Pedestrian

Wael alhajyaseen's picture

Consideration of Vehicular and Pedestrian Flows in A Multi-Modal Traffic Signal Optimization Strategy for Isolated Intersections

Journal Title, Volume, Page: 
An-Najah University Journal for Research - Natural Sciences - Volume 28, Issue 1, 2014
Year of Publication: 
2014
Authors: 
Wael Alhajyaseen
Department of Civil Engineering, Faculty of Engineering and Information Technology, An-Najah National University, Nablus. Palestine
Current Affiliation: 
Department of Civil Engineering, Faculty of Engineering and Information Technology, An-Najah National University, Nablus. Palestine
Meng LI
Department of Civil Engineering, Tsinghua University, 100084, Beijing, China
Preferred Abstract (Original): 

Current signal control strategies tend to ignore the pedestrian delays that may be imposed by reducing traffic delays. Such an objective is reasonable for motorways and rural roads where vehicular traffic is dominant over pedestrian traffic. However, it is not the case in metropolitan cities with large volume of pedestrian demands. This paper developed a traffic signal optimization strategy that considers both vehicular and pedestrian flows. The objective of the proposed model is to minimize the weighted vehicular and pedestrian delays. The deterministic queuing model is used to calculate vehicular traffic delay and pedestrian delay on sidewalk. Pedestrian delay on crosswalk is calculated based on an empirical pedestrian speed model, which considers interactions of pedestrian platoons and their impacts on average walking speed. A Japanese Intersection is utilized as a numerical case study to evaluate the proposed model. MATLAB is used to solve the optimization problem and to output a set of measures of effectiveness (MOEs). The results show that the proposed model improved average person delay (APRD) by 10% without changing the existing cycle length. Moreover, the model can optimize the cycle length and further improve APRD by as much as 44%. In order to demonstrate the applicability of the proposed model for general cases, this paper also conducted sensitivity analysis. The results showed that the proposed model is most significant and necessary for two circumstances: (1) metropolitan areas with high pedestrian demands and (2) major urban arterials with high pedestrian demands crossing major streets.

Wael alhajyaseen's picture

Analysis on the Variation of Left-Turning Vehicle Trajectories inside Intersections

Journal Title, Volume, Page: 
Journal of the Eastern Asia Society for Transportation Studies (EASTS), Vol.9, pp.1543-1557
Year of Publication: 
2011
Authors: 
Wael Alhajyaseen
Department of Civil Engineering, Nagoya University, Nagoya 464-8603, Japan
Current Affiliation: 
Department of Civil Engineering, An-Najah National University, Nablus P.O. Box 7, Palestine
Asano Miho
Department of Civil Engineering, Nagoya University, Nagoya 464-8603, Japan
Kazufumi SUZUKI
National Institute for Land and Infrastructure Management, Japan
Hideki Nakamura
Department of Civil Engineering, Nagoya University, Nagoya 464-8603, Japan
Preferred Abstract (Original): 
Although several safety countermeasures such as reforming intersection layouts have been implemented, methods to evaluate their effects prior to installation has not yet been established. One of the important safety issues at signalized intersections is the interaction between left-turning vehicles (left-hand traffic) and pedestrians/cyclists. This paper aims to analyze and model the trajectory variations of left-turning vehicles. Vehicle trajectories are collected at several signalized intersections with various traffic and geometric characteristics by video observations. The analysis reveals a significant variation in trajectories depending on intersection angle, number of exit lanes and vehicle type. For modeling individual vehicle trajectories and their distribution, the Euler-spiral-based approximation methodology is applied. Model validation showed that estimated trajectory distributions explain well the spatial maneuver of left-turning vehicles.
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