Autonomous Intersection Management for Connected and Automated Vehicles: A Lane-Based Method

Abstract

Most existing studies on autonomous intersection management (AIM) often focus on algorithms to accommodate conflicts among vehicles by assuming that the entrance lane and the exit lane of vehicles are exogenous inputs. This paper shows that allowing entrance lanes and exit lanes to be optimized can significantly improve traffic efficiency. In particular, this paper proposes "all-direction" lanes, where left-turn, through, and right-turn traffic is all allowed at the same lane. We develop two methods for optimizing entering time (i.e., when to enter the intersection) and route choice decisions (i.e., entrance lane and exit lane), including the sliding-time-window-based global optimum (GO-STW) and the first-come-first-served method with optimal route choices (FCFS-R). The developed lane-based methods can be formulated as mixed integer linear programming (MILP) problems, which can be solved using the CPLEX solver. A heuristic is further adopted to solve the MILP model in a timely manner, which illustrates the potential real-time applicability of the proposed method. Numerical analysis is conducted to examine performance and effectiveness of the proposed methods and heuristic. We found that the optimization of lane/route choices is often more critical than entering time. Index Terms-Autonomous intersection, connected and autonomous vehicles, lane-based method, sliding time window I. INTRODUCTIONutonomous vehicles promise a fundamental revolution in mobility [1,2], which brings enormous challenges and opportunities to planning and management of traffic systems [3]. By using connected vehicle technology [4,5], autonomous vehicles (AVs) are currently being tested and examined in a variety of scenarios [6,7]. How fully connected and autonomous vehicles will cross intersections, which is termed as autonomous intersection management (AIM), is one

Sharing Traffic Priorities via Cyber–Physical–Social Intelligence: A Lane-Free Autonomous Intersection Management Method in Metaverse

“…This safe pattern is still conservative because it excludes the chances that conflicting types of vehicles coexist in an intersection. Malikopoulos et al [28], Fayazi and Vahidi [29], Cai et al [30], Wu et al [31], Lee and Park [32], and Hadjigeorgiou and Timotheou [33] employed similar strategies to model collision avoidance constraints. Levin and Rey [34] believed that intervehicle collisions occur only at finite conflicting points.…”

A Route Planning and Traffic Control Model for Autonomous Intersections by Minimizing Conflict Zones

“…To address this issue, we formed conflict sets {(𝑔, 𝑖, 𝑗), … } , and then formulated constraints ( 17)-( 18) to ensure that the entry and exit times of each vehicle pair did not overlap. Notably, unlike [33], which investigated all vehicles under a discrete grid set, we only conducted conflict separation on grids traversed by two or more vehicles, thereby eliminating redundant solutions and effectively reducing the size of the solution space. The conflict separation constraint is expressed in Equations ( 17)- (18).…”

“…Based on the planed arrival time, we categorized the vehicles into time windows of 10 seconds [33]. The proposed model utilized a desktop computer equipped with a Windows 10 (64-bit) system, featuring an Intel (R) CoreTM i5-9400F processor clocked at 2.90 GHz and 8 GB of memory.…”

“…However, route optimization can significantly reduce conflicts between vehicles at intersections. For example, [33] constructed a mixed-integer programming model to optimize the vehicle routes within intersections, demonstrating that optimizing the route is an efficient approach to increase traffic efficiency at intersections compared to optimizing entering time. Nonetheless, their research did not consider the optimal utilization of the intersection space, which may diminish the traffic efficiency.…”