A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion

 

ABSTRACT

Advanced information and communication technologies can be used to facilitate traffic incident management. If an incident is detected and blocks a road link, in order to reduce the incident-induced traffic congestion, a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this work. Time-dependent shortest path algorithms are used to generate a sub network where vehicles should receive such information. A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well modeled. Simulation results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles, operation time interval of the proposed strategy, and traffic density in the traffic network, and the scope of the area where traffic incident information is delivered. The results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents.

 EXISTING SYSTEM :

TRAFFIC incidents are any non-recurring events including traffic crashes, disabled vehicles, roadway maintenance and reconstruction projects, and special non-emergency events, e.g., ball games, concerts, or any other events that significantly affect roadway operations . They can cause a significant capacity reduction of roadways. Traffic incident management (TIM) makes a systematic effort to detect, respond to, and remove traffic incidents. It aims to offer the rapid recovery of traffic safety and capacity, and leads to many measurable benefits, such as decreases in fuel consumption, incident duration, secondary accidents, and traffic jams . There are many traditional traffic control methods for TIM in highways, such as lane control, variable speed limit control , and ramp metering control . So far, incident based urban traffic congestion is mostly controlled and prevented through traffic flow diversion with the help of the traffic police. Such a strategy is unfortunately labor-intensive, inflexible, and costly. Intelligent transportation systems such as advanced traveler information systems (ATIS), can be employed to improve the network efficiency via direct or indirect recommendation of alternative routes . Real-time traffic information can be sent to drivers through two main kinds of devices: in-car  and road-side devices. The type, such as radio GPS-navigators and Google Maps, helps drivers make sensible routing decisions at bifurcation nodes of the network. However, there are some disadvantages with these kinds of devices. On one hand, drivers who are familiar with the traffic conditions in a network may not use such agencies and thus optimize their individual routes based on past experiences. On the other hand, incident information is only useful to a finite number of selected drivers near the incident, and useless to others. The second kind of devices can be used to deliver information on major traffic events (e.g., incidents and congestion) and reduce incident-based congestion or enhancing traffic safety. However, they are usually spatially and/or temporally limited and constrained in the amount of information delivered. Thus, to the best of our knowledge, we find no intelligent strategies that can decide which drivers should be informed of a particular traffic incident.

PROPOSED SYSTEM:

If an incident is detected and blocks a road link, in order to reduce the incident-induced traffic congestion, a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this work.This paper presents a new strategy, which provides incident information to drivers and helps them make detours in urban areas. Traffic incident information is only transmitted to the affected vehicles that head towards the blocked link created by the incident. These vehicles are in a sub-network that can be generated  algorithm. In this work we further extend the CTM , build a model to simulate incident based traffic jams in urban areas and illustrate the effectiveness of our proposed strategy.

CONCLUSION:

This paper presents a new strategy, which provides incident information to drivers and helps them make detours in urban areas. Traffic incident information is only transmitted to the affected vehicles that head towards the blocked link created by the incident. These vehicles are in a sub-network that can be generated by the Dijkstra’ s algorithm. Simulations are done to test the effectiveness of the proposed strategy. The CTM-based model is used to estimate the congestion and promote the implementation of our strategy.

Future work should consider real world traffic conditions when different links have different traffic density. We also need to design algorithms to accurately estimate the time for vehicles to pass road links, and thus, obtain the time-dependent shortest path.