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

Abstract

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.

The verbiage in variable message signs and traffic diversion during crash incidents

“…Yim and Ygnace (1996) found displaying real-time traffic information (level of delay) useful in attaining higher compliance. The importance of VMS message information details was also confirmed by a recent simulator-based study by Morgan State University (Banerjee et al, 2020). However, based on a driving simulator experiment, Xu et al (2020) concluded that an increase in information details in VMS messages increases the information load to the drivers, demanding more cognitive efforts to perceive the information.…”

“…For example, “crash 13 miles ahead, use caution” and “crash ahead, prepare to stop” could both be used to inform drivers of a crash incident ahead. Past studies based on stated preference (SP) surveys (Peeta and Ramos, 2006; Spyropoulou and Antoniou, 2014; Kim et al , 2014) and simulator-based studies (Banerjee et al , 2020) have concluded that the verbiage of the message matters to the drivers in their response to the message. With limited understanding of diversion behavior of the driver in response to different verbiage of crash message based on real-field data, two ordered logit models of increase in diversion rate were fitted using VMS message history of I-15 in the Salt Lake City metro area.…”

“…For example, "crash 13 miles ahead, use caution" and "crash ahead, prepare to stop" could both be used to inform drivers of a crash incident ahead. Past studies based on stated preference (SP) surveys (Peeta and Ramos, 2006;Spyropoulou and Antoniou, 2014;Kim et al, 2014) and simulator-based studies miles to crash + delay information crash location + "use caution" + lane of crash miles to crash + "use caution" + lane of crash crash location + speed suggestion crash location + lane blocked miles to crash + lane blocked crash location + "prepare to stop" miles to crash + "prepare to stop" miles to crash + speed suggestion others Percentage (%) (Banerjee et al, 2020) have concluded that the verbiage of the message matters to the drivers in their response to the message. With limited understanding of diversion behavior of the driver in response to different verbiage of crash message based on realfield data, two ordered logit models of increase in diversion rate were fitted using VMS message history of I-15 in the Salt Lake City metro area.…”

Assessing temporary traffic management measures on a motorway: Lane closures vs narrow lanes for connected and autonomous vehicles in roadworks

“…With regards to LC, CAVs can receive information from surrounding infrastructure and neighbouring vehicles about the new road layout and re-route accordingly. Banerjee et al, [21] found that early on signs of LC are very helpful for route decision. Hess et al [22] modelled the lane change behaviour for a closed lane scenario using a driving simulator.…”

Validity of Variable Message Sign Information: Is It Influenced by Drivers’ Short-Term Memory?

“…From the perspectives of driver comprehension and response, a road network that is displayed graphically must be simple and recognizable. For the congestion information displayed on a VMS, the level of information that drivers need to comply with can have a significant impact on their detour or route-switching behavior ( 19 , 21 , 22 ). A field study by Shen and Yang demonstrated that detour rate increases 10% to 20% when the congestion message is varied from “moderate traffic congestion” to “heavy congestion” ( 23 ).…”