Modeling Reservation-Based Autonomous Intersection Control in VISSIM

Abstract

The use of autonomous vehicles is attracting more and more attention as a promising approach to improving both highway safety and efficiency. Most previous studies on autonomous intersection management relied heavily on custom-built simulation tools to implement and evaluate their control algorithms, but the use of nonstandard simulation platforms makes the comparison of systems almost impossible. Furthermore, without support from standard simulation platforms, reliable and trustworthy simulation results are hard to obtain. In this context, this paper explores a way to model autonomous intersections through the use of VISSIM, a standard microscopic simulation platform. A reservation-based intersection control system named autonomous control of urban traffic (ACUTA) was introduced and implemented in VISSIM through the use of VISSIM's external driver model. The operational and safety performance characteristics of ACUTA were evaluated with VISSIM's easy-to-use evaluation tools. In comparison with the results obtained with optimized signalized control, significantly reduced delays, along with a higher intersection capacity and lower volume-to-capacity ratios under various traffic demand conditions, resulted from the use of ACUTA. The safety performance of ACUTA was evaluated by use of the surrogate safety measure model, and few conflicts between vehicles within the intersection were detected. Moreover, the key steps and elements for implementation of ACUTA in VISSIM were introduced. These steps and elements can be useful for other researchers and practitioners implementing their autonomous intersection control algorithms in a standard simulation platform. By use of a standard simulation platform, the performance characteristics of autonomous intersection control algorithms can eventually be compared.

Policy and society related implications of automated driving: A review of literature and directions for future research

“…According to these researchers, this system could offer near-to optimal delays (up to 0.35 seconds); about ten times lower than the delays observed in conventional control systems. The efficiency of reservationbased intersection controls in reducing delays was also demonstrated by Fajardo, Au, Waller, Stone, and Yang (2012), Li, Chitturi, Zheng, Bill, and Noyce (2013) and Levin, Fritz, and Boyles (2016). Yet, Levin, Boyles, and Patel (2016) indicated some cases that optimized signals can outperform reservation-based intersection controls (e.g.…”

Optimizing Signalized Intersections Performance Under Conventional and Automated Vehicles Traffic

“…Several other studies have also explored different options to prioritize vehicles' crossing sequence under a variety of settings. (Ahmane et al (2013); Elhenawy et al (2015); Feng et al (2015); He et al (2012); Levin & Boyles (2016); Li & Wang (2006); Li et al (2013); Tachet et al (2016); Wu et al (2013); Xie et al (2012); Yan et al (2008); Zhong et al (2015)). Li et al (2014) proposed a rolling-horizon procedure to make joint decisions on vehicles' trajectory and signalization at an isolated intersection with AVs only and with two conflicting through movements.…”

Evaluation of a transportation system employing autonomous vehicles

“…While the data requirements are not unique, a deep understanding of a number of the specific problem and modeling methodology is sometimes necessary to even use or interpret simulation results [28]. As such, the few implementations of autonomous vehicles in existing software packages from previous studies have generally ignored vehicle dynamics [29] or have been limited in scope and constrained to studying a single problem at a time such as intersection negotiation [12] or vehicle platooning [30].…”

“…Human-computer interfacing when a human driver is necessary in manual or semiautonomous operation is considered by reference [9], and the comfort or perceptions of passengers in autonomously-operated vehicles where they may pose issues in adoption is analyzed in references [10,11]. The vast majority of infrastructure-related work is focused on urban intersection handling where wireless vehicle-to-infrastructure (V2I) communication is in vehicle right-of-way coordination [12,13]. Lastly, high-level strategies for improving traffic flow generally focus on headway regulation [14,15] and optimal routing [16,17].Optimization algorithms for planning transportation services according to [18,19] generally fall into several broad categories: (i) vehicle assignment and rescheduling; (ii) crew scheduling; and (iii) passenger logistics.…”