scholarly journals Travel Time Estimation Model for Emergency Vehicles under Preemption Control

2013 ◽  
Vol 96 ◽  
pp. 2147-2158 ◽  
Author(s):  
Jiawen Wang ◽  
Meiping Yun ◽  
Wanjing Ma ◽  
Xiaoguang Yang
Keyword(s):  
Travel Time ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Estimation Model ◽  
Emergency Vehicles

scholarly journals DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision

2018 ◽  
Author(s):  
Hanyuan Zhang ◽  
Hao Wu ◽  
Weiwei Sun ◽  
Baihua Zheng
Keyword(s):  
Travel Time ◽  
Deep Neural Networks ◽  
Time Estimation ◽  
Travel Time Estimation ◽  
Urban Mobility ◽  
Time Cost ◽  
Trajectory Data ◽  
Estimation Model ◽  
New Development ◽  
Supervision Model

Estimating the travel time of a path is of great importance to smart urban mobility. Existing approaches are either based on estimating the time cost of each road segment which are not able to capture many cross-segment complex factors, or designed heuristically in a non-learning-based way which fail to leverage the natural abundant temporal labels of the data, i.e., the time stamp of each trajectory point. In this paper, we leverage on new development of deep neural networks and propose a novel auxiliary supervision model, namely DeepTravel, that can automatically and effectively extract different features, as well as make full use of the temporal labels of the trajectory data. We have conducted comprehensive experiments on real datasets to demonstrate the out-performance of DeepTravel over existing approaches. 

scholarly journals Travel Time Estimation Modelling under Heterogeneous Traffic: A Case Study of Urban Traffic Corridor in Surat, India

2018 ◽  
Vol 47 (4) ◽  
pp. 302-308 ◽  
Author(s):  
Krishna Saw ◽  
Aathira K. Das ◽  
Bhimaji K. Katti ◽  
Gaurang J. Joshi
Keyword(s):  
Travel Time ◽  
Heavy Traffic ◽  
Time Estimation ◽  
Urban Traffic ◽  
Heterogeneous Traffic ◽  
Travel Time Estimation ◽  
Estimation Model ◽  
Traffic Condition ◽  
Side Friction ◽  
The Impact

Achievement of fast and reliable travel time on urban road network is one of the major objectives for a transport planner against the enormous growth in vehicle population and urban traffic in most of the metropolitan cities in India. Urban arterials or main city corridors are subjected to heavy traffic flow resulting in degradation of traffic quality in terms of vehicular delays and increase in travel time. Since the Indian roadway traffic is characterized by heterogeneity with dominance of 2Ws (Two wheelers) and 3Ws (Auto rickshaw), travel times are varying significantly. With this in background, the present paper focuses on identification of travel time attributes such as heterogeneous traffic, road side friction and corridor intersections for recurrent traffic condition and to develop an appropriate Corridor Travel Time Estimation Model using Multi-Linear Regression (MLR) approach. The model is further subjected to sensitivity analysis with reference to identified attributes to realize the impact of the identified attributes on travel time so as to suggest certain measures for improvement.

scholarly journals Development of Degree-of-Priority Based Control Strategy for Emergency Vehicle Preemption Operation

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Jiawen Wang ◽  
Wanjing Ma ◽  
Xiaoguang Yang
Keyword(s):  
Simulation Model ◽  
Travel Time ◽  
Control Strategy ◽  
Control Method ◽  
Time Estimation ◽  
Emergency Vehicle ◽  
Estimation Model ◽  
Model Based ◽  
Adverse Impacts ◽  
Emergency Vehicles

This paper proposes a degree-of-priority based control strategy for emergency vehicle preemption operation to decrease the impacts of emergency vehicles on normal traffic. The proposed model features its effectiveness to the following three aspects: (1) a multilayer fuzzy model was established to determine the degree-of-priority based on emergency vehicle preemption demand intensity and preemption influence intensity; (2) for emergency vehicles with proper classification, a travel time estimation model for emergency traffic was formulated, an optimal emergency route determines model based on the level of priority of emergency events, and the emergency vehicle travel time was developed to minimize evacuation time as well as minimize the adverse impacts of preemption on normal traffic; and (3) a conditional traffic signals priority control method at each intersection of the evacuation route was built, so that traffic queue at each intersection can be cleared before the arrival of emergency vehicles. A simulation model based on field data was developed, and the performance of the proposed strategy was compared with the conventional local detection based method under the microscopic simulation model. The results validated the efficiency of the proposed strategy in terms of minimizing the delay of emergency vehicles and reducing adverse impacts on normal traffic.

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