ISEP 2013 IMPROVEMENT OF HIGHWAY LEVEL OF SERVICE USING RAMP METERING Martin Gregurić, Mario Buntić, Edouard Ivanjko, Sadko Mandžuka University of Zagreb, Faculty of Transport and Traffic Sciences, Department of Intelligent Transportation Systems ZUK Borongaj, Object 71, Borongajska 83A, HR-10000 Zagreb, Croatia [email protected], {mario.buntic, edouard.ivanjko, sadko.mandzuka}@fpz.hr Abstract • Congestion minimization and improved throughput of Ramp metering is used to improve the Level of service of mainline traffic flows on the highway; highways containing a higher number off on- and off-ramps • Reduction of travel time on highways and increased with traffic load at peak hours. An overview of existing Ramp reliability in the planning time required to travel across metering strategies, from early simple approaches to the recent highways; more sophisticated control designs is given in this paper. A • description of various case studies of implemented Ramp Reducing traffic demand for highway usage in short metering systems in EU is included in the overview. Most of journeys; implementation has been custom made to fulfil respective • Prevention of accidents and incidents on highway; demands on reducing congestion, average travel time, and • Improving environmental protection as a result of increasing traffic safety. Some EU research projects and reduced noise and rational fuel consumption. initiatives with significant influence on the EU Ramp metering Ramp metering is today more and more used in order to approach are described, also. An analysis of Ramp metering strategies on a section of the Zagreb bypass is given regarding improve LoS of highways containing a higher number of implementation possibilities to improve its Level of Service traffic on- and off-ramps with periodically increased traffic and traffic safety. load at peak hours [3]. An overview of existing Ramp metering strategies, from Keywords simple approaches to the recent more sophisticated control Ramp metering, Level of Service, Neural networks, Fuzzy designs and strategies is given in this paper. Emphasis of logic the overview is on proactive and cooperative systems as they present current state of the art of Ramp metering. A INTRODUCTION description of various case studies of implemented Ramp metering systems in EU is included in the overview, also. Most of implementation has been custom made to fulfil Increased using of road vehicles in the last 30 years respective demands on reducing congestion, average travel induced extremely high occupation of roads and especially time, and increasing traffic safety. Some EU research urban highways. Such an amount of traffic is exceeding projects and initiatives with significant influence on the EU traffic capacities of urban highways and urban bypasses. Ramp metering approach are described, also. An analysis of There is no more space for constructional expansion of Ramp metering strategies on a section of the Zagreb bypass highways in most urban areas (build only approach) [1]. is given regarding implementation possibilities to improve Both mentioned reasons make a contribution to the fact that its LoS and traffic safety. most highways operate at or are approaching their capacity limit. In other words generally high Level of Service (LoS) projected for highways is significantly reduced due to traffic OVERVIEW OF MOSTLY USED RAMP METERING overload. ALGORITHMS Highway entrance/exit ramps or on- and off-ramps are places where it is possible to make a significant influence Most important part of Ramp metering is the control on highway LoS using appropriate control strategies [2]. algorithm which produces decisions about the amount of Such control of interactions between on-ramp and on-ramp vehicles that are allowed to merge with mainstream traffic flows is known as Ramp metering. Ramp mainstream traffic flow. Generally it is possible to divide metering uses road signals at on-ramps to control the rate or Ramp metering algorithms in two major categories or size of vehicle platoons entering mainstream traffic flow strategies: local (or isolated) and coordinated [4]. according to current traffic conditions. Whole system is based on traffic data collected in real time by road sensors Local strategies (inductive loops, cameras, etc.) and controllable traffic lights. Sensors are usually placed on the ramps and on the Local strategies include Ramp metering algorithms that main road. They measure and estimate the traffic flow, take into account only the traffic condition on particular on- speed and occupancy levels. ramp and nearby segment of highway where they are Ramp metering generally has following main operative applied. The ALINEA algorithm is the most often used reasons for implementation: standard local Ramp metering algorithm. Reason for this lays in the algorithms optimal ratio between simplicity and ISEP 2013 efficiency. The core concept of ALINEA is to keep the downstream occupancy of the on-ramp at a specified level Cooperative unit by adjusting the metering rate. Main disadvantages of ALINEA are: inability to resolve upstream congestions of Queue exceed threshold Detected congestion the particular ramp and to locate optimal detector mounting zone. It is also important to mention that ALINEA has Slighty numerous enhanced versions developed to include local and Decreased metering rate Increased metering rate coordinated Ramp metering approaches properties. Most recent versions are: MALINEA, VC-ALINEA and X- Decreased metering rate ALINEA/Q. All these derived versions are less efficient than the original ALINEA algorithm, but are often used in cases when downstream highway occupancy measurement Local decision: On-Ramp 3 is not available or possible. Queue len.: long Highway sec. density: high Zone algorithm is based on metering zones which can Metering rate: very short contain one or more metered and unmetered on- and off- ramps. Zones have one upstream boundary which denotes Local decision: On-Ramp 1 Local decision: On-Ramp 2 free-flow area and one downstream boundary. Downstream Queue len.: short Queue len.: short Highway sec. density: low Highway sec. density: low boundary usually denotes the place where bottlenecks Metering rate: long Metering rate: long occur. Zone algorithm frequently adjusts metering rate to maintain a constant traffic density within a particular zone. Figure 1: Basic functionality of cooperative Ramp metering Decision about the metering rate value is based on entering algorithms and exiting traffic volumes from mainstream traffic flow. Modern approaches in local Ramp metering algorithm ACCEZZ algorithm is a coordinated Ramp metering development also include neural networks which are using algorithm based on Fuzzy logic control and genetic learning capabilities to produce metering plans. Other algorithm optimization. Generally genetic algorithm modern approaches in local Ramp metering algorithm achieves global optimum of all metered on-ramps metering development are based on fuzzy logic and hybrid intelligent rates produced by local Fuzzy logic algorithms and thereby systems [5]. better coordination between them is established [7]. Coordinated algorithms Table 1: Comparison of Ramp metering algorithms Algorithm features Coordinated algorithms are taking into account the Ability to traffic situation on the longer part of the highway (highway resolve segment) or highway network as a whole. In the literature these algorithms are divided on: cooperative, competitive and integrated algorithms [6]. Ramp metering algorithms level** Proactive category* Algorithm algorithms Used in EU based on cooperation are working in two phases. In the first Complexity Upstream Congestion Congestion Ramp metering phase the metering rate for each on-ramp is computed by Downstream local Ramp metering algorithms. In the second phase ALINEA L L x x further adjustment of each local on-ramp metering rate is done based on system-wide information about the traffic ZONE L M x x situation on the whole highway segment. Basic functionality HELPER C M x of cooperative Ramp metering algorithms can be seen in HERO C H x x Fig. 1. ACCEZZ C H x x x HELPER algorithm is one among the first algorithms which have used mentioned cooperative Ramp metering SWARM C H x x x working principle. It includes several local traffic (*)L – Local, C – Coordinated (**) L-Low, M-medium, H-High responsive Ramp metering algorithms which are communicating with a centralized operational unit equipped System-Wide Adaptive Ramp metering (SWARM) uses with local metering rate override possibility. HELPER two different types of control algorithms: SWARM1 and algorithm creates virtual queues in upstream on-ramps to SWARM2B. SWARM1 algorithm works on a global reduce queue length on the congested one. coordination level by taking into account traffic state on HEuristic Ramp metering coOrdination (HERO) is each on-ramp. For final Ramp metering rate value primary developed to establish cooperation between usually computation SWARM1 algorithm uses also predictions of independent Ramp metering algorithms such as the highway traffic bottlenecks based on historical traffic ALINEA algorithm. HERO algorithm primary assigns to parameters data. SWARM2B is a local Ramp metering every local on-ramp control algorithm certain relative queue algorithm and defines metering rate according to difference threshold and waits until one of the on-ramp queues exceeds between current and critical traffic density for a particular its threshold. In a case when for the first