PEDESTRIAN TRAVEL PATTERN AT PUBLIC TRANSIT STATIONS

Transcription

1 International Journal of Civil, Structural, Environmental and Infrastructure Engineering Research and Development (IJCSEIERD) ISSN(P): ; ISSN(E): Vol. 6, Issue 5, Oct 2016, TJPRC Pvt. Ltd. PEDESTRIAN TRAVEL PATTERN AT PUBLIC TRANSIT STATIONS NOOR SHAZREEN A.RAHMAN 1, YASMIN SUHARA AHMAD KAMAL 2, FARAH HAYATI MUSTAFA 3 & LI-SIAN TEY 4 1 Faculty of Civil Engineering, Universiti Teknologi MARA, Pasir Gudang Campus, Malaysia 2, 4 Faculty of Civil Engineering, Universiti Teknologi MARA, Pulau Pinang Campus, Malaysia 3 Science and Mathematics Department, Universiti Teknologi MARA, Pulau Pinang Campus, Malaysia ABSTRACT Public transit station is provided by offering affordable basic mobility for non-drivers, decreasing the traffic congestion and increasing the connectivity in the urban areas. Therefore, pedestrian infrastructure is built near the public transit station to serve the public transit users provided the safety and comfort is guaranteed. To ensure the safety of pedestrians, the level of awareness of pedestrian, pedestrian risky behaviour and pedestrian travel pattern towards certain types of pedestrian facilities are important. Questionnaire and video recording were incorporated in the current study to investigate the fore-mentioned parameters. The study areas selected are a few main public transit stations in Penang; namely, Komtar Bus Terminal, Pangkalan Raja Tun Uda Ferry Terminal and Pangkalan Sultan Abdul Halim Ferry Terminal. The pedestrian level of awareness through questionnaire survey was grouped into three different categories: knowledge, practice and concern. The results from the mean score ranked knowledge as the highest among the other variables followed by practice and concern. This finding reflects that knowledge does not promise, practical action and self-concern which governs their safety. Meanwhile, the risky behaviour and the pedestrian travel pattern were analyzed from the video recording. The overall observation of the three study areas showed that non-compliance behaviour rate is comparatively high. The risky behaviour and the pedestrian travel pattern were then further analyzed into compliance and non-compliance patterns according to variables studied; gender, age groups, alone/in groups, with/without carrying things, and with/without facing obstacle. Original Article KEYWORDS: Level of Awareness, Public Transport Station, Risky Behaviour, Safety, Travel (Crossing) Pattern Received: Sep 03, 2016; Accepted: Sep 27, 2016; Published: Oct 03, 2016; Paper Id.: IJCSEIERDOCT20164 INTRODUCTION Public transit station is a shared passenger transport service which serves the general public either privately or publicly owned. With the availability of the public transit, the infrastructure is built in the surrounding area of the stations such as sidewalks, crosswalk, mid-block crossing and others, to serve the major users or known as pedestrians, in term of comfort, safety and to reduce the pedestrian-vehicle conflict. In the urban area, pedestrians are taken into account in the planning and design of the traffic facilities and controls. According to the National Traffic Safety Administration (NHTSA), (2014), most pedestrian deaths occur in cities (73%) and at places other than intersections (70%). It has also been reported that each year, nearly 5,000 pedestrians die in motor vehicle- related accidents, and approximately 76,000 pedestrians in 2012 suffered injuries when hit by a car or truck (Reuters, 2015). Meanwhile, Malaysia has suffered 25 accident-related deaths per 100,000 of the population in 2010, compared to 17 deaths in Thailand, 8.5 in Indonesia and 3.8 deaths in Singapore editor@tjprc.org

2 34 Noor Shazreen A. Rahman, Yasmin Suhara Ahmad Kamal, Farah Hayati Mustafa & Li-Sian Tey (World Health Organization, 2013). In addition, the pedestrian is the third most number of fatalities due to road accidents (Jabatan Keselamatan Jalan Raya, 2014). In Penang Island, over the past year, as many as 32 out of 401 fatal accidents involved pedestrians (Utusan Online, 2013). Similar to national statistic, in Penang, the pedestrian is reported to be the third highest group killed in a road accident after motorcycle and car. There is no single factor that completely responsible for the problem of pedestrian-vehicle crashes resulting in injuries and fatalities. The combination of risky pedestrian behaviour, vehicle and driver factors, problematic physical environments and other special conditions contribute to pedestrian-vehicle accidents. The factors such as driver negligence, distraction on the part of the pedestrian or those in wheelchairs or strollers were found to be the most common factors that cause the pedestrian accidents (Reuters, 2015). Pedestrian mobility is usually not similar from one place to another depending on circumstances and trip purposes. The result of pedestrian mobility depending on a variety of pedestrian facilities and surroundings, therefore it will create a variety of patterns (Washington State Department of Transportation, 1997). The determination of travel pattern is important to the relevant authorities to improve pedestrian facilities and to ensure the safety and comfort of the pedestrian (Roads and Traffic Authority, 2002). Predicting individual movement patterns through space is becoming an increasingly important goal of urban and transport planners interested in designing effective urban spaces for pedestrians (Willis et al., 2004). Based on the previous research, there are many variables and methods that had been studied and used to determine the pedestrian behaviors. Jain et al. (2014) used four different methods including direct observation, video observation, time lapse photography and pedestrian opinion survey by analyzing pedestrian crossing speeds in order to determine pedestrian travel behaviour. While Daamen & Hoogendoorn (2003) organised walking behaviour experiments to study the effect of walking behaviour and flow characteristic towards four process variables of interest; namely free-speed, walking direction, density, and the effect of bottlenecks. In the current paper, parameter of pedestrian compliance is used to investigate pedetrian behaviour towards a series of pedestrian facilities at the selescted study sites, through pedestrian awareness survey and video recording of pedestrian risky behaviour and their travel patterns. Pedestrian compliance is defined as pedestrian adhere to the traffic rules. For example, crossing the roads using the pedestrian crossing provided to avoid pedestrian-vehicle conflicts. Similarly, pedestrians should stop whenever the pedestrian traffic signal turns red. This paper is structured as follows: Section 2 provides a description of study background and methodology of data collection; Section 3 presents and compares the results from the field surveys and Section 4 concludes the main findings. METHODS The current study was conducted in the city of Penang, Malaysia. Penang is a tourist island which is a great destination for vacation with many historical buildings and monuments to be visited. Penang can be reached by various modes of transportation either by road, rail, sea or air. Hence, among the public transport provided in Penang are public bus services by Rapid Penang and cross-channel ferry services by Penang Ferry Service. Therefore, pedestrian activities at these locations are high. The three main public transit stations were selected as study areas; namely Komtar Bus Terminal, Pangkalan Raja Tun Uda Ferry Terminal and Pangkalan Sultan Abdul Halim Ferry Terminal. These locations are selected based on the high Impact Factor (JCC): NAAS Rating: 3.01

3 Pedestrian Travel Pattern at Public Transit Stations 35 pedestrian flow due to the center of attraction from the public transport users and many pedestrian facilities provided. Komtar Bus Terminal (Site 1) is located below the Menara Komtar, the tallest building in Penang and the landmark in the city of George Town. It neighbored to 1 st Avenue Mall and Perangin Mall and these three buildings are connected by sky bridge where people could move from one building to another without having to cross the busy streets of George Town. Komtar Bus Terminal is the hub of the bus services operated by Rapid Penang Bus. All the bus routes of Penang radiate from this terminal. The schematic diagram of the pedestrian facilities at Komtar Bus Terminal is shown in Figure 1. Figure 1: Schematic Diagram of Pedestrain Faclities in Komtar Bus Terminal Pangkalan Raja Tun Uda Ferry Terminal (Site 2) is the place for people arriving by ferry in Penang from the mainland Butterworth. It is also one of the two ferry terminals that provide services to cross from the mainland to the island. Other than ferry service, Pangkalan Raja Tun Uda also provides other public transport such as taxi and bus services. The taxi service is located next to the bus terminal while the bus terminal is the main terminal for Rapid Penang buses. Figure 2 shows the schematic diagram of the pedestrian facilities at Pangkalan Raja Tun Uda Ferry Terminal. between Figure 2: Schematic Diagram of Pedestrain Facilities in Pangkalan Raja Tun Uda Ferry Terminal Pangkalan Sultan Abdul Halim (Site 3) or known as Butterworth Ferry Terminal provides ferry services that ply editor@tjprc.org

4 36 Noor Shazreen A. Rahman, Yasmin Suhara Ahmad Kamal, Farah Hayati Mustafa & Li-Sian Tey Geroge Town and Butterworth, transporting both passengers and vehicles to and from the island. The ferries shuttled across the channel to Pangkalan Raja Tun Uda in George Town. There is Butterworth Railway Station, taxi station, Rapid and Express Bus Terminal located not far from Butterworth Ferry Terminal. Figure 3 shows schematic diagram of the pedestrian facilities provided in Pangkalan Sultan Abdul Halim Ferry Terminal. Figure 3: Schematic Diagram of Pedestrain Facilities in Pangkalan Sultan Abdul Halim Ferry Terminal Among the facilities provided at the studied areas are pedestrian signal, pedestrian crossing (zebra/ladder), median, foot walk/footpath and pedestrian bridge as summarised in Table 1. Table 1: Pedestrain Facilities Available at the Three Study Areas In this study, questionnaire survey and video recording were two methods that have been adopted for data collection. The questionnaire survey was used to determine the pedestrian level of awareness about the facilities provided. The questions were divided into 6 parts; namely; Part A - pedestrian signal, Part B - pedestrian crossing, Part C - median, Part D - foot walk, Part E - pedestrian bridge and Part F - pedestrian characteristics. Each part consists different questions related to knowledge, practice and concern. Questions on the knowledge are to get the information, whether the respondents have knowledge on the facilities provided where they might have learnt from the institutions such as schools or universities. Meanwhile, questions on practice are to determine the attitudes of the respondents towards the facilities provided. Lastly, questions on concern is used to analyse whether the respondents awared about their safety at the study Impact Factor (JCC): NAAS Rating: 3.01

5 Pedestrian Travel Pattern at Public Transit Stations 37 sites. A pilot study which consisted of 10 sets of questionnaire was conducted to check on the validity and reliability by using Chronbach s Alpha. Some questions which were not related to the study were discarded to fit with the objectives of the study. The alpha values have ranged from 0 to 1; with alpha values more than 0.5 is considered to be acceptable. However, the ideal value of Chronbach s Alpha coefficient should be above 0.7 (DeVellis, 2003). 90 sets of the refined questionnaire were then distributed among the pedestrian at the studied sites. In the questionnaire, the scale factored analysis was adopted. There are five scales of satisfying statement including strongly disagree, disagree, fair, agree and strongly agree, with 1 to 5 scale number, respectively. The mean score of each variable of interest was analysed and represented in decimal form. Video recording was used to identify pedestrian risky behaviour and travel pattern. A video camera was erected at the highest location for each of the sites to enable clear view of the pedestrian movement and behaviour as well as the operations of the warning devices. The video footage was captured under normal daylight condition and was replayed on a personal computer in order to compile the data. In determining the risky behaviour, the data were counted for both compliance and non-compliance towards the pedestrian facilities. From the observation, pedestrian compliance is defined as pedestrian total adherence to the traffic rules. Five variable were sorted; namely gender, age groups (children, teenager, adult and senior citizen), walking categories (individual, partner or grouping), carrying things such as luggage, backpack or handbags (with or without loads) and facing an obstacle such as buses, taxis or bicycles (with or without obstacle). Similarly, pedestrian travel (crossing) patterns had been sorted out from the video recording. The patterns were determined based on the movement of the pedestrian while using the facilities at the study areas. Analysis was done by compiling their travel patterns into the compliance and non-compliance categories. RESULTS The data for the demographic characteristics of the respondents contain gender and age group for the three sites. Majority of the respondents are woman, 66.67%, compare to male, 33.33%. Age criteria were divided into four groups which are children s group (<18 years old), teenager (19 25 years old), adult (26 50 years old) and senior citizen (>51 years old). Most of the respondents at the three sites are teenagers (53.33%), followed by children (30.00%), adult (14.44%) and lastly senior citizen (2.22%). Level of Awareness The pedestrian s level of awareness was determined using the information obtained from the questionnaire survey which contain a series of questions testing the respondents reaction towards the rule or pedestrian facilities at the study area. Before further analysis, the effectiveness of the new set of questionnaire has been done using Chronbach s Alpha Coefficient according to the study areas. Since all of the Alpha Coefficient was above 0.5 as shown in Table 2, the questionnaire was acceptable and valid to be used for the three selected study areas. The result of the questionnaire was compiled and analysed using SPSS. The variables ranked using mean score data is shown in Table 2. The mean score was a value that measured the average values based on the scale factored analysis with 1 to 5 scale number. The mean score for level of awareness in term of the knowledge are 4.178, and for Sites 1, 2 and 3 respectively. These values were the highest among the three variable of interest, followed by practice (mean score 3.961, and for Sites 1,2 and 3 respectively) and concern (mean score 3.687, and for editor@tjprc.org

6 38 Noor Shazreen A. Rahman, Yasmin Suhara Ahmad Kamal, Farah Hayati Mustafa & Li-Sian Tey Sites 1,2 and 3 respectively). The results of each variable of interest in the three study areas was approaching the same mean score values, showing that the level of awareness is similar across the study areas. It is interesting to find, the trend of mean score values shows that pedestrians at all study areas know the existence of the regulation and function of the facilities provided. However, although they know about the advantages of practicing safety behaviour, they have seen it as something trivial and omit the rule if they felt inconvenienced. Table 2: The Chronbach s Alpha Coefficient and Mean Score for Variables of Interest According to the Study Areas Pedestrian Risky Behaviour From the video recording, the pedestrian movement was categorised into compliance and non-compliance behaviour, according to five potential variables; namely gender, carrying things, facing obstacles, categories of group walking and age as described in Section 2 and shown in Figure 4. Data from the three study sites was combined for analysis. Based on the three study areas, 69.26% of females complied to the pedestrian facilities rules compare with male, 64.63%. This proves the evidence of the previous studies that women tend to comply the rule and more careful than men when crossing the roads (Tom & Granie, 2011). For the carrying things compliance criteria, 71.97% of pedestrian that not carrying things shows higher percentage compared with 63.97% of pedestrian that carrying things. Meanwhile, the pedestrian that not facing any obstacle to cross the road tend to comply the criteria with higher percentage of 67.09% rather than 63.58% that not complying the rule because of facing an obstacle. Pedestrians tend to expedite their journey in order to decrease the burden of carrying things and to avoid the obstacles. Individual walking shows higher percentage of compliance, 70.31% than walking in a group, 40.09%. Lastly, the highest compliance age group was teenagers, 74.64%, and the least compliance was children group, 39.74%. The finding that teenager age group has highest compliance rate, is contradicted with common understanding from previous study that the higher the age, the higher the risk of fatality (Martin, 2006; National Highway Traffic Safety Administration, 2014). This finding probably indicates that compliance rate is not a main contributing factors to the risk of fatality. Impact Factor (JCC): NAAS Rating: 3.01

7 Pedestrian Travel Pattern at Public Transit Stations 39 Figure 4: Compilance Percentage According to the Pedestrain Characterestics Pedestrian Travel Pattern The analysis of the travel pattern was sorted out based on the compliance behaviour towards facilities. Figure 5 to Figure 9 shows the compliance and non-compliance travel patterns by the pedestrian when utilised the facilities at the study sites, where Pattern 1 indicates the compliance pattern, while Patterns 2, 3 and 4 indicate the non-compliance patterns. From the observation, there was similar travel pattern for pedestrian zebra crossing facilities for each study site as shown in Figure 5. Figure 5: Travel Pattern at Pedestrian Zebra Crossing Facilities at Sites 1, 2 And 3 editor@tjprc.org

8 40 Noor Shazreen A. Rahman, Yasmin Suhara Ahmad Kamal, Farah Hayati Mustafa & Li-Sian Tey Figure 6: Travel Patterns at Pedestrain Ladder Crossing and Signal Facilities at Site 1 Figure 7: Travel Patterns at Pedestrain Foot Walk/Footpath Facilities at Site 1 Figure 8: Travel Patterns at Pedestrain Bridge Facilities at Site 2 Impact Factor (JCC): NAAS Rating: 3.01

9 Pedestrian Travel Pattern at Public Transit Stations 41 Figure 9: Travel Patterns at Foot Walk at Site 3 For the overall study areas, the pedestrian at Site 3 shows the highest percentage of compliance travel pattern to the facilities with 88.57%, as shown in Figure 10. Most of pedestrian take their own risk by neglecting the safety behaviour at Site 1 and Site 2 with the percentage of non-compliance pattern 64.58% and 69.25% respectively. As stated before, the facilities that provided at Site 3 were only pedestrian crossing and foot walk/footpath. The basic facilities unencumbered and pedestrians tend to comply with the rules as compared with other areas that have a facility that was tended to non-complying rules such as pedestrians need to climb the stairs to cross the bridge and long crossing distance (Refer Table 1). Figure 10: Percentage of Compliance Behaviour According to Sites 1, 2, 3 CONCLUSIONS In conclusion, the level of awareness at the three locations reflects that the respondents have higher knowledge about the implemented facilities and rules. However, they tend to break the rules by not practicing the knowledge and neglecting the concern for their safety. From the observation, the groups that show the highest percentage of non-compliance behaviour were the male group, children group, pedestrians walking in a group, pedestrian carrying things and facing an obstacle when crossing the road. These groups were exposed to the risk of accident and fatality. In addition, there are variations of pedestrian travel pattern. Although there maybe other contributing factos, but in general the result tells that, the pedestrian tend to comply with the facilities which are easily dealt with and less burdensome. editor@tjprc.org

10 42 Noor Shazreen A. Rahman, Yasmin Suhara Ahmad Kamal, Farah Hayati Mustafa & Li-Sian Tey ACKNOWLEDGEMENTS AND LEGAL RESPONSIBILITY The authors would like to express sincere gratitude to the Ministry of Higher Education under RAGS 2014 with reference number 600-RMI/RAGS 5/3 (169/2014) and Universiti Teknologi MARA for the opportunity to carry out this research by supporting the financial aid. REFERENCES 1. National Highway Traffic Safety Administration (NHTSA) (2014). Traffic Safety Fact 2012 Data. U.S. Department of Transportation 2. Reuters, T. (2015). Pedestrian Accident Overview. (Find Law article, Thomson Reuters). Retrieved from 3. World Health Organization (WHO) (2013). World Report on Road Traffic Injury Prevention. (Global status report on safety) Retrieved from 4. Jabatan Keselamatan Jalan Raya (2014). Pelan Keselamatan Jalan Raya (Ministry of Transportation report). Retrieved from Documents/Darat/Pelan+KJRM pdf. 6. Utusan Online (2013, May 18). Pedestrian is the Third Highest Contributor of Death. (Newspaper report). Retrieved from 7. Washington State Department of Transportation (WSDOT) (1997). Pedestrian Fasilities Guidebook: Incorporating Pedestrians Into Washington s Transportation System. Retrieved from 8. Roads and Traffic Authority (RTA) (2002), How To Prepare A Pedestrian Access And Mobility Plan: An easy three stage guide. (Technical manual). Retrieved from 9. Willis, A., Gjersoe, N., Havard, C., Kerridge, J., & Kukla, R. (2004). Human Movement Behaviour in Urban Spaces: Implications the Design and Modelling of Effective Pedestrian Environments. Environment and Planning B: Planning and Design December doi: /b Jain, A., Gupta, A., & Rastogi, R. (2014). Pedestrian Crossing Behaviour Analysis At Intersections. International Journal for Traffic and Transport Engineering doi: /ijtte (1) Daamen, W., & Hoogendoorn, S. (2003). Experimental Research of Pedestrian Walking Behavior. Transportation Research Record, 1828(1), doi: / DeVellis, R. F. (2003). Scale development: Theory and applications (2nd ed.). California: Sage Publications. 13. Tom A & Granie M (2011). Gender differences in pedestrian rule compliance and visual search at signalized and unsignalized crossroads. Accident Analysis and Prevention. 14. Elservier. doi: /j.aap Martin A. (2006). Factor Influencing Pedestrians Safety: A Literature Review. Project RePort: London Road Safety Unit). Retreieved from Impact Factor (JCC): NAAS Rating: 3.01