Yok Hoe Yap
@utb.edu.bn
Assistant Professor
Universiti Teknologi Brunei
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Somnuk Phon-Amnuaisuk, Soon-Jiann Tan, Yok-Hoe Yap, Florence Chiao-Mei Choong, Pikul Vejjanugraha, Kok-Chin Khor, and Keng-Hoong Ng
IEEE
This study focuses on the optimization of Traffic Light System (TLS) control through the use of adaptive agents. The performance of adaptive cycle TLS was compared with fixed cycle TLS. Two different adaptive cycle TLS agents were investigated, reactive and Deep Q-Network (DQN) agents. The reactive agent adjusted its control signals based on traffic measures such as queue length, while the DQN agent employed a deep reinforcement learning algorithm to determine its control signals. Two sets of simulations were conducted to evaluate the performance of both approaches. The results showed that the adaptive cycle TLS was more effective in reducing waiting times and increasing traffic throughput than the fixed cycle TLS. Among the adaptive agents, the reactive agent outperformed the DQN agent, due to the difficulty in learning an optimal policy in the traffic control domain, which has a non-stationary and complex nature. This preliminary study showed the potential benefits of using adaptive agents for traffic light control, and further studies in various areas such as employing more advanced TLS control methods, expanding the scale of the study, and applying real-demand in the simulation, could be carried out in future work.
El-Said Mamdouh Mahmoud Zahran, Soon Jiann Tan, Eng Hie Angel Tan, Nurul Amirah 'Atiqah Binti Mohamad 'Asri Putra, Yok Hoe Yap, and Ena Kartina Abdul Rahman
Informa UK Limited
AbstractReducing road traffic accidents (RTA) and their socioeconomic costs is an increasingly important priority in many countries. In recent years, many authors have proposed various approaches t...
El-Said Mamdouh Mahmoud Zahran, Soon Jiann Tan, Yok Hoe Yap, Eng Hie Tan, Christian Marc Francisco Pena, Hui Fong Yee, and Mohammad Rakib Uddin
IEEE
The aim of this paper is to investigate the impact of alternate road lighting (i.e. switching off every other road light at selected roadways) on road traffic accident (RTA) hotspots using Spatial Traffic Accident Analysis (STAA) – a GIS hotspot analysis method that takes into account RTA frequency and socio-economic impact. STAA was used to identify and rank into four hierarchical risk levels day-time and night-time RTA hotspots before and after the implementation of alternate road lighting along a study road. Using the day-time RTA hotspots as a comparison group and night-time RTA hotspots as treatment group, the changes to the length of RTA hotspots of the four hierarchical risk levels were evaluated. There was an overall increase in the lengths of RTA hotspots with moderate and serious risk levels, while there was an overall reduction in the lengths of RTA hotspots with minor and significant RTA risk levels. Some of the limitations of the current study were identified and further research is recommended to validate the current findings.
Muhammad Amirul Afiq bin Ramli, Mohammad Rakib Uddin, Soon Jiann Tan, El-Said Mamdouh Mahmoud Zahran, and Yok Hoe Yap
IEEE
Several measures, such as reduced lighting, may be adopted to minimise energy consumption while providing an optimal and safe level of road lighting. One approach to evaluate the safety impact of reduced road lighting is by using Geographical Information System (GIS) to identify road sections with low level of illumination and high risk of road traffic accidents. The GIS approach required a cost-effective and efficient system to measure the level of lighting provision at close intervals along a road network. This paper presents the development and validation of a road illumination measurement system developed for this purpose. The system is based on TSL2561 illumination sensors, u-blox NEO-6M GPS module, Robotdyn Arduino Mega Pro Embed and Catalex microSD shield. The results showed that the measurements obtained from the developed system followed a similar trend as a commercial light meter, and that it could be used to identify road sections with relatively low levels of illumination for further safety analysis using GIS.
M M Rahman, Y H Yap, N R Ramli, M A Dullah, and M S W Shamsuddin
IOP Publishing
Shortage and delay in materials supply is argued to be one of the most important factors that lead to delay in construction project delivery globally. However, the relevant underlying reasons vary from country to country. As such, this paper summarises the outcomes of a study that targeted identifying causes of shortage and delay in materials supply in Brunei Darussalam. The study was conducted through fifteen semi-structured interviews of contractors and materials suppliers in Brunei. The study identified six causes of shortageof materials and nine causes of delay in materials supply in Brunei. The most importantcausefor shortage of materials relates to the origin or availability of construction materials. On the other hand, the most influential cause of delay in material supply was found to be poor materials procurement and inventory management system, which has other underlying reasons such as late identification of the type of materials needed. The observations are expected to help in formulating or reviewing relevant policies, in order to ensure on-time project delivery.
El-Said M.M. Zahran, Soon Jiann Tan, Yok Hoe Yap, Ena K.A. Rahman, and Nurulhikmah H. Husaini
EDP Sciences
Road Traffic Accidents (RTA) are known to be one of the main causes of fatalities worldwide. One usef ul approach to improve road safety is through the identification of RT A hotspots along a road, so they can be prioritised and treated. This paper introduces an approach based on Geographical Information System (GI S) to identify and prioritise RTA hotspots along a road network using historical RTA data. One particular urban road in Brunei with a historically high rate of RT As, Jalan Gadong, was selected as a case study. Five years of historical RTA data were acquired from the relevant authorities and input into a GIS database. GI S analysis was then used to identify the spatial extension of the RT A hotspots. The RT A hotspots were ranked according to three different schemes: frequency, severity and socio-economic impact of RTAs. A composite ranking scheme was also developed to combine these schemes; this enabled the prioritisation and development of intervention and maintenance programmes of the identified RTA hotspots. A visualisation method of the RTA spatial distribution within each identified RTA hotspot was also developed to determine the most risky road stretches within each hotspot, which is important for treatment prioritisation when limited resources are available.
Yok Hoe Yap, Helen M. Gibson, and Ben J. Waterson
American Society of Civil Engineers (ASCE)
Accurate roundabout capacity models are essential for optimal roundabout designs, but there exist significant differences in the predicted capacities of various state-of-the-art models and in their included explanatory variables. An empirical study into roundabout lane entry capacity was thus performed in the U.K. using data from 35 roundabout entry lanes, where various model forms and explanatory variable sets were tested. Two regression models and an artificial neural network were developed. A negative exponential relationship with circulating flow predicted lane capacity better at high and low circulating flows, and better reflected the overall trends in the aggregated capacity data, compared to a linear model. The regression models performed relatively well and provided better information on the impacts of the variables than the neural network. The models consistently suggest that entry-exit separation and flows exiting on the same arm have stronger significant effects on capacity than variables such as entry angle and entry radius. These findings could thus contribute to an improved understanding of the variables that affect entry lane capacity and therefore the development of better roundabout capacity models.
Nicholas Brian Hounsell and Yok Hoe Yap
Institute for Operations Research and the Management Sciences (INFORMS)
In traffic systems where driving is on the left, right-turning movements tend to be difficult to efficiently accommodate at signal controlled junctions. A hook turn is one potential solution for this. A hook turn is where a right turn is made from the nearside lane rather than an offside lane at a four-leg signalised junction. After entering the junction, the turning vehicle waits at a nearside position in front of the side road stop line, and then proceeds toward the exit arm when the side road signal turns green.
The research described in this paper uses microscopic simulation modelling in an innovative way to compare the traffic performance of a hypothetical hook-turn junction with an equivalent conventional junction with opposed right turns. The simulation model evaluated traffic performance under various combinations of demand flow, turning proportions, and signal timings. It was found that hook turns reduced delays to through traffic from the same approach in nearly all cases. Overall junction performance depended on the scale of any increased delays to left-turning traffic and side road traffic resulting from the hook-turn movement. It is concluded that hook turns could be used much more widely than at present-including where driving is on the right-offering significant operational benefits in the right circumstances.
Yok Hoe Yap, Helen M. Gibson, and Ben J. Waterson
Informa UK Limited
Roundabouts are an increasingly common form of road junction worldwide, and their effective design requires a detailed analysis of maximum vehicle throughput capacities. In this paper, the worldwide state-of-the-art in roundabout capacity modelling is examined, covering the three main methodologies on which models are based: fully-empirical, gap acceptance and simulation. It is shown that due to their limitations, each of these methodologies on their own cannot completely explain the complex behavioural and physical processes involved in roundabout entries, hence all the models require strong semi-empirical or fully-empirical bases using data obtained from their countries of origin. Differences in driver behaviour and methodologies thus result in differences in predicted capacities by the various models, and although local calibration allows some transferability, it is often limited by the availability of data or an incomplete understanding of the relationships between model parameters and capacity.