Smart Driving System for Improving Traffic Flow

Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

Author(s):  
Anastasia Spiliopoulou ◽  
Diamantis Manolis ◽  
Foteini Vandorou ◽  
Markos Papageorgiou

This study presents an ACC (adaptive cruise control)–based traffic control strategy which aims to adapt in real time the driving behavior of ACC-equipped vehicles to the prevailing traffic conditions so that motorway traffic flow efficiency is improved. The potential benefits obtained by applying the proposed control concept are demonstrated for different ACC penetration rates by use of validated microscopic simulation applied to a real motorway stretch where recurrent traffic congestion is created under the current manual driving conditions because of an on-ramp bottleneck. The simulation results demonstrate that, even for low penetration rates of ACC vehicles, the proposed control concept improves the average vehicle delay and fuel consumption by reducing the space-time extent of congestion compared with the case of only manually driven or regular ACC vehicles.


Author(s):  
Jianzhong Chen ◽  
Yang Zhou ◽  
Jing Li ◽  
Huan Liang ◽  
Zekai Lv ◽  
...  

In this paper, an improved multianticipative cooperative adaptive cruise control (CACC) model is proposed based on fully utilizing multivehicle information obtained by vehicle-to-vehicle communication. More flexible, effective and practical spacing strategy is embedded into the model. We design a new lane-changing rule for CACC vehicles on the freeway. The rule considers that CACC vehicles are more inclined to form a platoon for coordinated control. Furthermore, we investigate the effect of CACC vehicles on two-lane traffic flow. The results demonstrate that introducing CACC vehicles into mixed traffic and forming CACC platoon to cooperative control can improve traffic efficiency and enhance road capacity to a certain extent.


Author(s):  
Ioannis A. Ntousakis ◽  
Kallirroi Porfyri ◽  
Ioannis K. Nikolos ◽  
Markos Papageorgiou

Vehicle merging on highways has always been an important aspect, which directly affects the capacity of the highway. Under critical traffic conditions, the merging of main road traffic and on-ramp traffic is known to trigger speed breakdown and congestion. Additionally, merging is one of the most stressful tasks for the driver, since it requires a synchronized set of observations and actions. Consequently, drivers often perform merging maneuvers with low efficiency. Emerging vehicle technologies, such as cooperative adaptive cruise control and/or merging-assistance systems, are expected to enable the so-called “cooperative merging”. The purpose of this work is to propose a cooperative merging system and evaluate its performance and its impact on highway capacity. The modeling and simulation of the proposed methodology is performed within the framework of a microscopic traffic simulator. The proposed model allows for the vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication, which enables the effective handling of the available gaps between vehicles. Different cases are examined through simulations, in order to assess the impact of the system on traffic flow, under various traffic conditions. Useful conclusions are derived from the simulation results, which can form the basis for more complex merging algorithms and/or strategies that adapt to traffic conditions.


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