moving Driving Simulators

Many studies were conducted to evaluate safety at railway crossings equipped with different types of warning devices. In this study, a desktop driving simulator (fixed simulator) and an advanced simulator (moving simulator) were used to identify the impacts of two warning devices namely stop sign and in-vehicle audio warning on alerting drivers at railway crossings. Although these high-end technologies have been widely used for safety evaluation in many areas, there is a little research on their application and comparison at railway crossings. This paper reports the results of a comparison of the two simulators. As a preliminary result, vehicle speeds at given distance/time were analyzed. The results showed that when the warning started, drivers in the fixed simulator were slower than those in the moving simulator in responding. However, after four seconds of warning, the speed from both simulators showed statistically identical results. In summary, the different properties of the simulator lead drivers to react to warnings differently.

Evaluation of Transit Signal Priority Implementation for Bus Transit along a Major Arterial Using Microsimulation

Abstract Transit Signal Priority (TSP) provides preferential treatment for public transit vehicles at signalized intersections when implemented. TSP is usually provided by interrupting the typical signal timings and extending the green or truncating the red for the signal phases that serve transits. This study investigates the impact of implementing a TSP treatment along a major arterial. A microsimulation approach was used to model, assess, and evaluate the potential benefits of implementing this treatment to bus transit vehicles. The network was built in a VISSIM multimodal microsimulation environment to test the traffic network performance with and without priority treatments. The study considered different peak hours for performance assessment. Three transit routes were considered in the microscopic modeling. The results showed a significant benefit of implementing TSP for the transit vehicles. The travel time was reduced by more than 40% in some cases, which can be translated into lower transit delay and more reliable transit service. The results also showed that TSP has a minimal negative effect on the general traffic. In fact, the general traffic along the studied transit routes benefited from the TSP implementation because of the better traffic progression and additional green times.