scholarly journals Comprehensive Analysis of Dynamic Message Sign Impact on Driver Behavior: A Random Forest Approach

Urban Science ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 49
Author(s):  
Snehanshu Banerjee ◽  
Mansoureh Jeihani ◽  
Danny D. Brown ◽  
Samira Ahangari
Keyword(s):  
Random Forest ◽  
Driving Simulator ◽  
Driver Behavior ◽  
Route Choice ◽  
Potential Effect ◽  
Dynamic Message Signs ◽  
Road Users ◽  
Choice Analysis ◽  
Simulation Session ◽  
Message Signs

This study investigates the potential effect(s) of different dynamic message signs (DMSs) on driver behavior using a full-scale high-fidelity driving simulator. Different DMSs are categorized by their content, structure, and type of messages. A random forest algorithm is used for three separate behavioral analyses—a route diversion analysis, a route choice analysis, and a compliance analysis—to identify the potential and relative influences of different DMSs on these aspects of driver behavior. A total of 390 simulation runs are conducted using a sample of 65 participants from diverse socioeconomic backgrounds. Results obtained suggest that DMSs displaying lane closure and delay information with advisory messages are most influential with regards to diversion, while color-coded DMSs and DMSs with avoid route advice are the top contributors potentially impacting route choice decisions and DMS compliance. In this first-of-a-kind study, based on the responses to the pre- and post-simulation surveys as well as results obtained from the analysis of driving-simulation-session data, the authors found that color-coded DMSs are more effective than alphanumeric DMSs, especially in scenarios that demand high compliance from drivers. The increased effectiveness may be attributed to reduced comprehension time and ease with which such DMSs are understood by a greater percentage of road users.

Does Displaying Safety Messages on Dynamic Message Signs have Measurable Impacts on Crash Risk?

2021 ◽  
pp. 036119812110444
Author(s):  
Megat-Usamah Megat-Johari ◽  
Nusayba Megat-Johari ◽  
Peter T. Savolainen ◽  
Timothy J. Gates ◽  
Eva Kassens-Noor
Keyword(s):  
Negative Binomial ◽  
Driver Behavior ◽  
Field Research ◽  
Crash Risk ◽  
Traffic Crashes ◽  
Crash Data ◽  
Safety Issues ◽  
Dynamic Message Signs ◽  
Safety Message ◽  
Message Signs

Transportation agencies have increasingly been using dynamic message signs (DMS) to communicate safety messages in an effort to both increase awareness of important safety issues and to influence driver behavior. Despite their widespread use, evaluations as to potential impacts on driver behavior, and the resultant impacts on traffic crashes, have been very limited. This study addresses this gap in the extant literature and assesses the relationship between traffic crashes and the frequency with which various types of safety messages are displayed. Safety message data were collected from a total of 202 DMS on freeways across the state of Michigan between 2014 and 2018. These data were integrated with traffic volume, roadway geometry, and crash data for segments that were located downstream of each DMS. A series of random parameters negative binomial models were estimated to examine total, speeding-related, and nighttime crashes based on historical messaging data while controlling for other site-specific factors. The results did not show any significant differences with respect to total crashes. Marginal declines in nighttime crashes were observed at locations with more frequent messages related to impaired driving, though these differences were also not statistically significant. Finally, speeding-related crashes were significantly less frequent near DMS that showed higher numbers of messages related to speeding or tailgating. Important issues are highlighted with respect to methodological concerns that arise in the analysis of such data. Field research is warranted to investigate potential impacts on driving behavior at the level of individual drivers.

scholarly journals Research on the Relationship between Dynamic Message Sign Control Strategies and Driving Safety in Freeway Work Zones

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Wenxiang Xu ◽  
Xiaohua Zhao ◽  
Yufei Chen ◽  
Yang Bian ◽  
Haijian Li
Keyword(s):  
Driving Simulator ◽  
Control Strategies ◽  
Free Flow ◽  
Driving Safety ◽  
Work Zones ◽  
Analytic Hierarchy ◽  
Dynamic Message Signs ◽  
Traffic Jams ◽  
Analysis Strategy ◽  
Message Signs

Several studies have researched the effect of dynamic message signs (DMSs) on the driving safety in work zones. However, only a few studies have examined the design of DMS control strategies in work zones. The purpose of this study is to investigate the effects of DMS control strategies on driving decisions and behaviors and to improve the driving safety in work zones by changing the content and placement of DMSs. In this study, five control strategies are proposed by combining five DMSs with different contents (“change lane” versus “go straight”). A total of 32 participants participated in this study. Each participant drove in five scenarios in a high-fidelity driving simulator corresponding to strategies 1-5. The results show that the control strategies have a significant effect on drivers’ decisions and behavior (e.g., the driving speed, acceleration, and lateral placement). All strategies reduce the drivers’ speeds and improve their control stability and compliance. After conducting analytic hierarchy process (AHP) analysis, strategy 2 was removed because the approaching speed exceeded the speed limit. The weight vectors of strategies 1, 3, 4, and 5 under free-flow traffic and traffic jam conditions are Ƴfree-flow  traffic=0.25,0.28,0.17,0.23 and Ƴtraffic  jam=[0.17,0.28,0.2,0.3], respectively. These results show that strategy 4 is not suitable for free-flow traffic in work zones, while strategies 5 and 3 are suitable for traffic jams in work zones. Strategy  3 is suitable for both free-flow traffic and traffic jams. The first occurrence of a decision sign that contains lane change content is key to the driver’s decision; in addition, the position of signage with such information should gradually be moved closer to work zones with increasing traffic flow.

Examining Driver Compliance with a Move-Over/Slow Down Law in Consideration of Vehicle Type and Messages Displayed on Upstream Dynamic Message Signs

2021 ◽  
pp. 036119812110278
Author(s):  
Nusayba Megat-Johari ◽  
Megat-Usamah Megat-Johari ◽  
Peter Savolainen ◽  
Timothy Gates ◽  
Eva Kassens-Noor
Keyword(s):  
Driver Behavior ◽  
Field Studies ◽  
Minimal Impact ◽  
Logistic Regression Models ◽  
Dynamic Message Signs ◽  
Position Data ◽  
Lane Position ◽  
Compliance With The Law ◽  
The One ◽  
Message Signs

Move-over laws are intended to enhance the safety of road agency and law enforcement personnel who are working on or near the roadway. This study examined driver behavior through a series of field studies where these types of vehicles were located on the outside shoulder of a freeway with their lights activated. The study also evaluated the use of upstream dynamic message signs (DMS) to discern whether targeted safety messages had any impact on behavior under this scenario. Upstream and downstream speed and lane position data were collected from vehicles originally traveling in the rightmost lane upstream of the DMS and emergency/service vehicle at two locations in Michigan. Logistic regression models were estimated to assess driver compliance with the law while considering important contextual factors, such as the type of vehicle on the shoulder and the message displayed on the DMS. The results indicated that drivers were more likely to move over or reduce their speeds when a police car was located on the shoulder as compared to a transportation agency pickup truck. In general, the type of message displayed had minimal impact on driver behavior. The one exception showed that drivers were likely to drive at or below the speed limit when targeted move-over messages were shown as compared to standard travel time messages. For all message types, both speed and lane compliance improved if the roadside vehicle was a police car.

Understanding Driver Behavior after Concussion: A Machine-Learning Approach

2020 ◽  
Vol 64 (1) ◽  
pp. 1911-1915
Author(s):  
Maryam Daniali ◽  
Dario D. Salvucci ◽  
Maria T. Schultheis
Keyword(s):  
Machine Learning ◽  
Task Performance ◽  
Verbal Memory ◽  
Driving Simulator ◽  
Cognitive Impairments ◽  
Driver Behavior ◽  
Memory Task ◽  
Learning Approach ◽  
Behavioral Task ◽  
Machine Learning Approach

Concussions are common cognitive impairments, but their effects on task performance in general, and on driving in particular, are not well understood. To better understand the effects of concussion on driving, we investigated previously gathered data on twenty-two people with a concussion, driving in a virtual-reality driving simulator (VRDS), and twenty-two non-concussed matched drivers. Participants were asked to per-form a behavioral task (either coin sorting or a verbal memory task) while driving. In this study, we chose a few common metrics from the VRDS and tracked their changes through time for each participant. Our pro-posed method—namely, the use of convolutional neural networks for classification and analysis—can accu-rately classify concussed driving and extract local features on driving sequences that translate to behavioral driving signatures. Overall, our method improves identification and understanding of clinically relevant driv-ing behaviors for concussed individuals and should generalize well to other types of impairments.

scholarly journals Drivers’ Attention Strategies before Eyes-off-Road in Different Traffic Scenarios: Adaptation and Anticipation

2021 ◽  
Vol 18 (7) ◽  
pp. 3716
Author(s):  
Zhuofan Liu ◽  
Wei Yuan ◽  
Yong Ma
Keyword(s):  
Visual Attention ◽  
Driving Simulator ◽  
Test Drive ◽  
Urban Road ◽  
Strong Shift ◽  
Related Information ◽  
Road Users ◽  
Urban Rural ◽  
Within Subjects ◽  
Driving Task

The distribution of drivers’ visual attention prior to diverting focus from the driving task is critical for safety. The object of this study is to investigate drivers’ attention strategy before they occlude their vision for different durations under different driving scenarios. A total of 3 (scenarios) × 3 (durations) within-subjects design was applied. Twenty-three participants completed three durations of occlusion (0, 1, and 2 s) test drive in a motion-based driving simulator under three scenarios (urban, rural, motorway). Drivers’ occlusion behaviour, driving behaviour, and visual behaviour in 6 s before occlusion was analyzed and compared. The results showed that drivers tended to slow down and increased their attention on driving task to keep safety in occlusion 2 s condition. The distribution of attention differed among different driving scenarios and occlusion durations. More attention was directed to Forward position and Speedometer in occlusion conditions, and a strong shift in attention from Forward position to Road users and Speedometer was found in occlusion 2 s condition. Road users was glanced more frequently in urban road with a higher percentage of attention transitions from Forward position to Road users. While gaze switching to Speedometer with a higher intensity was found on motorway. It suggests that drivers could adapt their visual attention to driving demand and anticipate the development of upcoming situations by sampling enough driving-related information before eyes-off-road. Moreover, the adaptation and anticipation are in accordance with driving situation and expected eyes-off-road duration. Better knowledge about attentional strategies before attention away from road contributes to more efficient and safe interaction with additional tasks.

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