Proper Lane Research Articles

Optimized Flexible Lane Assignment Using Simulation and Metaheuristic Algorithms

Technological advances with connected and autonomous vehicles (CAVs) have opened opportunities to increase the efficiency of transportation networks. A novel control framework called combined flexible lane assignment and reservation-based intersection control (CFLARIC) system has been recently proposed for better management of directionally unrestricted CAVs traffic flows in an urban environment. CFLARIC offers a full spectrum of lane assignment possibilities in combination with the appropriate reservation-based intersection control. In CFLARIC, vehicles position themselves in a proper lane before they reach the downstream intersection, which enables resolution of vehicular conflicts both between intersections and within the intersection boxes. Although CFLARIC has shown promising results, only a limited number of lane assignment scenarios have been designed and tested using some preset rules and based on the previous research objectives. Therefore, the optimality of their performance has never been studied. The objective of this study is to address the flexible traffic lane assignment in such a system as a network optimization problem, in which an optimal lane assignment schema is achieved using metaheuristic optimization algorithms. To this end, a combination of NetLogo and the BehaviorSearch tool is utilized for the simulation modeling and optimization process using random search and brute-force as the search algorithms. The output of the optimization process is the lane assignment that leads to a minimum total travel time for a given network geometry and traffic volumes. Results indicate that a flexible control concept such as optimized CFLARIC has great potential to improve the efficiency of traffic control strategies with CAVs.

Combined flexible lane assignment and reservation-based intersection control in field-like traffic conditions

A concept called Combined Alternate-Direction Lane Assignment and Reservation-based Intersection Control (CADLARIC) was recently proposed for better management of directionally unrestricted traffic flows in a Connected and Autonomous Vehicles (CAVs) environment. In CADLARIC, vehicles must position themselves in a proper lane before they reach the downstream intersection, which enables the resolution of vehicular conflicts both between intersections and, as traditionally, within the intersection boxes. CADLARIC has shown very promising results, but it is quite infrastructurally demanding, requiring six lanes per intersection approach. To overcome this problem, we propose here Combined Flexible Lane Assignment and Reservation-based Intersection Control (CFLARIC), a more robust concept that offers a full spectrum of lane assignment possibilities in combination with the appropriate reservation-based intersection control. Three distinctive CFLARIC strategies are tested on a simulated three-intersection corridor from West Valley City, Utah. The efficiency and safety performance of the proposed CFLARIC scenarios are evaluated through a comparison with Fixed-Time Control (FTC) and Full Reservation-based Intersection Control (FRIC), both with conventional lane assignments. The results illustrate that CFLARIC scenarios: (i) outperform FTC and FRIC in terms of efficiency (delay and number of stops), and (ii) improve overall safety (by reducing a number of conflicting situations) when compared to FRIC. The findings of this study prove that flexible control concepts such as CFLARIC have a great potential to improve safety and efficiency in future CAV environment. Future research needs to define under which conditions and how the proposed concept could be partially implemented in field operations.

Congestion Identification for Multilane Highway by Vehicle Lane Change as Driver Behavior


 
 
 
 This work introduces a new way to assess the condition of highways and classify them as congested or uncongested highways. This was done by recording a video and sorting the number of lane change orders instead of finding the traffic density, delay, and flow rate. Then extracting data from the video and performing a microscopic simulation for it to study the driver's behavior and create the statistical model. Thus, obtaining the mathematical relationships and coefficients that illustrate that process, after verifying the reliability and calibration of these variables.
 This research aims to facilitate the highway assessment process, as an alternative or supplementary method of highway evaluation by the Highway Capacity Manual 2010. It is adequate to record a video and count the number of vehicles that change their lanes and then compare them with the results that have been determined in the search to judge the highway is congested or not.
 The study area was achieved by choosing five segments of multilane arterial roads (six lanes divided) on the left coast of Mosul city. These segments were selected to be as similar as possible in the geometric configuration as well as like traffic flow. After that, cameras were installed according to criteria to record traffic movement and for a time not less than ten hours for each segment, and on the workdays for traffic movement. Then, the videos were uploaded using the Goodvision traffic data recognition program. These outputs were converted to be entered into the PTV-VISSIM traffic simulation program in addition to the other geometric information needed by the program to complete the analysis process and find traffic flow parameters. In the extraction process, the normal distribution and the uniform nature of the data representation of the observed event on the segments were examined using the Z-test and the K-S test, the results were normal and significant. Then the results were verified and the traffic parameters such as density and flow rate were checked to ensure the nature of the traffic flow. The process was also verified using the vehicle motion graphic representation method (Vehicle Trajectory), which is the initial examination to estimate the new variable.
 A new variable has been extracted, which is one of the traffic movement variables, which depends on the percentage of complete and proper lane change completion within the parameters imposed by the simulation program, it’s the Lane Change Occupancy factor (LnChOc.). Then the statistical model was derived using SPSS for the new variable. It describes traffic conditions on highways and the results are verified and calibrated in more than one way. It’s a simple statistical model was obtained to estimate the traffic movement from this variable and vice versa from the following equation:, Which gave results for critical traffic on multi-lane roads in the Mosul city as follows: -
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Service Operations for Mixed Autonomous Paradigm: Lane Design and Subsidy

This study aims to examine and design operational strategies for mixed flows of autonomous vehicles (AVs) and human‐driven vehicles (HVs). We propose a stylized model wherein utilitarian individuals either drive HVs or take privately operated AVs that are collectively dispatched. In the baseline mixed policy where AVs and HVs share the same lanes, we find that AVs under‐join the traffic (queue) while HVs over‐join. We identify a “crowding‐out effect” such that AVs will tend to mitigate the over‐joining HVs and reduce overall congestion/throughput. To improve the traffic efficiency of the baseline mixed policy, we consider a fully dedicated policy in which both AVs and HVs are segregated to different lanes and a partially dedicated policy in which only AVs enjoy dedicated lanes. We find that dedicated policies outperform the mixed policy in both social welfare and the aggregate throughput when the platooning effect is moderate or strong. Exact conditions are derived for the selection of fully dedicated policy and partially dedicated policy. Furthermore, we find that a carefully designed subsidy is necessary for the dedicated policy to simultaneously improve the social welfare and the throughput when the platooning effect is very weak. These results shed interesting light on the policy regulation for the emerging mixed autonomous paradigm: a dedicated policy with proper lane design and subsidy (if necessary) will improve both social welfare and aggregate throughput.

Identification of factors associated with various types of impaired driving

Despite significant progress in reducing impaired driving, impaired drivers are still a public threat to themselves and others. Studying all types of drivers’ impairment is especially important as impairment in the literature has been mainly looked at from an angle of the driving under the influence (DUI). In other words, there is a definitional ambiguity regarding the impaired driving in the literature review. Addressing that unclarity is especially important as while many considered impaired driving such as distraction and fatigued driving are similar to DUI, they account for a higher proportion of fatalities on roadway, compared with DUI. Thus, first we highlight links between DUI and other impaired driving based on the literature review, and then this study highlighted factors associated with various impaired driving so drivers’ actions and behaviors could be addressed more efficiently. Here, in addition to DUI, impaired drivers are defined as whether drivers were fatigued, distracted, or under some emotional conditions at the time of crashes. Multinomial logit model (MNL) was extended to a model excluding or equating some coefficients across categories, making parameters’ estimates more robust. The analysis results highlighted, for instance, types of vehicles that the drivers own, drivers’ gender, age, seatbelt use, and various drivers’ actions such as failure to keep the proper lane and following too close are associated with various impaired drivers’ actions. These associations are expected to be related to unseen drivers’ characteristics that were not recorded at the time of crashes. This is one of the earliest comprehensive studies, investigating the association of various factors and different types of impaired driving.

Assessment of Commercial Truck Driver Injury Severity as a Result of Driving Actions

The disaggregate modeling approach is a new trend in the literature to analyze the injury severity of truck-involved crashes. The assessment of truck driver injury severity based on driver action is still missing in the literature. This paper presents an extensive exploratory analysis that highlights significant variability in the severity of truck drivers’ injuries based on various action types (i.e., aggressive driving, failure to keep proper lane, driving too fast, and no improper driving). Binary logistic regression with the Bayesian random intercept approach was developed to examine the factors contributing to fatal or any injuries of truck drivers using 10 years (2007–2016) of historical crash data in Wyoming. Log-likelihood ratio tests were performed to justify that separate models by various driving action types are warranted. The results demonstrated the effects of various vehicle, driver, crash, and roadway characteristics, combined with truck driver-specific action, on the corresponding severity of driver injury. The gross vehicle weight, age and gender of the driver, time of day, lighting condition, and the presence of junctions were found to have significantly different impacts on the severity of truck driver injury in various driving action-related crashes. With the incorporation of the random intercept in the modeling procedure, the analysis found a strong presence (27%–33%) of intra-crash correlation in driver injury severity within the same crash. Finally, based on the findings of this study, several recommendations are made.

Study on Uncontrolled Intersection Under Mixed Traffic Condition-A Review

Every people in the world can access the road for the transportation purpose. Several traffic signs and signals are placed in order, to maintain safety for the people. Some places which don’t have the proper signals at the intersection might lead to cause more accidents and that kind of intersection are called as uncontrolled intersection. When several type of vehicles sharing and moves in a same carriage width without any gap between vehicles without any proper lane discipline is known as mixed traffic condition. Due to these accidents many people lose their life and many properties are also damaged. Several studies are being done by many literates about the uncontrolled intersection and it is available in the literature under mixed traffic condition for finding out the causes and some remedial measure were provided in those studies. Some of the study indicates about the Gap acceptance, Conflicts, pedestrian crossing behaviour, occupation time of the vehicle and so on. In this study we are going to discuss about those literatures and to give some remedial measures for the conflicts that occur in the uncontrolled intersection under mixed traffic condition.

Determination of Passenger Car Unit for Urban Roads: A Case Study in Addis Ababa

In Ethiopia, specifically on Addis Ababa city roads operating, vehicles are mixed with varying static and dynamic traffic characteristics that are very challenging for the traffic analyst to come up with a sole solution to the traffic malady. Under heterogeneous traffic, each vehicle type cannot be compared with other vehicle types since it shows different effects on the road. It could be observed that the majority of the drivers in Addis Ababa road networks do not follow proper lane discipline to use any available space on the road sections. Currently, Ethiopia is using the passenger car unit values from other countries manual, which doesn't represent the local traffic and roadway conditions. This study was initiated to establish the PCU values that will cater the local settings. Hence, this study was focused on estimating the PCU values of multilane highways in Addis Ababa city and determining the influence of traffic volume and width of the road on the values of PCU. The PCUs were estimated for four vehicle types based on the variation of traffic volume and carriageway width. Dynamic PCU method was used to determine PCU values, and a linear regression analysis was performed for model development. The developed model is used to estimate PCU values having the same traffic conditions and roadway conditions found in other countries. The study results indicated that as the traffic volume and carriageway width increases, the passenger car unit value also increases. Also, it was found out that the results of PCU values in this study showed higher values than those provided in Highway Capacity Manual (HCM). Hence, the PCU values obtained are recommended to reflect the existing traffic condition in the locality.

Determination of Passenger Car Unit for Urban Roads: A Case Study in Addis Ababa

In Ethiopia, specifically on Addis Ababa city roads operating, vehicles are mixed with varying static and dynamic traffic characteristics that are very challenging for the traffic analyst to come up with a sole solution to the traffic malady. Under heterogeneous traffic, each vehicle type cannot be compared with other vehicle types since it shows different effects on the road. During the field observations, most of the drivers in Addis Ababa road networks did not follow proper lane discipline to use any available space on the road sections. Currently, Ethiopia is using the passenger car unit values from other countries' manuals, which don't represent the local traffic and roadway conditions. This study was initiated to establish the passenger car unit (pcu) to cater to the regional settings. Hence, the study's focus was to estimate the pcu values of multilane highways in Addis Ababa city and determine the influence of traffic volume and width of the road on the importance of pcu. The passenger car units were estimated for four vehicle types based on traffic volume and carriageway width variation. Dynamic PCU method was used to determine values and performed a Linear Regression analysis for model development. The developed model was used to estimate pcu values having the same traffic and roadway conditions in other countries. Results indicated that as the traffic volume and carriageway width increase, the passenger car unit also increases. Also, this study found out that pcu values were higher than those provided in Highway Capacity Manual. Hence, the pcu values obtained are recommended to reflect the existing traffic condition in the locality.

Design improvements of vehicle bumper for low speed impact

With high number of vehicles on road and without any proper lane management and lack of concentration during parking the amount of collision has increased drastically. Generally, crashes are avoided but in some unfortunate case when the situation is unavoidable the crash is most likely to be taken by the bumpers of the vehicle. The bumpers of a vehicle are provided in front and back both sides of the vehicle. “The key role of the bumper is to provide the safety to the expensive parts like engine, radiator, cooling mechanism, headlights etc. The bumper also helps in the energy absorption during high and low speed impacts. Generally, the slow speed impact condition is not considered while designing of a bumper, and the amount of energy absorption is not considered for slow speed. “In this paper, low speed impact analysis of a car bumper is performed for the central impact and corner impact. Five different design variations are performed using finite element analysis. Parameters like the shape of the bumper and thickness are varied and impact condition is taken into consideration. The fifth design that is “Effect of increased thickness for modified profile” is found to be best in energy absorption during impact. From the analysis performed it is observed that the damage of the vehicle can be reduced by providing lining of suitable stiffness to the front metal bumper.

On the modeling of passenger mobility for stochastic bi-modal urban corridors

This paper proposes a methodology to estimate the passenger macroscopic fundamental diagram for bi-modal urban corridors while accounting for the stochastic nature of bus operations. The proposed framework extends the existing variational theory (VT) approaches by: (i) introducing a probabilistic VT graph, where the costs are computed using an efficient stochastic shortest path algorithm; (ii) capturing the effects of stochastic moving bus bottlenecks and the correlation of bus arrival times; (iii) incorporating a macroscopic passenger model that reflects the passenger dynamics for the different modes; and (iv) accounting for the effects that the traffic conditions might have on bus operations.Using a Monte-Carlo simulation and empirical data from a bi-modal corridor in Zurich, Switzerland, we not only successfully validate the results yielded by our stochastic VT approach, but also show its applicability on a real corridor. A comparison with a deterministic VT approach reveals the value of the proposed framework, especially for corridors with a high bus frequency and considerable stochasticity. The results demonstrate that incorporating stochasticity and the traffic conditions is essential if buses run with relatively short and variable headways. Moreover, we introduce an innovative application example for the evaluation of different bus lane layouts, aiming to maximize the passenger throughput along a bi-modal urban corridor. The application example shows that the proposed framework can be used as an efficient modeling tool for practitioners. In particular, it can be used to identify a proper lane allocation strategy by computing the critical density of cars when a mixed lane should be switched to a dedicated bus lane or vice versa. It is important to note that such application would not have been possible without our proposed VT extensions, which account for both passenger dynamics and the impact of traffic conditions. Finally, given that the proposed methodology is generic, it can be easily extended to various traffic problems involving stochasticity.

Application of multinomial and ordinal logistic regression to model injury severity of truck crashes, using violation and crash data

In 2016 alone, around 4000 people died in crashes involving trucks in the USA, with 21% of these fatalities involving only single-unit trucks. Much research has identified the underlying factors for truck crashes. However, few studies detected the factors unique to single and multiple crashes, and none have examined these underlying factors to severe truck crashes in conjunction with violation data. The current research assessed all of these factors using two approaches to improve truck safety. The first approach used ordinal logistic regression to investigate the contributory factors that increased the odds of severe single-truck and multiple-vehicle crashes, with involvement of at least one truck. The literature has indicated that past violations can be used to predict future violations and crashes. Therefore, the second approach used risky violations, related to truck crashes, to identify the contributory factors to the risky violations and truck crashes. Driver actions of failure to keep proper lane following too close and driving too fast for conditions accounted for about 40% of all the truck crashes. Therefore, the same violations as the aforementioned driver actions were included in the analysis. Based on ordinal logistic regression, the analysis for the first approach indicated that being under non-normal conditions at the time of crash, driving on dry-road condition and having a distraction in the cabin are some of the factors that increase the odds of severe single-truck crashes. On the other hand, speed compliance, alcohol involvement, and posted speed limits are some of the variables that impacted the severity of multiple-vehicle, truck-involved crashes. With the second approach, the violations related to risky driver actions, which were underlying causes of severe truck crashes, were identified and analysis was run to identify the groups at increased risk of truck-involved crashes. The results of violations indicated that being nonresident, driving off-peak hours, and driving on weekends could increase the risk of truck-involved crashes. This paper offers an insight into the capability of using violation data, in addition to crash data, in identification of possible countermeasures to reduce crash frequency.

Hardware Simulation of Advanced Driver Assistance Systems Based on Fuzzy Logic

Advanced Driver Assistance Systems (ADAS) is a system that has the function of helping the driver to be safe the trip without reducing the convenience. The subsystems developed in ADAS among other Automatic Braking System (ABS) which functions to make braking decisions when there is an object in front of it, Rear-end Collision Avoidance System (RCAS) that serves to avoid rear-end collision, Active Lane Keeping Assist (ALKA) which serves to keep the vehicle from getting off lane from its proper lane, and Adaptive Cruise Control (ACC) which serves to adjust the distance of the car with another car in front. This paper discusses the development of fuzzy logic based algorithms for those subsystems. The developed algorithm test was conducted using experimental car. The test results on the three variations of speed: slow-speed, medium-speed, and high-speed shows that the algorithm developed of ABS, RCAS, ALKA, and ACC can work according to design.

Automatic Number Plate Recognition System

Objectives: To develop a well-organised system in the vehicle number plate detection. Methods: The major techniques used in the implementation of the designs are gray scale conversion, black and white image conversion, filling holes, border detection and image segmentation. This is helpful to easily detect the license plate and identify the vehicle details. This is implemented on the real images. Findings: This algorithm provides overall accuracy and the average processing time with the images processing during day and night. This system works well in different illumination conditions. Applications: This system can be used for Indian roads scenario since there is no proper lane marking system and there is always a chance to get many disturbances in the images. This technique is applicable mainly at different restricted areas and highly confidential areas.

Outfit of Exemplar-SVMs for Object Detection and Beyond

Objectives: The main objective is the development of an efficient method in the recognition of vehicles in real world. Methods: The system relies on setting up of an alternate direct SVM classifier for every model in the planning set. Each of these Exemplar-SVMs is subsequently defined by a singular positive event and a large number negatives. While each discoverer is altogether specific to its model, we precisely watch that a troupe of such Exemplar-SVMs offers shockingly awesome theory. Our execution on the PASCAL VOC revelation errand is keeping pace with the altogether all the more bewildering idle part-based model of Felzenszwalb et al., at only a humble computational cost increase. But the central benefit of our approach is that it makes an unequivocal relationship between each acknowledgment and a singular get ready model. Findings: Since most revelations show incredible course of action to their related model, it is possible to trade any open model meta-data (segmentation, geometric structure, 3D model, etc.) clearly onto the recognizable pieces of proof, which can then be used as an element of general scene understanding. The current methods are taking negative information and processing them. They use the information mining to filter out the negative values, since the classifier is direct SVM the values are represented parametrically. However this system depends on an exceptionally basic thought. We use every model utilizing unending HOG template. The use of exemplar SVM will make the number of examples in the dataset more and the efficient way of processing the objects and identifying them. Applications: This system can be used for Indian roads scenario since there is no proper lane marking system and there is always a chance to get many disturbances in the images. This system can be more developed into a constant evolving model where the processed objects can be stored within and keeps on integrating the data set.

Abstract WP151: Increased Risky Driving in Acute Compared to Chronic Ischemic Stroke Drivers

Introduction: Guidelines recommend that patients refrain from driving in the acute phase of stroke. Patients are permitted to resume driving if no significant motor, cognitive, or perceptual deficits are present. This study investigated the driving performance of patients with mild ischemic stroke in the acute and chronic stages of recovery. It was hypothesized that patients with acute stroke would commit more risky driving errors (e.g. collisions, lane deviations) and that patients with chronic stroke would perform comparably to healthy matched controls. Methods: Driving simulator technology (STISIM) was used to compare the driving performance of 11 patients with acute mild ischemic stroke (NIHSS<5, <1 month post-stroke), 11 patients with chronic mild ischemic stroke (NIHSS<5 at discharge, >3 months post-stroke), and 11 healthy age- and education-matched controls. Participants completed a city-driving task and a car following task, which requires sustained attention and error monitoring. Results: Patients with acute stroke committed over three times as many risky driving errors compared to healthy controls during the city-driving task (6.2 vs. 1.7, p<0.01). Acute stroke patients made more errors (8.7 vs. 2.0, p<0.05) and had difficulty maintaining proper lane position (p<0.05) compared to controls during the car following task. Patients with chronic stroke committed fewer errors than acute stroke patients during the car following task (3.0 vs. 8.7, p<0.05) and tended to commit fewer risky driving errors during the city-driving task (2.7 vs. 6.2, p=0.076). Patients with chronic stroke performed comparably to controls during the driving tasks. Conclusions: Results suggest that patients with acute mild ischemic stroke may demonstrate impaired driving ability and that performance may improve in the chronic phase of recovery. The results reinforce the importance of refraining from driving in the acute phase of stroke and suggest that patients with good functional and cognitive recovery may be safe to resume driving in the chronic phase of injury. A large-scale longitudinal study is required to determine the optimal time for patients to resume driving after stroke.

The effect of chevron alignment signs on driver performance on horizontal curves with different roadway geometries

To develop a practicable and clear guideline for implementing Chevrons on China’s highways, it is necessary to understand the effect of Chevrons on driving performance in different roadway geometries.Using a driving simulator, this study tests the effect of China’s Chevrons on vehicle speed and lane position on two-lane rural highway horizontal curves with different roadway geometries.The results showed a significant effect of Chevrons on speed reduction, and this function was not significantly affected by curve radius but was statistically affected by curve direction. The speed reduction caused by Chevrons was also significant at the approach of curve, middle of curve and point of tangent. The 85th percentile speed was also markedly lower when Chevrons were present. We also found a significant effect of Chevrons in encouraging participants to drive the vehicle with a more proper lane position at the first half of curves; and this function was slightly affected by curve radius. Meanwhile, the effect of Chevrons on keeping drivers staying in a more stable lane position was also statistically significant at the second half of curves. In sharp curves, the function of Chevrons to make drivers keep a stable lane position was lost. Besides, the impact of curve direction on the function of Chevrons on lane position was always present, and drivers would drive slightly away from Chevrons.Regardless of the curve radius, China’s Chevrons at horizontal curves provide an advance warning, speed control and lane position guide for traffic on the nearside of Chevrons. Besides, combing with the function of Chevrons on preventing excessive speed and the benefit to make drivers keep a more proper lane position, China’s Chevrons appear to be of great benefit to reduce crashes (e.g., run-off-road) in curves.

A Study on the Lane Width of Car-Only Urban Underground Road

Theoretical analysis combined with experimental study was conducted to determine the proper lane width for urban car-only underground road. Vehicle trajectory data were collected in the experiment using three different ways including naturalistic driving experiment, video image processing and driving simulation. Lateral offset of each vehicle moving on the lane were obtained to determine the lane width. The results shows that for the car-only underground road, the design vehicle width is 1.8m,considering the safety margin and driving comfort, the minimum lane width 3m and 3.25m are reasonable and safe for the design speed 60km/h and 80km/h respectively.

All aboard the robotic road train

Public transportation has its own drawbacks: Buses and trains don't start at your home and don't end at your destination, nor do they leave just when you'd like or even guarantee you a seat. To get the best of both worlds, we could teach our cars to work together, as closely grouped cyclists do in a peloton. The lead car could be entrusted to a professional driver to whom the other drivers would of course each pay a small fee; all the other cars would follow it automatically. The cars would all use networked communications coupled with the optical or electromagnetic sensors already installed in some luxury cars to avoid head-on collision, stay in the proper lane, and brake in case of emergency. These systems have been developed at great expense to provide active safety, as distinguished from the passive kind afforded by seat belts. But this investment, having been made, can now be exploited for other things-like allowing you to relax and read the paper. If only we'd let them. Active systems are improving at a splendid rate. Adaptive cruise control, for example, maintains a car's speed while using radar or lidar to keep a safe distance from the car in front of it, thus automating much of the braking and accelerating. The latest generation of this system can follow a lead car from highway speed to a stop and then resume automatically when that car drives away. Soon the system will get additional data from vision sensors and digitized maps and additional support for the steering, allowing it to slow down on curves.

Naturalistic Validation of an On-Road Driving Test of Older Drivers

The objective was to compare a standardized road test to naturalistic driving by older people who may have cognitive impairment to define improvements that could potentially enhance the validity of road testing in this population. Road testing has been widely adapted as a tool to assess driving competence of older people who may be at risk for unsafe driving because of dementia; however, the validity of this approach has not been rigorously evaluated. For 2 weeks, 80 older drivers (38 healthy elders and 42 with cognitive impairment) who passed a standardized road test were video recorded in their own vehicles. Using a standardized rating scale, 4 hr of video was rated by a driving instructor. The authors examine weighting of individual road test items to form global impressions and to compare road test and naturalistic driving using factor analyses of these two assessments. The road test score was unidimensional, reflecting a major factor related to awareness of signage and traffic behavior. Naturalistic driving reflected two factors related to lane keeping as well as traffic behavior. Maintenance of proper lane is an important dimension of driving safety that appears to be relatively underemphasized during the highly supervised procedures of the standardized road test. Road testing in this population could be improved by standardized designs that emphasize lane keeping and that include self-directed driving. Additional information should be sought from observers in the community as well as crash evidence when advising older drivers who may be cognitively impaired.