Document Type


Date of Award

Spring 9-30-1975

Degree Name

Doctor of Engineering Science in Civil Engineering


Civil and Environmental Engineering

First Advisor

Harold D. Deutschman

Second Advisor

Leonard W. Schaper

Third Advisor

Ira S. Kuperstein

Fourth Advisor

Julian M. Scher

Fifth Advisor

Frederick G. Lehman


This research analyzes the Passenger Vehicle Interface of the street transit systems and presents applications for design optimization. The Passenger Vehicle Interface (PVI) is defined as the interaction between the passenger and vehicle elements of the street transit system.

Human observer and photographic studies were conducted in 17 cities in the United States and Canada to measure the time for queues of passengers to board various transit vehicles. The data were analyzed by considering seven factors that affect the Passenger Vehicle Interface: Human Factor, Modal Factor, Operating Practices, Operating Policies, Mobility, Climate and Weather, and Other System Elements. Those effects which could be quantified were divided into the categories of direction of flow, method of fare collection, and door characteristics and use. A series of equations for each of these categories was developed to predict passenger service time when the number of alighting or boarding passengers is known or estimated. A range of values was developed for the parameters of each equation to reflect the effects of unquantifiable factors such as the type of passenger, physical characteristics of the passenger, passenger preferences, baggage carried, seating configuration, and congestion. The use of Passenger Influence Zones has indicated that passenger service time can range from approximately six to 14 percent of total trip time, depending upon vehicle type, door use, and method of fare collection. These zones have also been used to indicate how vehicle door use and characteristics can increase berth requirements by up. to 200 percent, and New different methods of fare collection can increase berth productivity in terms of passengers per hour by 87 percent.

Distributions of passenger service times through the vehicle doors were identified based on the analysis of photographic studies and determined to be represented by an Erlang function. The analysis also inferred that the K value in the Erlang function is equal to the number of doors on the vehicle and that the minimum service time is approximately equal to half the average service time. The validity of the Erlang functions was determined by using the special purpose simulation programming language, GPSS, and the Erlang functions to estimate the time requirements for queues of passengers to board vehicles. The simulated times were compared with observed times, and the differences were found to be not statistically significant at the 95 percent level.

A GPSS model was used to simulate the operations of a street tran sit loading area and to evaluate the effects of method of fare collection upon queue length and average waiting time under varying rates of passenger arrivals.

This research provides sufficient information to perform sub- optimizations of several operations within the Passenger Vehicle Interface. Although not directed toward an optimization of street transit systems, it does provide the necessary information about the Passenger Vehicle Interface for others to perform this optimization after they have assembled comparable information on system elements and other interactions.



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