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    reviewed paper    Proceedings REAL CORP 2012 Tagungsband   14-16 May 2012, Schwechat. http://www.corp.at   ISBN: 978-3-9503110-2-0 (CD-ROM); ISBN: 978-3-9503110-3-7 (Print) Editors: Manfred SCHRENK, Vasily V. POPOVICH, Peter ZEILE, Pietro ELISEI 563  Pedestrian Crossing Behaviour in Signalized Crossings in Middle Size Cities in Greece  Athanasios Galanis, Eliou Nikolaos (Dr Transportation Engineer Athanasios Galanis, University of Thessaly Greece, Pedion Areos, 38334, Volos, atgalanis@uth.gr) (Assoc. Prof. Nikolaos Eliou, University of Thessaly Greece, Pedion Areos, 38334, Volos, neliou@uth.gr) 1   ABSTRACT Pedestrian road safety is a key point of the transport road safety policy in urban areas. Pedestrians are vulnerable road users and despite their limited representation in traffic events, pedestrian involved injuries and fatalities are overrepresented in traffic collisions. This paper presents the findings from the examination of the pedestrian crossing behaviour in signalized crosswalks. The study took place in the city of Volos, Greece, in peak traffic hours, during the summer of the year 2010. The target of the study was to count the  pedestrian crossing time and velocity for each crosswalk. Furthermore, the target was to identify the illegal  pedestrian crossing with red traffic light, criticize their behaviour and propose remedial actions. More than 1300 pedestrians were recorded using a video camera in twelve signalized crossings located in the center of the city, across main arterials. The pedestrians were categorized according to their sex in men and women and their age in three age groups: 0-20, 20-50 and over 50 years old. The analysis of the pedestrian video data was achieved with the use of a state of the art tool, the Captiv L2100 (TEA). The researcher entered the video data in avi format and created the project, the description protocol and the video configuration. The researcher tested each video, marking each pedestrian crossing in the video sequence window, with great accuracy in a short period of time. After the data analysis and the creation of the post coding file, the results were exported in excel format, where they were following analyzed. Some of the results of the study were that the 17% of the pedestrians crossed the streets with red traffic light. The velocity of the younger pedestrians was 1,32m/sec and of the older ones was 1,19m/sec. Men walked faster (1,32m/sec), than women (1,25m/sec). Furthermore, the pedestrians walked faster crossing the streets with red traffic light (1,34m/sec), than with green one (1,28m/sec). Finally, this study criticizes the lack of  pedestrian road safety education and illegal crossing behaviour. 2   INTRODUCTION 2.1   Pedestrian road safety Pedestrian road safety is a key point of the transport road safety policy in urban areas. Pedestrians are vulnerable road users and despite their limited representation in traffic events, pedestrian involved injuries and fatalities are overrepresented in traffic collisions. Crosswalks are sites where pedestrians face lower levels of road safety, because they have to cross the street and must be aware of the incoming traffic. Intersections with high vehicle flows should be signalized in order to prevent accidents and raise the level of road safety for both pedestrians and vehicle drivers. The pedestrian illegal crossing behaviour is a major fact in the road safety issue. The main concerns are the following: Pedestrians cross the streets without noticing the incoming traffic, usually because their attention is distracted. Pedestrians usually miscalculate the traffic gaps. Pedestrians walk across the street, usually due to lack of space on sidewalks. Pedestrians cross the streets in midblock location or out of designated crosswalks. Pedestrians do not follow the indications of the traffic lights. 2.2   Objective of the study This study examines the pedestrian crossing behaviour in twelve signalized crosswalks located across main urban arterials in the city of Volos, Greece with the use of a new tool that analyzes video data: Captiv L2100 (TEA). The pedestrians were categorized according to their age and sex. The main questions of the study were the following: How much is the pedestrian crossing time.  Pedestrian Crossing Behaviour in Signalized Crossings in Middle Size Cities in Greece 564  REAL CORP 2012: RE-MIXING THE CITY  –  Towards Sustainability and Resilience?    How much is the pedestrian crossing speed. Do pedestrians cross the street with red or green traffic light. 3   LITERATURE REVIEW 3.1   Pedestrian crossing behaviour Many studies have examined the pedestrian crossing behaviour analyzing several factors. Rosenbloom (2008) analyzed the behavior of 1392 pedestrians in signalized crosswalks. The first hypothesis was that  pedestrians’ behavior waiting to cross the street depends on the factor of being alone or in group. It was expected that the pedestrians would be more optimistic of crossing the street with red traffic light if they were accompanied. Furthermore, the second hypothesis was that he pedestrians would be more optimistic of crossing the street with red traffic light if another pedestrian crossed before him. The first hypothesis did not come true, but the second did so. Moreover, men were more optimistic to cross the street with red traffic light than women. At last, the longer waiting time in red light phase and the less waiting pedestrians increases the possibility of a pedestrian crossing the street with red traffic light. Hill and Holland (2008), analyzed the factors that influence the pedestrians’ crossing behavior. Using video data they checked the crossing decisions of 213 pedestrians. They counted safe or not traffic gaps for every  person, according to their walking speed. The most unsafe choices were taken from men and especially the older ones. Factors like the pedestrians’ driving experience, their physical skills, walking speed, sex, age and understanding of the traffic characteristics, were important in order to decide where and when to cross the street. Pedestrian risk decreases as pedestrian flow is also decreased (Leden, 2002). He made that conclusion after studying pedestrian accident data from 300 signalized intersections in Hamilton, Ontario, during the years 1983-1986. Pedestrian safety at semi-protected schemes, where left-turning vehicles face no opposing traffic  but have possible conflicts with pedestrians, was compared with pedestrian safety at normal non-signalized approaches, where right-turning vehicles have potential conflicts with pedestrians. Pedestrian safety seems to  be affected much more by the traffic pattern (left or right-turning traffic). At low vehicular flows, right turns and semi-protected left turns tend to be equally safe for pedestrians, but right turns are safer for pedestrians than semi-protected left turns at high vehicular flows. If risk for pedestrians is calculated as the expected number of reported pedestrian accidents for pedestrian, the risk decreases with increasing pedestrian flows. One explanation could be increased driver alertness with increasing pedestrian flow. However, an increased  pedestrian flow might lead to more pedestrian accidents if promotion is not accompanied by appropriate safety measures. Ekman (1996) examined 95 non-signalized intersections in Malmo and Lund in Sweden and concluded that the rate of pedestrian conflicts per pedestrian was not influenced from pedestrian flow. According to Ekman the individual pedestrian does not seem to benefit from the presence of other pedestrians. Another explain is that the motorists expect the presence of pedestrians (at least if pedestrian flow exceeds 30 pedestrians per hour. Ekman also found that if risks for pedestrians are calculated as the expected number of reported  pedestrian accidents or conflicts for pedestrian, the risk increases as traffic flow is also increased. Signalized intersections should consider signal phases for pedestrians which do not significantly delay them. Wang et al (2008) concluded that with high delay, pedestrians are likely to violate the signal. From field observations, most pedestrians searched for traffic gaps and crossed the street without following the traffic signal indications. Furthermore, pedestrian intervals should adjust to the vehicle crossing phase, based on the rule that no conflicting phase should be on together. Pedestrian road safety depends on their exposition on traffic flow. Many studies have concluded that about 25% of the pedestrians cross the streets illegally (Mullen et al, 19 90). Keegan and O’Mahony (2003) reported that 35% of the pedestrians cross during the red light phase. Pedestrians usually cross the streets in sites they consider as more convenient or located across their desire route in order to achieve minimum time delay of physical effort. Many studies have used video data in order to examine the pedestrian crossing behaviour (Hao et al, 2008; Jiangang et al, 2008; Eliou and Galanis, 2009). Some of them use state of the art equipment. Ismail et al (2009) used a real time video data analysis system, which registers vehicle and pedestrian tracks and  Athanasios Galanis, Eliou Nikolaos Proceedings REAL CORP 2012 Tagungsband   14-16 May 2012, Schwechat. http://www.corp.at   ISBN: 978-3-9503110-2-0 (CD-ROM); ISBN: 978-3-9503110-3-7 (Print) Editors: Manfred SCHRENK, Vasily V. POPOVICH, Peter ZEILE, Pietro ELISEI 565  recognizes traffic conflicts. Relative equipment can examine bicyclists’ behaviour. Constant et al (2010) used an “Intelligent Video Analysis System” (IVAS). Connecting an in ternet protocol (IP) with a video camera in a building above the tested street they could track the bicyclists’ route and count their speed. 4   METHODOLOGY 4.1   Data collection The crosswalks where located across the Benizelou St. and Kartali St, which are main arterials located in the center business district of the city (Fig. 1). The crossing streets were the following: Gallias St. (collector arterial) 28 Oktovriou St. (collector arterial) Dimitriados St. (main arterial) Iasonos St. (man arterial) The data collection took place in June 2010, during peak traffic hours (12:00-14:00). A video camera was put in the opposite of each crosswalk in order to have a complete view of the pedestrians waiting and crossing the street in both sides. The time duration of each video record was 30min for each crosswalk. After the video data collection, certain amount of photos of the crosswalks were collected and the crosswalks’ length was noticed in order to count the pedestrians’ speed. Fig. 1: Study area 4.2   Data analysis After the video data collection, the video was exported from the camera to the pc in avi format in order to be compatible with the Captiv L2100 software. The first step of the analysis was the creation of the project in the site: C:\Program Files\Captiv L2100\ Project. The second step was the formation of the “Description Protocol”, which is the most important step of the analysis because the researcher forms the coding (Fig. 2). The pedestrian crossing behaviour was analyzed according to their sex and age. The columns of the description protocol were the following: Code: 020mrs (abbreviation of the characteristic) Coding: 020 man red start (analytic presentation of the characteristic) Class: 1man C: Color of each code  Pedestrian Crossing Behaviour in Signalized Crossings in Middle Size Cities in Greece 566  REAL CORP 2012: RE-MIXING THE CITY  –  Towards Sustainability and Resilience?    12 classes and 24 codes were formed because in order to notice the time when the pedestrians start and finish crossing the street. So, the coding “020 man red start” describes a pedestrian in the age group of 0 -20 years old who starts crossing the street with red traffic light and the coding “020 man red stop” describes the  pedestrian in the age group of 0-20 years old who stops crossing the street with red traffic light. For each coding line a proper colour was selected. With red color was marked the coding referring to pedestrians who crossed the street with red traffic light and with green colour the ones who crossed with green traffic light. Darker colours referred to men and brighter to women. Fig. 2: Description Protocol (Captiv L2100) After the formation of the description protocol, wa s formed the “Video Configuration” file (Fig. 3). This file was created when the videos were entered in the project. Each video was characterized from its description name, the file where it was saved, the start and end time and its duration (about 15min). Fig. 3: Video Configuration (Captiv L2100) The next step was the formation of the “Video Sequence” file, which was the basic tool for our analysis (Fig. 4). Each button referred to a coding and its one colour (Fig. 2). We run the videos and marked each  pedestrian start and stop time, based on our coding. We were able to stop the video (pause), play it back or synchronize it in a selected time when a pedestrian crossed the street. All the registrations were saved in a “Post Coding” file, which refers to  the start and stop time of the pedestrian crossing according to the coding.
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