From Goods to Traffic: First Steps Toward an Auction-Based Traffic Signal Controller

Abstract

Abstract. Tra c congestion is a major issue that plagues many urban road networks large and small. Tra c engineers are now leaning towards Intelligent Tra c Systems as many physical changes to road networks are costly or infeasible. Multi-Agent Systems (MAS) have become a popular paradigm for intelligent solutions to tra c management problems. There are many MAS approaches to tra c management that utilise market mechanisms. In market-based approaches, drivers "pay" to use the roadways. However, a major issue with many of these solutions is that they require technology that, as yet, does not exist or is not widely available. For example, they rely on a special software agent that resides within the vehicle. This "vehicle agent" is responsible for participating in the market mechanism and communicating with the transportation infrastructure. In this paper, an auction-based tra c controller is proposed which exploits all the benefits of market mechanisms without the need for a vehicle agent. Experimental results show that such a controller is better at reducing delay and increasing throughput in a simulated city, as compared to fixed-time signal controllers.

An Intersection-Centric Auction-Based Traffic Signal Control Framework

“…In conclusion, our work here and in [21] demonstrate the feasibility of a multi-agent auction-based traffic controller that does not require vehicle agents. SATQ reduced travel time by over 30 % under certain traffic conditions compared to a Fixed time traffic controller of initially identical cycle length.…”

“…The most basic phase plan is the two-phase plan where each street in a standard cross junction (C) is given a phase. The two-phase signalisation plan was used in our initial work [21]. Figure 2 illustrates the relationship between our traffic signal agents and the traffic phases.…”

“…In our initial work, we defined saturation as the ratio of traffic volume on a road segment to its capacity and used this as a measurement of the level of use of a phase [21]. In general, a stream of traffic that is functioning closer to its capacity is more susceptible to traffic jams and delays [29].…”

A Hybrid Cellular Swarm Optimization Method for Traffic‐Light Scheduling

“…Many methods attempt to optimize the traffic light scheduling recently. Raphael et al [14] proposed an auction-based traffic controller that exploits the benefits of market mechanisms without vehicle agents. Compared with fixed-time signal controllers, they proved that their controller reduce delay and increase through put in a simulated city better.…”

Social Cost Guarantees in Smart Route Guidance

“…Unfortunately, conventional traffic control systems have proven unable to efficiently decrease congestion levels, as they are not designed to be adaptive to the dynamics of city traffic, which changes over space and time. On the other hand, it has been shown [22,17] that by putting some sort of intelligence/smartness into traffic control systems, we can make them adapt to the changes of the traffic flow. A key objective within these smart traffic control systems is to address the so-called traffic assignment problem (TAP), in which mobile agents (i.e., typically drivers) declare their intended destination to the system, perhaps via their satellite navigation systems, and are then assigned a route to follow, in such a way that some objective function of the overall traffic flow in the system is optimized (i.e., minimizing the total traveled distance or maintaining an efficient traffic load balance).…”