Predicting the duration and impact of the non-recurring road incidents on the transportation network

Abstract

hour of prediction.Moreover, we are interested in not only predicting incidents' impact but informing the drivers about the current and future traffic state is also our area of concern. Currently, in order to inform or alert the commuters about the traffic situation during the road incidents, several LED displays, better known as variable message signs or VMS messages, have been installed by the LTA on the expressways of Singapore. Therefore, apart from building the predicting models, this thesis also aims to evaluate the impact of VMS displays on the overall traffic distribution of Singapore whether these displays are really helpful to the drivers or not. To this end, the incidents data and their corresponding VMS messages are collected from the two busiest expressways of Singapore, namely Pan Island Expressway (PIE) and Central Expressway (CTE). The analysis shows that approximately 14% of the vehicles change their direction after the VMS messages have been activated.Lastly, since Singapore is a tropical country having a significant amount of rainfall throughout the entire year, the weather condition has a noticeable impact on the traffic of Singapore. Therefore, we also aim to analyze the influence of rainfall on traffic incidents if the frequency of these incidents, especially accidents, increases after rainfall or not. Therefore, the rainfall data acquired from the National Environmental Agency (NEA) of Singapore is analyzed to investigate the correlation between the occurrence of traffic incidents and rainfall. Overall, the obtained results support the hypothesis that the frequency of traffic incidents is higher during rainfall as compared to dry periods. Moreover, the frequency is the highest after rainfall. Besides, it is observed that traffic speed and flow decrease by 10.14% and 3.88% respectively during rainy weather.Overall, this thesis aims to help avoid incident-induced traffic jams by designing the urban traffic prediction models. Thus, the cost of time and fuel can be saved, which will benefit the national economy as a whole.

Travel Demand Management in an Auto Dominated City: Can Travel Behaviour Be Nudged in the Kingdom of Saudi Arabia?

“…A lot of these problems happen as a consequence of high car ownership and use and the decline of the public transportation systems. Therefore, most world cities and local authorities are seriously occupied to fully understand the level of traffic problems and come up with appropriate measures and measures that can mitigate the negative environmental impacts of traffic, which may also lead to improved road safety [14][15][16][17]. Many transport measures have been assessed and tested theoretically and empirically for the purpose of managing congestion and the demand for travel in cities.…”

A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System

“…Recurring congestion occurs regularly, mostly due to the excessive number of vehicles during peak hours [5]. On the other hand, unpredictable events-such as weather, work zones, incidents, and special events-are the causes of nonrecurring congestion [6][7][8]. According to the United States Department of Transportation Federal Highway Administration (DOT-FHWA), nonrecurring congestion contributes to more than 50% of all traffic congestion, where 40% of congestion is caused by recurring congestion [3].…”

“…A sustainable and resilient transportation system should be able to offer interrupted functionality during unexpected events. Due to the increased intensity and frequency of the natural-related disasters, nonrecurring congestion is a field of study that should be explored extensively in terms of measurement approach, predictive analysis, and uncertainty investigation [7,15,[72][73][74]. The probability of occurring congestion varies for different types of events, where some events are completely unpredictable, such as incidents from vehicles crashes unexpected weather changes, and evacuation due to disasters [7,8,75,76].…”