A vehicle-by-vehicle approach to assess the impact of variable message signs on driving behavior

Abstract

Variable Message Signs (VMS) provide real-time information on traffic conditions, making it possible to guide drivers through electronic signs along the road. Relevant literature has proved VMS to be effective, especially for diverting traffic during incidents in the highway or inducing a speed reduction. Previous efforts, however, usually involve off-highway experiences, including the use of simulators or stated preference surveys, or the measurement of aggregate values of traffic through technologies that are prone to a higher failure rate, such as loop detectors. For bridging this gap, in this research, we propose a novel vehicle-by-vehicle approach (VBV), that differentiate by vehicle type, to assess the impact of VMS on drivers’ road behavior patterns along a section of a Chilean urban highway during risky situations. In addition to the messaging information, we use full traffic data obtained from free-flow gates equipped with automatic vehicle identification (AVI) technology. We conduct statistical analyses to study two potential messaging-induced behavioral changes, namely speed reduction and lane changes. For the speed reduction behavior, in 87.50% of the studied messages, the results indicate that the messages failed to induce the desired change in behavior. This value decreases to 71.85% for lane changes. The results indicate that heavy vehicle drivers and low-mileage drivers are more likely to follow lane change messages.