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This study represents the drivers' behavior regarding the implementation of an in-vehicle Eco-Speed-Control (ESC) system in order to provide real-time speed guidance in the vicinity of an intersection by using a full-scale high-fidelity 3D driving simulator. Infrastructure-to-vehicle communication is assumed, and the vehicles have full knowledge of the traffic light timings in the driving horizon. The advantage of the ESC system used in this study, compared to other eco-driving systems, is that it considers the roadway grade (uphill vs downhill). The ESC system is also applicable for different types of vehicles (light-duty, heavy-duty, and hybrid electric vehicles) and calculates the speed trajectory and fuel- more efficiently by considering real-time traffic. The system includes a visual dashboard display or audio guidance that provides moment-by-moment speed guidance aimed at improving fuel efficiency based on the drivers’ current performance, and the actions required to improve fuel economy whenever possible. Since it may take a long time for most vehicles road networks to be equipped with level 4 or 5 automation, this system allows the vehicle to take over and traverse the intersection and equips vehicles with a speed guidance system till the road network will be ready for full automation. However, the success of such a system partially depends on how well it can direct the driver. To study the driver’s behavior a network was simulated in the driving simulator. The study area used was a medium-size road network of the Baltimore metropolitan area, which consists of three signalized intersections, as shown in Figure 1.
Figure 1. Study Area
Seventeen scenarios were used for different road characteristics, traffic conditions, and Eco-Speed-Guidance (ESG) (Table 1) to investigate drivers' behavior and the reduction of CO2 emissions. Participants began by driving in a base scenario, with no guidance to provide a general measure of driving behavior for purpose of comparison, before using ESG systems. Participants then drove different ESG scenarios on a midsize road network in the Baltimore metropolitan area, including three intersections with uneven roads (uphill and downhill). In each scenario, the ESG was provided 200 meters before, and 200 meters after each intersection.
Table 1: Simulated Scenarios' Description
In the above-mentioned ESG area, at each intersection the participants were given the "Recommended Speed" or "Speed Change" via Voice, Text, and Graphic/Color. In “Recommended Speed” scenarios, the exact speed was announced; while in “Speed Change” scenarios, participants were given general statements such as "Increase Speed", "Decrease Speed", and "No Change”. Participants were expected to drive at a speed limit of 30 mph, and change their speed in response to the information provided via ESG (except in the base scenario) and go through the signalized intersection without stopping. The goal of the study was to measure the ability of drivers to follow the ESG.
The seventeen scenarios include no information as a benchmark, aside from providing “Recommended Speed” and “Speed Change” (Increase or Decrease or No Change) via Voice, Text, and Graphic/Color (Figure 2). Uphill versus Downhill was differentiated (due to differences in emission), along with “No Traffic” versus “Mild Traffic” (Traffic Intensity = 0.5E). The overall outcome of this study confirmed the effectiveness of an ESC system in reducing fuel consumption and emissions. In addition, the Speed Change-Color was identified as one of the best forms of Eco-Speed-Guidance when considering safety and emissions.
Figure 2 ESG
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