How Do Transit Commuters Make Trade-offs Between Schedule Delay Penalty and Congestion Cost? Empirical Study in Beijing
operations - traffic, ridership - commuting, ridership - attitudes, policy - congestion, mode - rail, mode - tram/light rail
Work trips, Travel behavior, Traffic delay, Traffic congestion, Schedules, Peking (China), Peak periods, Mental attitudes, Mathematical models, Light rail transit, Journey to work, Gridlock (Traffic), Costs, Commuters, Beijing (China), Attitudes, Arrival times
The riding behavior of commuters who take transit from home to workplace during peak periods is examined. Costs associated with the schedule delay penalties for early or late arrival and in-vehicle congestion are considered for formulating a mathematical programming model that generates a solution of equilibrium transit riding behavior. Survey data obtained from the No. 13 light rail transit in Beijing are used to show how these commuters make the trade-off between the two costs. A linear relationship was found between the in-vehicle passenger number and the corresponding transit run number. The concavity and convexity characteristics of in-vehicle congestion cost function and the schedule delay cost function should be opposite. In other words, if the schedule delay cost function is concave, the marginal cost of in-vehicle congestion must increase with each additional passenger; that is, the congestion function is convex, and vice versa. Furthermore, the ratio of arrival late and early penalties was estimated by using a piecewise linear schedule delay cost. The ratio is around 1, which is quite different from the finding reported in literature and thus reflects that commuters in different countries may have different attitudes to the schedule delay costs.
Tian, Qiong, Huang, Hai-Jun, Lam, William, (2009). How Do Transit Commuters Make Trade-offs Between Schedule Delay Penalty and Congestion Cost? Empirical Study in Beijing. Transportation Research Record: Journal of the Transportation Research Board, 2134, pp 164-170.