Supplementary Benefits from Partial Vehicle Automation in an Ecoapproach and Departure Application at Signalized Intersections

Abstract

One of the objectives of the U.S. Department of Transportation's connected vehicle (CV) research program is to develop innovative applications that take advantage of communications between vehicles and roadside infrastructure as well as between the vehicles themselves to improve safety, mobility, and the environmental performance of multimodal transportation systems. Many of the energy- and environment-focused CV applications involve the prescription of optimal speed profiles for vehicles that travel within the transportation network. These recommended speed profiles can then be provided to the drivers through human–machine interfaces (HMIs). However, the drivers may not be able to follow the recommended speed profiles closely. In that case, the effectiveness of the applications might be degraded. These HMIs may even be distracting and detrimental to safety. Partial vehicle automation can be used to follow a recommended speed profile and play an important role to ensure that the benefits of these CV applications are realized fully. This paper presents an evaluation of the supplementary benefits from partial vehicle automation in CV applications with the use of an ecoapproach and departure application at signalized inter sections in a case study. This application provides recommended speeds for vehicles as they approach and travel through a signalized intersection so that they pass through the intersection on green or decelerate to a stop in the most ecofriendly manner. The evaluation was based on real-world HMI manual driving data and in simulated partial automation data. The results showed different levels of supplementary benefits, which depended on the ability of the drivers to follow the recommended speeds, compared with the actual target speed profiles that would have been achieved through partial vehicle automation.

Delivering improved alerts, warnings, and control assistance using basic safety messages transmitted between connected vehicles

“…Both the public and private sectors are interested in applications and implications of connected vehicles. Applications include intersection signals (Lee and Park, 2012;Christofa et al, 2013;Guler et al, 2014;Hu et al, 2014;Wu et al, 2014;Bagheri et al, 2015;Feng et al, 2015), pavement assessments (Bridgelall, 2013), traffic queue estimation (Li et al, 2013), vehicle routing and travel time estimation (Kianfar and Edara, 2013;Tian et al, 2013;Genders and Razavi, 2015;Moylan and Skabardonis, 2015), driving behavior monitoring and warnings (Sengupta et al, 2007;Goodall et al, 2014;Chrysler et al, 2015;Doecke et al, 2015;Du and Dao, 2015;Osman et al, 2015), and fuel efficiency (Kishore Kamalanathsharma and Rakha, 2014;Liu et al, 2016).…”

Fuel economy testing of autonomous vehicles

“…Wu et al (Wu et al, 2014) investigated the performance gains that could be expected from partial vehicle automation when using information of the current traffic signal status and schedule for the approaching intersection, when compared to human drivers given the same information. In the manual drive case the dashboard would indicate target velocities when approaching an intersection and the driver would attempt to obey the advice.…”

“…Fuel consumption was simulated using the EPA's Motor Vehicle Emission Simulator. Partial automation was found to improve fuel consumption by approximately 5-7% compared to a human driver given similar instructions (Wu et al, 2014). Rajamani and Shladover (Rajamani and Shladover, 2001) investigated cooperative adaptive cruise control (CACC) systems to ascertain the highest capacity gains and decreases in headway possible.…”

An Investigation of Autonomous Vehicle Roundabout Situation

“…In the supposed partial automation case, if the recommendations had been followed perfectly, what would have happened would be shown by a speed profile (Wu et al, 2014). According to the survey, partial automated vehicles save about 5-7 % of energy compared to human-driven vehicles.).…”