Roads congestion pricing has been considered as an effective solution following the successful implementation of such programs by many cities such as Singapore, Stockholm, and London. In multiple cases, congestion pricing projects have not been implemented, and multitudinous industrialized countries’ governments are struggling to find an effective and satisfactory way of introducing congestion pricing schemes that will not be affected by the public’s negative opinion and resistance. The lack of political and public acceptability can, therefore, be blamed for the nonimplementation of many congestion pricing projects in many cities around the world. This paper reviews eight cases where congestion pricing schemes were implemented or rejected, as well as the major influencing factors that enable congestion pricing introduction and acceptability by road users, discusses public and political acceptance of urban road pricing, and provides a valuable guideline for policy and decision-makers.
In order to make the congestion pricing policy more equitable and effective, and take a full consideration the time-dependent nature of traffic flow and the dynamics of users' departure time decisions, an optimal dynamic congestion pricing problem is addressed in this paper. A nonlinear distance-based toll considering the congestion-level correction is levied for road users in a charging cordon. It is assumed that both users' departure time and route choice behavior follow the dynamic user equilibrium (DUE) principle. A bilevel programming model for the nonlinear distance-based dynamic pricing which considers the congestion-level correction is formulated to determine the optimal toll rate. The upper level aims to maximize the total social benefits, while the lower level depicts user' departure time as well as route choice behavior in terms of the DUE theory. The model proposed here can be used to design the optimal toll rate for the dynamic congestion pricing.
Pedestrians are more likely to be seriously injured in vehicle collisions. In fact, multiple collisions between vehicles and pedestrians occur on residential roads that lack street-to-sidewalk dividers and have numerous blind spots. Traditional traffic safety features and equipment, such as speed bumps and traffic signs, are not always sufficient to prevent pedestrian accidents on such residential roads. Therefore, we suggest a collision risk warning service for residential roads as a solution to this issue. We use CCTVs with computer vision techniques and radar to accurately detect objects in real-time and to trace their trajectories. In addition, we employ a time-to-collision-based method to identify dangerous situations. The service warns drivers and pedestrians about hazardous situations using a light-emitting diode sign board. We applied our service to three different roads on a university campus in Seoul, Korea, and then conducted a user survey to evaluate the service. In summary, more than 90% of respondents stated that the service was necessary for these specific locations, and 76.9% noted that the service significantly contributed to traffic safety on the campus. This implies that the proposed service improved traffic safety and can be applied to various locations on residential roads.
<abstract> <p>Congestion pricing has been unquestionably recognized as an efficient strategy for managing traffic demand following the successful introduction of such schemes in a number of cities. However, the lack of political and public acceptance can be blamed for the nonexecution of congestion pricing projects in numerous cities around the world. This paper sheds light on the impacts of congestion pricing and the factors influencing its public acceptance. Our research was aimed to answer the following questions: (ⅰ) What are the factors that can influence public acceptance of congestion pricing? (ⅱ) What are the impacts of implementing a congestion pricing scheme? (ⅲ) How can we overcome the barriers that currently stand in the way of public acceptance of congestion pricing? To answer these questions, we developed a case study combining stated preference and revealed preference data collected in Nanjing, China. The study analyzes the acceptance of congestion pricing and the factors influencing it, such as socioeconomics, the perceived impact, fairness and public transit-related factors. We compare logistic regression and artificial neural network models to gain a deeper knowledge of the important factors and investigate the respondents' attitudes. The results revealed that the perceived impacts on congestion, the environment, trips to the city center, revenue allocation, public transportation price satisfaction, annual income, fairness, car ownership and travel frequency, along with the efficiency and capacity of public transport systems, need to be included when evaluating individuals' acceptance of congestion pricing. Among these, the perceived impacts on congestion and the environment, fairness and revenue allocation to public transportation are the most significant factors. Moreover, we offer further qualitative insight into the individual, economic and social impacts of congestion pricing. This paper provides decision- and policy-makers with important advice on how to promote public acceptance when considering the implementation of a congestion pricing scheme.</p> </abstract>
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