Proactive Traffic Merging Strategies for Sensor-Enabled Cars

Proactive Traffic Merging Strategies for Sensor-Enabled Cars

Ziyuan Wang (University of Melbourne, Australia), Lars Kulik (University of Melbourne, Australia) and Kotagiri Ramamohanarao (University of Melbourne, Australia)
DOI: 10.4018/978-1-60566-338-8.ch010

Abstract

Congestion is a major challenge in today’s road traffic. The primary cause is bottlenecks such as ramps leading onto highways, or lane blockage due to obstacles. In these situations, the road capacity reduces because several traffic streams merge to fewer streams. Another important factor is the non-coordinated driving behavior resulting from the lack of information or the intention to minimize the travel time of a single car. This chapter surveys traffic control strategies for optimizing traffic flow on highways, with a focus on more adaptive and flexible strategies facilitated by current advancements in sensor-enabled cars and vehicular ad hoc networks (VANETs). The authors investigate proactive merging strategies assuming that sensor-enabled cars can detect the distance to neighboring cars and communicate their velocity and acceleration among each other. Proactive merging strategies can significantly improve traffic flow by increasing it up to 100% and reduce the overall travel delay by 30%.
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Background

In this section, we first review current research on traffic models. These models provide the foundation to explore the effects of implementing new traffic control strategies. We argue that the mobility models commonly used in the study of communication ranges and information disseminations in VANETs are not sufficient for investigating traffic control strategies. Then, we review automotive sensors that can be implemented in the sensor-enabled cars. Those sensors collect traffic information as the input for the traffic model applied in traffic control strategies. Finally, we highlight some basic vehicular traffic theory concepts, with a focus on the traffic congestion on highways to provide a better understanding of traffic flow and design the flow control strategy.

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